The present disclosure relates to systems and techniques for querying databases and displaying queried data in an interactive user interface.
A database may store a large quantity of data. For example, a system may comprise a large number of sensors that each collect measurements at regular intervals, and the measurements may be stored in the database. The measurement data can be supplemented with other data, such as information regarding the locations where measured data was captured, and the supplemental data can also be stored in the database.
In some cases, a user may attempt to analyze a portion of the stored data. For example, the user may attempt to analyze a portion of the stored data that is associated with a specific location. However, as the number of measurements increases over time, it can become very difficult for the user to identify the relevant data and perform the analysis.
The systems, methods, and devices described herein each have several aspects, no single one of which is solely responsible for its desirable attributes. Without limiting the scope of this disclosure, several non-limiting features will now be discussed briefly.
Disclosed herein are various systems and methods for accessing data stored in one or more databases in substantially real-time in response to input from a user in order to determine associations between the data and physical locations and to provide the determined associations to the user in an interactive user interface. For example, the computing device may be configured to project a three-dimensional path onto a two-dimensional plane to generate a two-dimensional path, wherein the three-dimensional path corresponds to a trajectory in physical space and comprises a plurality of locations. In response to a received request specifying one or more attributes or event types associated with the three-dimensional path, wherein an event type is associated with one or more events, the computing system may access a database to retrieve data corresponding to the requested one or more attributes or event types, determine associations between the retrieved data and respective locations on the two-dimensional path, and generate user interface data for rendering an interactive user interface, wherein the user interface data includes the two-dimensional path and indications of at least a portion of the retrieved data at corresponding locations on the two-dimensional path, based upon the associations between the retrieved data and respective locations on the two-dimensional path.
In some embodiments, the three-dimensional path may comprise a three-dimensional model of the trajectory.
In some embodiments, the indications of at least a portion of the retrieved data at corresponding location on the two-dimensional path comprises one or more bars associated with the selected attributes or event types at the corresponding locations on the two-dimensional path, wherein a length of a bar of the one or more bars at a particular location is based at least in part upon a value associated with the attribute or event type associated with the bar at the particular location. For example, the request may specify at least a first attribute or event type and a second attribute or event type, wherein one or more bars associated with the first attribute or event type are overlaid on top of one or more bars associated with the second attribute or event type. In some embodiments, a bar of the one or more bars may correspond to at least two events associated with a path location of the bar, wherein a length of the bar is based at least in part upon an aggregate value associated with the at least two events. In some embodiments, in response to a selection of a bar of the one or more bars, the interactive user interface may display data corresponding to an attribute or event associated with the selected bar. In some embodiments, a bar of the one or more bars is displayed to be substantially perpendicular to a tangent of the path at a location on the two-dimensional path corresponding to the bar.
In some embodiments, determining associations between the retrieved data and respective locations on the two-dimensional path may comprise determining associations between the retrieved data and respective locations on the three-dimensional path, and determining associations between the locations on the three-dimensional path and respective locations on the two-dimensional path.
Another aspect of the disclosure provides a computing system configured to generate user interface data for rendering the interactive user interface on a computing device, the interface user interface including a map corresponding to a physical region. The computing system may further be configured to receive a selection specifying at least one attribute, access the database to identify attribute values associated with the selected at least one attribute, determine one or more associations between the identified attribute values and locations on the map, generate a heatmap corresponding to the map, based at least in part upon the determined one or more associations, and update the user interface data such that the interface user interface includes the heatmap overlaying the map.
In some embodiments, the at least one attribute may comprise a depth attribute or a thickness attribute of a geological layer. The at least one attribute may comprise a measurement value associated with a sensor or structure located on the map.
In some embodiments, the attribute values may comprise an aggregation of two or more different attributes. For example, the two or more different attributes may comprise a first thickness of a first geological layer and a second thickness of a second geological layer, wherein an attribute value associated with a particular location corresponds to a sum of the first thickness and the second thickness at the particular location.
In some embodiments, the computing system may be further configured to calculate one or more predicted attribute values, wherein the predicted attribute values are associated with locations that are not associated with the identified attribute values. Calculating a predicted attribute value may be based at least in part upon a distance between the location associated with the predicted attribute value and a location associated with an identified attribute value.
Another aspect of the disclosure provides a computing system configured to access data stored in one or more databases in substantially real-time in response to input from a user in order to determine information related to measured data points and provide the determined information to the user in an interactive user interface, the computing system comprising: a computer processor; a database storing parameter values associated with a first parameter for a plurality of physical structures; and a computer readable storage medium storing program instructions configured for execution by the computer processor in order to cause the computing system to: generate user interface data for rendering the interactive user interface on a computing device, the interactive user interface including a first container and a second container, wherein the first container comprises a geographic map depicting a location of the plurality of physical structures; receive a selection of the first parameter and a first parameter value; determine one or more physical structures in the plurality of physical structures associated with a parameter value greater than the first parameter value; update the user interface data such that the geographic map depicts a location of the determined one or more physical structures; and update the user interface data such that the second container comprises a histogram identifying a number of the determined one or more physical structures that are associated with a parameter value greater than the first parameter value.
In some embodiments, the computer readable storage medium further stores program instructions that cause the computing system to update the user interface data such that each icon representing the location of the determined one or more physical structures is shaded a color that corresponds with the parameter value associated with the respective physical structure.
In some embodiments, the computer readable storage medium further stores program instructions that cause the computing system to: receive a selection of a first icon in the geographic map representing a location of a first physical structure; receive a selection of a second icon in the geographic map representing a location of a second physical structure after receiving the selection of the first icon; and update the user interface data such that the interactive user interface displays a first depth graph associated with the first physical structure and a second depth graph associated with the second physical structure.
In some embodiments, the first depth graph is located to the left of the second depth graph in the interactive user interface. The first depth graph may comprise a geological layer at a first depth level and the second depth graph comprises a geological layer at a second depth level that is different than the first depth level, such that the geological layer in the first depth graph and the geological layer in the second depth graph are depicted in a different horizontal plane in the interactive user interface. The computer readable storage medium further may store program instructions that cause the computing system to: receive a selection of the geological layer in the first depth graph; and update the user interface data such that the geological layer in the first depth graph and the geological layer in the second depth graph are depicted in a same horizontal plane in the interactive user interface.
In some embodiments, the first depth graph comprises a first attribute graph plotting attribute values measured at different depths associated with the location of the first physical structure. The computer readable storage medium may further store program instructions that cause the computing system to: receive a selection of a second attribute graph plotting attribute values measured at different depths associated with the location of the second physical structure; and update the user interface data such that the first depth graph displays the second attribute graph adjacent to the first attribute graph. In some embodiments, the computer readable storage medium may, in response to a received indication that the second attribute graph is dragged over the first attribute graph, update the user interface data such that the first attribute graph reflects attribute values measured at different depths associated with the location of the first physical structure and the location of the second physical structure. In some embodiments, the first sensor reading graph comprises readings from a first sensor, wherein the second sensor reading graph comprises readings from a second sensor, and wherein the computer readable storage medium further stores program instructions that cause the computing system to: receive an indication that the second sensor reading graph is dragged over the first sensor reading graph; and update the user interface data such that the first sensor reading graph comprises the readings from the first sensor and the readings from the second sensor.
In some embodiments, the computer readable storage medium further stores program instructions that cause the computing system to: receive a selection of a first layer identifier in the geographic map, wherein a first geographic layer is associated with the first layer identifier; and update the user interface data such that the interactive user interface displays the first geographic layer in the geographic map under the depiction of the location of the plurality of physical structures.
Another aspect of the disclosure provides computing system configured to access one or more databases in substantially real-time in response to input from a user provided via an interactive user interface in order to display a preview of a shape in the interactive user interface, the computing system comprising: a computer processor; and a computer readable storage medium storing: a data structure including a plurality of shape files; and program instructions configured for execution by the computer processor to cause the computing system to: receive a search term; identify, in the data structure, a first shape file in the stored shape files that includes the search term, wherein the first shape file comprises a first file name with a first file extension; retrieve one or more shape files in the data structure that comprise the first file name, wherein each retrieved file comprises a file extension different than the first file extension; generate a shape preview based on data in the first shape file and data in the retrieved one or more shape files; and generate user interface data for rendering the interactive user interface on a computing device, the interactive user interface including the shape preview.
In some embodiments, one of metadata of the first file or code in the first file may comprise the search term.
In some embodiments, the computer readable storage medium may further store program instructions that cause the computing system to: receive a request to view a shape associated with the shape preview; and update the user interface data such that the interactive user interface comprises a geographic map and a representation of the shape in the geographic map.
In some embodiments, the shape preview comprises a depiction of a geological layer.
In some embodiments, the computer readable storage medium further stores program instructions that cause the computing system to: receive a request to rotate the shape preview from a first orientation to a second orientation; and update the user interface data such that the interactive user interface displays the shape preview in the second orientation.
In some embodiments, the computer readable storage medium further stores program instructions that cause the computing system to: receive a request to download the first file and each file in the one or more databases that comprises the first file name; and transmit the first file and each file in the one or more databases that comprises the first file name to a user device over a network.
In some embodiments, the computer readable storage medium further stores program instructions that cause the computing system to: receive a request to download the first file and each file in the one or more databases that comprises the first file name; aggregate the first file and each file in the one or more databases that comprises the first file name into a compressed data file; and transmit the compressed data file to the user device over the network.
In some embodiments, the content of each file in the one or more databases that comprises the first file name is not searchable. The shape preview may comprise a three-dimensional shape. The interactive user interface may further include a preview of text present in the first file. In some embodiments, at least a portion of a file name of each of the retrieved files comprises the first file name.
It has been noted that design of computer user interfaces “that are useable and easily learned by humans is a non-trivial problem for software developers.” (Dillon, A. (2003) User Interface Design. MacMillan Encyclopedia of Cognitive Science, Vol. 4, London: MacMillan, 453-458.) The present disclosure describes various embodiments of interactive and dynamic user interfaces that are the result of significant development. This non-trivial development has resulted in the user interfaces described herein which may provide significant cognitive and ergonomic efficiencies and advantages over previous systems. The interactive and dynamic user interfaces include improved human-computer interactions that may provide reduced mental workloads, improved decision-making, reduced work stress, and/or the like, for a user. For example, user interaction with the interactive user interfaces described herein may provide an optimized display of maps and charts and may enable a user to more quickly and accurately access, navigate, assess, and digest the map and chart data than previous systems.
Further, the interactive and dynamic user interfaces described herein are enabled by innovations in efficient interactions between the user interfaces and underlying systems and components. For example, disclosed herein are improved methods of displaying geographic maps, determining cross-section layer information along paths, generating heatmaps on geographic maps, projecting paths onto a two-dimensional plane, and associating event and/or attribute data with physical locations on a projected path. The interactions and presentation of data via the interactive user interfaces described herein may accordingly provide cognitive and ergonomic efficiencies and advantages over previous systems.
Various embodiments of the present disclosure provide improvements to various technologies and technological fields. For example, existing data analysis technology is limited in various ways, and various embodiments of the disclosure provide significant improvements over such technology. Additionally, various embodiments of the present disclosure are inextricably tied to computer technology. In particular, various embodiments rely on detection of user inputs via graphical user interfaces, calculation of cross-section data and/or other attribute data based on those user inputs, generation of heatmaps based upon user-selected attributes or aggregations of user-selected attributes, generation of a two-dimensional path projection from a three-dimensional path, automatically displaying indications of attribute values and/or events along the path projected at locations corresponding to the attributes values and/or events. Such features and others are intimately tied to, and enabled by, computer technology, and would not exist except for computer technology. For example, the interactions with displayed data described below in reference to various embodiments cannot reasonably be performed by humans alone, without the computer technology upon which they are implemented. Further, the implementation of the various embodiments of the present disclosure via computer technology enables many of the advantages described herein, including more efficient interaction with, and presentation of, various types of electronic image data.
Additional embodiments of the disclosure are described below in reference to the appended claims, which may serve as an additional summary of the disclosure.
In various embodiments, computer-implemented methods are disclosed in which, under control of one or more hardware computing devices configured with specific computer executable instructions, one or more aspects of the above-described embodiments (including one or more aspects of the appended claims) are implemented and/or performed.
In various embodiments, non-transitory computer-readable storage mediums storing software instructions are disclosed, wherein, in response to execution by a computing system having one or more hardware processors, the software instructions configure the computing system to perform operations comprising one or more aspects of the above-described embodiments (including one or more aspects of the appended claims).
Further, as described herein, various embodiments of the system may be configured and/or designed to generate user interface data useable for rendering the various interactive user interfaces described. The user interface data may be used by the system, and/or another computer system, device, and/or software program (for example, a browser program), to render the interactive user interfaces. The interactive user interfaces may be displayed on, for example, electronic displays (including, for example, touch-enabled displays).
The term “comprising” as used herein should be given an inclusive rather than exclusive interpretation. For example, a general purpose computer comprising one or more processors should not be interpreted as excluding other computer components, and may possibly include such components as memory, input/output devices, and/or network interfaces, among others.
Overview: Data Analysis Via Interactive User Interfaces
As described above, it can become very difficult for the user to identify relevant data and perform an analysis when a database includes a large amount of data. This may be especially true if the user would like to compare two or more data sets that include measurements captured over various geological layers, where the data sets correspond to measurements taken in physical apparatuses (such as by sensors in oil wells, mines, or geological formations). For example, in the case of structures such as mines or oil wells, users with different specialties (e.g., chemists, physicists, petroleum physicists, etc.) may analyze different portions of the data that correspond with their specialty. These analyses may then be combined and presented to a geologist or other user in a user interface that includes a geographic map. However, the displayed data is static as the analyses have already been performed. It may then be difficult or burdensome for the geologist or other user to try to identify trends in the data and/or isolate current or future issues with the sensors, structures, geological layers, and/or the like.
Accordingly, disclosed herein are various systems and methods for displaying various graphs in an interactive user interface in substantially real-time in response to input from a user in order to determine information related to measured data points and provide the determined information to the user in the interactive user interface. For example, a first computing device may be configured to retrieve data measured by various sensors and compress the retrieved data so that the compressed data can be transported to and stored in one or more databases in an efficient manner. The sensors may be located in various physical structures, such as oil wells, mines, or geological structures or formations, and may be at various depths above and/or below the ground or the ocean surface. The sensors may include any available type of sensor, such as temperature, pressure, humidity, etc. sensors. In one embodiment, a sensor array may be in the form of a cable, such as a fiber optic cable, to provide a distributed acoustic sensing (DAS) system. For example, a single fiber optic cable may become a sensing element that includes hundreds to thousands of sensors that can detect vibrations and/or other physical parameters. As pulsed light is transmitted through the fiber optic cable, the fiber optic cable may act as a distributed interferometer and an optoelectronic device coupled to the fiber optic cable (e.g., Optical Time Domain Reflectometer (OTDR) instrumentation) may monitor a backscatter noise signature (e.g., a coherent Rayleigh backscatter noise signature) in the fiber optic cable. The optoelectronic device may measure the intensity of the reflected light after the light pulse is transmitted and changes in the reflected intensity of successive light pulses from the same region in the fiber optic cable can be determined. The intensity of the reflected light may be dependent on a strain and/or a temperature at various locations around the fiber optic cable. The optoelectronic device may be able to detect variations in the strain and/or temperature simultaneously at all regions in the fiber optic cable. The fiber optic cable may be hundreds of meters long and the sensors may be spaced evenly (or unevenly) throughout. In other embodiments, other types of sensors may be used.
The one or more databases may be located on land and coupled to the sensors via a communication medium, such as a cable or a wireless connection. Each instance of data measured by a sensor may include a plurality of parameters. For example, each instance of measured data may include an amplitude of the measured data, a depth at which the data was measured, a time at which the data was measured, a frequency range of the measured data (which may correspond to an octave in a plurality of octaves), and/or other like parameters.
A second computing device (e.g., the computing system 1700 of
The systems and methods described herein may provide several benefits. For example, the systems and methods described herein may improve the usability of the user interface by providing geographic maps and graphs that can be manipulated by a user in a concurrent manner, thereby allowing the user to identify trends or other information associated with the geographic maps and/or graphs. As another example, the systems and methods described herein may reduce the processor load while the user is interacting with the user interfaces by presenting depth graphs in a concurrent manner such that the user may not have to request sensor data associated with different structures separately and have the second computing system use additional processing resources to load and display the sensor data. Thus, the systems and methods described herein may improve the usability of the user interface.
As used herein, a “geological layer” or “zone” can be any stratum (e.g., a layer of sedimentary rock or soil with internally consistent characteristics that are distinguished from the characteristics of other layers) or geological formation (e.g., a combination of strata that may have a comparable lithology, facies, or other similar properties). Examples of a geological layer may include Hastings Beds, Kimmeridge Clay, Oxford Clay, Ferris Formation, and/or the like.
References herein to “databases” may refer to any type of data structure for storing and/or organizing data, including, but not limited to, relational databases (for example, Oracle database, mySQL database, and the like), spreadsheets, XML files, and text files, among others. The various terms “database,” “data store,” and “data source” may be used interchangeably in the present disclosure.
While the disclosure is described herein with respect to particular applications, such as mining, oil wells, and/or the like, this is not meant to be limiting. For example, the systems and methods described herein may facilitate the display of data captured by or associated with any physical apparatus or structure. Such physical apparatuses or structures may be those that include sensors used to measure physical parameters.
Examples of Manipulating the Geographic Map in an Interactive User Interface
The window 120 may include a mini-map 140 that displays a larger geographic area than is depicted in the window 120 and indication of the portion of the larger geographic area that is depicted in the window 120 (e.g., via box 145). The user may adjust the portion of the larger geographic area that is depicted in the window 120 by moving the box 145 within the mini-map 140.
The user interface 100 may further include filters. For example, the user may select filters in drop-down box 150 and/or values associated with the selected filters to pare the data depicted in the window 120. As illustrated in
The user interface 100 may further include a histogram 160. The histogram 160 may be associated with a selected filter such that the histogram 160 provides a more detailed view of the number of structures that satisfy the selected filter. For example, the histogram 160 indicates a number of structures that have a gamma radiation within different value ranges, such as between 11-15 μR/h, between 16-20 μR/h, between 21-25 μR/h, and so on.
A marker 165 may be displayed adjacent to the histogram 160 and can be used by the user to further filter the number of structures displayed in the window 120. For example, as illustrated in
As illustrated in
Each depth graph may present a cross-section of the composition of the ground at a location of the respective structure. For example, the depth graph 370 includes a y-axis that that identifies various depth levels and that identifies the depth levels at which various geological layers or zones are located within or surrounding the structure #1. In addition, the depth graph 370 may include a line graph (or other such graph) that plots the values measured from a sensor within the structure #1 at the depth levels indicated along the y-axis. In some embodiments, these graphs that plot attribute values measured along different depth levels may be referred to as “sensor reading graphs” or “reading graphs.” The values may be measured from the sensor for a single instance of time. The user may be able to adjust a time-axis such that the depth graph 370 displays values measured from the sensor at different time instances (not shown). As described in greater detail below, the depth graphs are not limited to displaying the readings from one sensor. The user may add additional line graphs that concurrently plot the values measured from other sensors within an structure.
The depth view in the user interface 350 may further include a mini-map 375. The mini-map 375 may include a smaller version of the geographic map illustrated in the window 120 and display the selected icons, as described above with respect to
In an embodiment, the windows 360, 362, and 364 can be manipulated such that the order in which they are displayed in the user interface 350 can be adjusted. For example, windows 362 and 364 can be swapped as illustrated in
Displaying information about the structures in the correct order may aid users in identifying trends. For example, a user may wish to determine whether the geographic map is accurate in displaying information about the selected structures, such as whether the location, geological layers, and/or the like are correctly displayed. The order may also be important in viewing the progression in geological topologies, which may aid in identifying trends in the data or current or future issues with the sensors, structures, geological layers, and/or the like.
The user may further provide one or more parameters that are associated with structures (e.g., values derived from the sensors of the structures) that are of interest. The user may provide the parameters in any way as described herein.
The cross-plot graph 465 may plot the two selected parameters against each other for each selected structure. For example, as illustrated in
In some embodiments, the selected parameters apply to a portion of an structure. For example, the selected parameters may apply to a specific geological layer. Alternatively, the user may actively limit the selected parameters to apply to only a portion of an structure. The icons associated with the structures in the cross-plot graph 465 may be color shaded or otherwise graphically differentiated to indicate the geological layer to which the selected parameters correspond.
The box 468 may display regressions and/or equations used to plot the data in the cross-plot graph 465. The box 468 may further include a legend that identifies the geological layer that corresponds with each color shade (or other graphical differentiation).
As illustrated in
Once the desired sensor reading is selected, the sensor measurements may be displayed within a graph 520 in the window 364 as illustrated in
As illustrated in
For example, after the align button 710 is selected using the cursor 170, the geological layer “formation #3” may be selected using the cursor 170, as illustrated in
The data used to populate the user interfaces depicted in
In further embodiments, not shown, the user may select a button or link in the geographic map and/or the depth view that causes the generation of a report (e.g., in a PDF format) that provides information on a selected structure. Such information may include the displayed sensor readings, depths levels of the structure, geological layers within or surrounding the structure, one or more other attributes relating to the structure (e.g., physical attributes, production attributes, etc.), historical information regarding these attributes, and/or the like.
In further embodiments, the user may include annotations in the windows 360, 362, and/or 364. For example, an annotation may include text that is associated with the structure (e.g., for an oil well structure, that there is a drilling inconsistency at a certain depth level) associated with the window in which the annotation is placed. The annotation may be specific to a sensor reading, depth level, and/or geological layer. The annotation may be stored in a database such that the annotation is displayed each time the structure is selected in the future.
Overview: Document Search
As described above, a shape or formation, such as a three-dimensional shape or formation, may be rendered and displayed in a user interface based on data present in a plurality of files with different file extensions. One or more of the files in the plurality may include text; however, such text may not be searchable using standard operating system file system search applications. For example, the files may not be searchable because they are in a non-standard and/or proprietary format. The files may also be stored in different databases that are coupled to the same network or share drive. Thus, it may be difficult to identify a desired shape or formation without accessing the databases and individually opening each stored file.
Accordingly, disclosed herein are various systems and methods for accessing one or more databases in substantially real-time in response to input from a user provided in an interactive user interface in order to display a preview of a shape in the interactive user interface. For example, the user can enter a search term. One or more databases may be parsed to identify one or more files that match or closely match the search term. Once a file is identified, the one or more databases may be parsed again to identify one or more files that share the same name as the identified file, but that may have different file extensions. The identified files may be processed to generate a preview of a shape or other formation and the interactive user interface may display the preview. The user interface may be interactive in that the user can manipulate the preview (e.g., by rotating the shape or other formation), select to download the files used to generate the preview, and/or select to view the shape or formation within a geographic map.
The systems and methods described herein may provide several benefits. For example, the systems and methods described herein may improve the user experience by allowing the user to identify a desired shape or formation without having to open specific files until the shape or formation is located. As another example, the systems and methods described herein may reduce the processor load because the user may not be continuously requested and opening complex data files during the search for the desired shape or formation.
Example Process Flow and Search for a Shape in an Interactive User Interface
In block 802, a search term is received. For example, as illustrated in user interface 820 of
In block 804, one or more databases are accessed to identify a first file that includes the search term. For example, the payload or metadata associated with files of a certain file extension (e.g., .dbf) may be searched in the one or more databases to identify one or more files that include the search term somewhere in the file data.
In block 806, a name of the located file is determined and each file in the one or more databases that shares that name (or at least a relevant portion of the name) with the first file is retrieved. For example, files with different file extensions may otherwise share the same file name. Files with the same file name may include data that can be used to generate a shape or formation. In some embodiments, 5 files with different file extensions share the same name.
In block 808, a shape preview is generated based on the first file and the retrieved files. For example, a shape preview 840 may be displayed in a window 830 within the user interface 820, as illustrated in
The window 830 may further include information about the shape, such as the name, path, source, etc., and two buttons: an open shape button 850 and a download shape button 860. The open shape button 850 may, when selected by a user using the cursor 170, may open the shape corresponding to the shape preview 840 in a geographic map or other similar graph. The download shape button 860 may, when selected by a user using the cursor 170, zip or otherwise aggregate the first file and the retrieved files (e.g., into a folder) and transmit the zipped or aggregated files to the user's computing device.
Cross Section Paths
It is often desirable to be able to effectively analyze how different values may vary across different locations. For example, it can be useful to view the values of particular attributes along one or more paths, in order to analyze how the attribute value changes over different locations, and to predict attribute values at particular locations. For example, due to the expense of drilling new mines or oil wells, deciding where to drill a new mine or well can be a very important decision. In order to make informed decisions regarding how and where to drill, it is often important to effectively analyze the cross-section composition indicating depth levels of various geological layers or zones at or around potential well locations. For example, it may be beneficial to view cross-section information along one or more paths, in order to analyze the cross-section composition changes over different locations. Although the techniques disclosed herein are described using particular contexts, such as mining or drilling oil wells, it is understood that they may also be applied to other applications, such as geological surveys, market analysis, and/or any application involving data associated with geographic locations. In addition, while the present specification may refer to cross-section information, it is understood that the techniques discloses herein may be applied to other types of attributes having values that vary by location (e.g., precipitation levels, population density, and/or the like).
In some applications, it may not be sufficient to view the layer cross-section at single points on the map. Instead, it may be desirable to be able to view cross-section information along a line or path (e.g., to be able view how the thicknesses and/or depths of the layers vary by location).
Once path 912 has been defined, a cross-section panel 914 is displayed showing cross-section layer data along path 912. In some embodiments, a width of cross-section panel 914 may be based upon a length of path 912, while in other embodiments, cross-section panel 914 may have a predetermined width.
When the user moves cursor 906 over cross-section panel 914, the position of cursor 906 relative to cross-section panel 914 (e.g., a horizontal position and/or a vertical position) may be noted. In some embodiments, in response to the user moving cursor 906 over cross-section panel 914, a marker 916 may be displayed on path 912 indicating a corresponding location on path 912, based upon a horizontal position of cursor 906 relative to cross-section panel 914. For example, the left side of cross-section 914 may correspond with the left side endpoint of path 912, while the right side of cross-section 914 may correspond with the right side endpoint of path 912. If cursor 906 is placed halfway between the left and right sides of cross-section panel 914, marker 916 may be displayed halfway along path 912 (e.g., in the middle of the line that makes up path 912). If the user moves cursor 906 to be 25% the width of cross-section panel 914 away from the left edge of cross-section panel 914, marker 916 may be moved to be 25% of the length of path 912 away from the left side endpoint of path 912. In some embodiments, the left edge of cross-section panel 914 may correspond with the first endpoint of path 912 defined by the user, while the right edge of cross-section panel 914 may correspond with the last endpoint of path 912 defined by the user.
In some embodiments, when the cursor 906 is placed over cross-section panel 914, a layer of the cross-section that the cursor 906 is placed over may be determined. In some embodiments, a layer panel 918 may be displayed, indicating to the user the current layer that cursor 906 is placed over. Layer panel 918 may contain an indication of a color associated with the layer by cross-section panel 914, layer name, and/or other layer data.
In some embodiments, a user may draw multiple paths on map 902 For example,
In response to the user defining a second path 918, a second cross-section panel 920 may be displayed showing cross-section layer data along second path 918. In some embodiments, cross-section panel 920 is displayed as a two dimensional plane even when second path 918 comprises multiple lines and/or curved lines that are not on the same plane. In some embodiments, in response to cursor 906 being placed over second cross-section panel 920, marker 922 may be displayed along second path 918, indicating a location on second 918 corresponding to the relative horizontal position of cursor 906 over second cross-section panel 920. For example, if cursor 906 is located 30% the width of second cross-section panel 920 away from the left edge of second cross-section panel 920, marker 922 may be displayed to be 30% of the length of second path 918 away from a first endpoint (e.g., a left side endpoint) of second path 918.
At block 1004, one or more inputs specifying one or more paths on the displayed map may be received. In some embodiments, the inputs may comprise two or more endpoint locations, wherein the specified path comprises one or more straight lines connecting the endpoints. In some embodiments, the inputs may comprise one or more drawn paths. A path may comprise a straight line, one or more connected straight lines, a curved line, and/or any combination thereof.
At block 1006, a layer model of the map may be accessed and used to determine cross-section layer data along the one or more paths. In some embodiments, the layer model may comprise a 3-D layer cake model that indicates depths for various geological layers or zones at various locations, and may be generated based upon seismic surveys, drilling data, satellite imaging data, data from other types of sensors, prediction models, and/or the like. In some embodiments, cross-section layer data is generated for each path specified by the one or more inputs.
At block 1008, the determined cross-section layer data may be displayed to the user. In some embodiments, the cross-section layer data may be displayed as a panel (e.g., cross-section panel 914 and/or 920, as illustrated in
At block 1010, a location of a cursor on the displayed cross-section layer data may be identified. For example, a user may move a cursor (e.g., a mouse pointer) over a displayed cross-section panel.
At block 1012, a location on the one or more paths corresponding to the identified cursor location may be displayed. For example, a marker may be displayed on a path corresponding to the cross-section panel that the cursor is currently over, wherein the location of the marker along the path corresponds to a horizontal position of the cursor relative to the cross-section panel.
Heatmaps
In some embodiments, heatmaps may be used to view properties or attributes across large areas of a displayed map, and to analyze the distribution of attribute values over a geographic area. In some embodiments, different attributes may be used to generate heatmaps. For example, in the context of geological layers, attributes for which it may be desirable to be able to generate heatmaps may include layer depth and layer thickness. In addition, other attributes, such as rock type, layer hardness, GIIP (gas initially in place) density, permeability, and/or the like, may also be used to generate heatmaps. In some embodiments, certain types of attributes may be associated with specific geographic points on the map instead of being modelled across the entire map. For example, a particular attribute may be measured at specific locations using one or more sensors, or may correspond to an operation performed at one or more specific locations (e.g., an ROP (rate of penetration) attribute may indicate a rate at which a drill bit was able to penetrate through a particular rock layer, as measured by actual drilling data at particular locations). These types of attributes may be referred to as “metrics.” In some embodiments, different attributes may also be combined or aggregated. For example, a first attribute and a second attribute may be combined to form an aggregate attribute, and a heatmap created over the map based upon the aggregate attribute.
Once the user has selected a particular attribute, a heatmap corresponding to the selected attribute may be displayed on map 1102. In some embodiments, a three-dimensional layer model is used to determine the value of the selected attribute across the area of map 1102. In some embodiments, the heatmap may be divided into a plurality of sub-units. Each sub-unit may correspond to a pixel, a block, and/or any other type of subset of the heatmap. An attribute value (e.g., depth of the selected layer) may be calculated for each sub-unit of the heatmap, which may then be converted to a color value and displayed to the user.
In some embodiments, a heatmap bar 1112 may be displayed, which indicates to the user the range of depths that the colors of the heatmap signify. For example, in the illustrated embodiment, the minimum depth of the selected layer is 80 m (represented by a first color, such as blue), while the maximum depth is 120 m (represented by a second color, such as red). In some embodiments, the values shown in heatmap bar 1112 may change based upon the specific attribute (e.g., layer) that has been selected.
In some embodiments, additional layers or objects may be displayed on map 1102. A toolbar 1110 may be used to allow the user to select types of additional layers or objects to be displayed. For example, objects such as structures may be displayed on the map or removed from the map using toolbar 1102. In some embodiments, which objects are displayed on the map may be based upon an attribute of the objects, such as structure type, structure status (e.g., operational, non-operational, under construction, and/or the like), etc. In addition, additional layers (e.g., overlays) may be displayed on the map. These may include a road overlay, a rivers or terrain overlay, a facilities overlay, one or more grids, and/or the like.
In some embodiments, in order to display the heatmap, the metric values are determined for the geographic points on the map for which they are available (e.g., at the locations of particular structures). The metric values may then be converted into color values at those locations and displayed to the user. In some embodiments, predicted attribute values may be calculated for areas of the map that do not correspond to a measured value (e.g., locations on the map that do not correspond to a specific structure). The predicted attribute values may then be converted into colors values at those locations of the map. In some embodiments, the predicted attribute values for a particular location may be based at least in part upon a distance from the location to one or more structures for which metric values are available. In addition, the predicted attribute values may also be based upon the metric values associated with the one or more structures. For example, a location that is close to a structure having a metric value represented by a color (e.g., blue) may be colored substantially the same color, while a location that is further away from the structure may be colored a lighter color due to the greater distance between it and the structure, forming a gradient of heatmap colors. In some embodiments, a steepness of the gradient may be based at least in part upon a metric value associated with one or more nearby structures. For example, the predicted color values near a location having a high metric value may fade at a slower rate with increasing distance, as compared to the predicted color value of locations near a location having a lower metric value.
For example, the heatmap illustrated in
At block 1204, one or more data sources may be accessed to identify attribute values that are associated with the selected attribute. For example, in some embodiments a three-dimensional layer model may be used to identify attribute values such as layer depth, layer thickness, and/or the like. In some embodiments, attribute data may be stored in one or more databases (e.g., a relational data store). In some embodiments, attribute data may be associated with particular objects that may be displayed on the map (e.g., oil wells, sensor stations, and/or the like).
At block 1206, associations between the identified attribute values and location on the displayed map are determined. In some embodiments, the associations may be determined using the three-dimensional layer model. In some embodiments, an attribute value may be associated with an object such structure having geographic location data. In some embodiments, the map is divided into a plurality of sub-units (e.g., pixels, blocks, grid spaces, and/or the like). Attribute values associated with each sub-unit of the map may be aggregated into an aggregate value and converted into a color value to be displayed. In some embodiments where attribute values (e.g., metric values) are associated with particular objects or locations on the map, color values for other locations on the map may be associated with a predicted attribute value based at least in part upon a distance between the location and map locations having attribute values.
At block 1208, a heatmap is displayed based upon the determined associations between the attribute values and the map locations.
Depth View Cross-Section
In some embodiments, cross-section paths may be used to analyze the cross-section composition of the terrain between existing well locations. For instance, as illustrated in
In addition, in some embodiments a user may be able to specify additional attributes for display. For example, a sidebar 1308 may be used to allow a user to select a particular structure (e.g., oil well or mine) for which the user wishes to view additional attributes. The user may then select an attribute category, which may cause a list of attributes within that category to be displayed for selection. In some embodiments, the user may also be able to move the locations of currently displayed graphs. For example, a user may be able to drag and drop attribute graph 1306 to a different location for easier viewing (e.g., to the left of first depth graph 1302, to the right of second depth graph 1304, and/or the like).
In some embodiments, the depth data used to generate first and second depth graphs 1302 and 1304 may be generated using actual depth measurements during the drilling associated with a particular structure. On the other hand, the cross-section layer data of cross-section graph 1310 may be generated from a model (e.g., a layer cake model). As such, there may sometimes be a mismatch between the data shown in depth graphs 1302 and 1304 and cross-section graph 1310 (e.g., the left edge of cross-section graph 1310 may not match with first depth graph 1302, or the right edge of the cross-section graph 1310 may not match with second depth graph 1304). In some embodiments, this may be simply due to an offset between the axes of the depth graphs and the cross-section graph. In some embodiments, this mismatch may be used to revise or adjust the model used to generate cross-section graph 1310, in order to create a more accurate model.
Event Timelines
Operations performed on a structure may require the performance of a large number of different events and tasks. For example, because of the time and expense associated with drilling structures such as oil wells, it is often important to be able to view and analyze the progress of drilling over time, and the various tasks that are being performed.
In some embodiments, a user may select a particular time on timeline 1402 (e.g., at time 1404). In response to the user selection, information pertaining to the events/phases/tasks/activities occurring at the selected time may be displayed at display area 1406. For example, in the illustrated embodiment, time 1404 on timeline 1402 corresponds to a particular activity (“Activity 1”) of a drill event of a production phase of an onshore drill event. Display area 1406 may contain information pertaining to the activity at the selected time. The information may comprise one or more attributes corresponding to the activity, such as a status of equipment (e.g., a motor assembly) used in the activity, a speed of the activity, a hole condition at the time of the activity, and/or the like. In some embodiments, the attributes shown in the information may be based upon a type of activity associated with the selected time. In addition, display area 1406 may display a time range corresponding to the activity (e.g., a start time and an end time), as well as a breadcrumb trail indicating a hierarchy of levels associated with the selected time.
In some embodiments, the user may be able to select a specific level (e.g., the task level) when selecting a time 1404 in timeline 1402. For example, instead of displaying information corresponding to the RIH activity at the selected time, display area 1406 may instead display information associated with a higher level associated with the selected time (e.g., a drill task, production phase, or drill event). In some embodiments, the displayed information may comprise an aggregation of attributes associated with lower levels (e.g., information displayed for a drill task may comprise aggregated attributes of one or more activities associated with the drill task).
In some embodiments, a second display area 1408 may be used to display information for a particular time period associated with the selected time 1404 (e.g. the day corresponding to the selected time 1404). For example, the information may comprise a current status of the well, a forecast for the well, and/or the like. In some embodiments, the information may comprise aggregated attributes of activities/tasks/phases/events that took place during the time period.
Path Trajectories
In some embodiments, it may not only be important to be able to analyze the progress of events occurring over time, but also how these events are associated with different locations. Understanding where events are occurring may be just as important as knowing when they are occurring. For example, in the context of drilling, certain events may be correlated with certain drill depths, drill trajectories, or the suspected interface between different geological layers. By viewing where these events occur on the path or trajectory, these correlations may be identified.
As such, in some embodiments, attribute values and/or events may be associated with particular locations along the path (e.g., an attribute value may be associated with a location where it was measured, while an event may be associated with a location where it occurred). Locations along the three-dimensional model of the path may be mapped to locations on the two-dimensional projection of the path. Thus, each attribute value and/or event may be associated a particular location on the two-dimensional path projection.
In some embodiments, the attribute and/or event data may be displayed as one or more bars extending from various locations along path projection 1504, wherein a length of a bar at a given location on the path projection indicates a particular magnitude or measure of the attribute or event corresponding to the location. For example, the bars that comprise attribute data 1506 may indicate an amount of gamma radiation that is measured at various locations along path projection 1504. Similarly, the bars that comprise event data 1508 may indicate how many hours of non-productive time occurred at particular locations of the path projection 1504. In some embodiments, an event type may be associated with a plurality of different attributes. In such cases, the length of the bars corresponding to the events may be based upon a particular attribute associated with the event or an aggregation of one or more particular attributes associated with the event. For example, for NPT events, the length of a bar at a particular location along the path projection may indicate a length of time associated with NPT events at that location. In some embodiments, a bar at a particular location of the path may be displayed such that it is substantially perpendicular to a tangent of the path at the particular location.
In some embodiments, bars associated with different attributes and/or event types may be overlaid on top of each other. The bars associated with different attributes and/or event types may be rendered with different colors or shadings for visual clarity. In some embodiments, in order to improve visibility for bars associated with a particular attribute and/or event type, the user may be able to change the order in which the bars associated with different event types and/or attributes are overlaid. For example, in some embodiments the user may select an event or attribute at toolbar 1510 in order to display the bars corresponding to the selected attribute or event type may be displayed in front.
In some embodiments, a particular bar may correspond to multiple events. For example, multiple NPT events may have occurred at a particular location in the path. In some embodiments, when a user selects a particular bar associated with NPT events, pop-up 1512 may indicate the one or more NPT events that are the particular bar at the particular location of the path projection 1504. In some embodiments, attribute values (e.g., length of time and/or other attributes) may be displayed separately for each event. In addition, aggregate information for the events associated with the bar (e.g., number of events associated with the selected bar, aggregated attribute values such as total length of time, and/or the like) may also be displayed.
By being able to view attribute data and event data as it relates to different locations, correlations between different attributes, events, and/or path shape may be more easily identified. For example, by examining NPT events with respect to the path projection, correlations may potentially be identified between where non-productive time occurred and changes in the direction or curvature of the path, the depth of the path, and/or various attribute values such as gamma radiation. For instance, it may be found that a large amount of non-productive time occurs near a location where the path changes direction, or where there is a high amount of gamma radiation.
At block 1604, a request is received specifying one or more attributes or events. The request may comprise any combination of attributes or events that can be associated with locations on the path. For example, a requested attribute may be associated with data measured by one or more sensors at various locations on the path. At block 1606, one or more data sources are accessed in order to retrieve event and/or attribute data corresponding to the received request.
At block 1608, one or more associations between the retrieved data (event and/or attribute data) and locations on the displayed trajectory are determined. For example, attribute data obtained from a particular sensor at a particular location on the path may be associated with the location. Similarly, event data may be associated with path locations at which the event(s) occurred. In some embodiments, determining the associations between the retrieved data and locations on the displayed trajectory may comprise determining associations between the retrieved data and respective locations on the three-dimensional path, and determining associations between the locations on the three-dimensional path and respective locations on the two-dimensional projection of the path.
At block 1610, the trajectory is displayed with indications of the event and/or attribute data at corresponding locations on the trajectory. For example, in some embodiments, the event and/or attribute data may be displayed as one or more bars located at corresponding locations on the path, wherein a length of the bar corresponds to a value associated with the attribute or event. In some embodiments, each attribute and/or event type may be displayed as a different set of bars on the path that are overlaid on top of each other.
In some embodiments, multiple events associated with the same location on the path may be aggregated into a single bar, wherein a length of the bar corresponds to an aggregated value associated with the events. In some embodiments, a displayed bar may be selected by the user to view the underlying attribute or event data associated with the selected bar.
Implementation Mechanisms
According to one embodiment, the techniques described herein are implemented by one or more special-purpose computing devices. The special-purpose computing devices may be hard-wired to perform the techniques, or may include digital electronic devices such as one or more application-specific integrated circuits (ASICs) or field programmable gate arrays (FPGAs) that are persistently programmed to perform the techniques, or may include one or more general purpose hardware processors programmed to perform the techniques pursuant to program instructions in firmware, memory, other storage, or a combination. Such special-purpose computing devices may also combine custom hard-wired logic, ASICs, or FPGAs with custom programming to accomplish the techniques. The special-purpose computing devices may be desktop computer systems, server computer systems, portable computer systems, handheld devices, networking devices or any other device or combination of devices that incorporate hard-wired and/or program logic to implement the techniques.
Computing device(s) are generally controlled and coordinated by operating system software, such as iOS, Android, Chrome OS, Windows XP, Windows Vista, Windows 7, Windows 8, Windows Server, Windows CE, Unix, Linux, SunOS, Solaris, iOS, Blackberry OS, VxWorks, or other compatible operating systems. In other embodiments, the computing device may be controlled by a proprietary operating system. Conventional operating systems control and schedule computer processes for execution, perform memory management, provide file system, networking, I/O services, and provide a user interface functionality, such as a graphical user interface (“GUI”), among other things.
For example,
Computer system 1700 includes a bus 1702 or other communication mechanism for communicating information, and a hardware processor, or multiple processors, 1704 coupled with bus 1702 for processing information. Hardware processor(s) 1704 may be, for example, one or more general purpose microprocessors.
Computer system 1700 also includes a main memory 1706, such as a random access memory (RAM), cache and/or other dynamic storage devices, coupled to bus 1702 for storing information and instructions to be executed by processor 1704. Main memory 1706 also may be used for storing temporary variables or other intermediate information during execution of instructions to be executed by processor 1704. Such instructions, when stored in storage media accessible to processor 1704, render computer system 1700 into a special-purpose machine that is customized to perform the operations specified in the instructions. Main memory 1706 may also store cached data, such as zoom levels and maximum and minimum sensor values at each zoom level.
Computer system 1700 further includes a read only memory (ROM) 1708 or other static storage device coupled to bus 1702 for storing static information and instructions for processor 1704. A storage device 1710, such as a magnetic disk, optical disk, or USB thumb drive (Flash drive), etc., is provided and coupled to bus 1702 for storing information and instructions. For example, the storage device 1710 may store measurement data obtained from a plurality of sensors.
Computer system 1700 may be coupled via bus 1702 to a display 1712, such as a cathode ray tube (CRT) or LCD display (or touch screen), for displaying information to a computer user. For example, the display 1712 can be used to display any of the user interfaces described herein with respect to
Computing system 1700 may include a user interface module to implement a GUI that may be stored in a mass storage device as executable software codes that are executed by the computing device(s). This and other modules may include, by way of example, components, such as software components, object-oriented software components, class components and task components, processes, functions, attributes, procedures, subroutines, segments of program code, drivers, firmware, microcode, circuitry, data, databases, data structures, tables, arrays, and variables.
In general, the word “module,” as used herein, refers to logic embodied in hardware or firmware, or to a collection of software instructions, possibly having entry and exit points, written in a programming language, such as, for example, Java, Lua, C or C++. A software module may be compiled and linked into an executable program, installed in a dynamic link library, or may be written in an interpreted programming language such as, for example, BASIC, Perl, or Python. It will be appreciated that software modules may be callable from other modules or from themselves, and/or may be invoked in response to detected events or interrupts. Software modules configured for execution on computing devices may be provided on a computer readable medium, such as a compact disc, digital video disc, flash drive, magnetic disc, or any other tangible medium, or as a digital download (and may be originally stored in a compressed or installable format that requires installation, decompression or decryption prior to execution). Such software code may be stored, partially or fully, on a memory device of the executing computing device, for execution by the computing device. Software instructions may be embedded in firmware, such as an EPROM. It will be further appreciated that hardware modules may be comprised of connected logic units, such as gates and flip-flops, and/or may be comprised of programmable units, such as programmable gate arrays or processors. The modules or computing device functionality described herein are preferably implemented as software modules, but may be represented in hardware or firmware. Generally, the modules described herein refer to logical modules that may be combined with other modules or divided into sub-modules despite their physical organization or storage.
Computer system 1700 may implement the techniques described herein using customized hard-wired logic, one or more ASICs or FPGAs, firmware and/or program logic which in combination with the computer system causes or programs computer system 1700 to be a special-purpose machine. According to one embodiment, the techniques herein are performed by computer system 1700 in response to processor(s) 1704 executing one or more sequences of one or more instructions contained in main memory 1706. Such instructions may be read into main memory 1706 from another storage medium, such as storage device 1710. Execution of the sequences of instructions contained in main memory 1706 causes processor(s) 1704 to perform the process steps described herein. In alternative embodiments, hard-wired circuitry may be used in place of or in combination with software instructions.
The term “non-transitory media,” and similar terms, as used herein refers to any media that store data and/or instructions that cause a machine to operate in a specific fashion. Such non-transitory media may comprise non-volatile media and/or volatile media. Non-volatile media includes, for example, optical or magnetic disks, such as storage device 1710. Volatile media includes dynamic memory, such as main memory 1706. Common forms of non-transitory media include, for example, a floppy disk, a flexible disk, hard disk, solid state drive, magnetic tape, or any other magnetic data storage medium, a CD-ROM, any other optical data storage medium, any physical medium with patterns of holes, a RAM, a PROM, and EPROM, a FLASH-EPROM, NVRAM, any other memory chip or cartridge, and networked versions of the same.
Non-transitory media is distinct from but may be used in conjunction with transmission media. Transmission media participates in transferring information between non-transitory media. For example, transmission media includes coaxial cables, copper wire and fiber optics, including the wires that comprise bus 1702. Transmission media can also take the form of acoustic or light waves, such as those generated during radio-wave and infra-red data communications.
Various forms of media may be involved in carrying one or more sequences of one or more instructions to processor 1704 for execution. For example, the instructions may initially be carried on a magnetic disk or solid state drive of a remote computer. The remote computer can load the instructions into its dynamic memory and send the instructions over a telephone line using a modem. A modem local to computer system 1700 can receive the data on the telephone line and use an infra-red transmitter to convert the data to an infra-red signal. An infra-red detector can receive the data carried in the infra-red signal and appropriate circuitry can place the data on bus 1702. Bus 1702 carries the data to main memory 1706, from which processor 1704 retrieves and executes the instructions. The instructions received by main memory 1706 may retrieve and execute the instructions. The instructions received by main memory 1706 may optionally be stored on storage device 1710 either before or after execution by processor 1704.
Computer system 1700 also includes a communication interface 1718 coupled to bus 1702. Communication interface 1718 provides a two-way data communication coupling to a network link 1720 that is connected to a local network 1722. For example, communication interface 1718 may be an integrated services digital network (ISDN) card, cable modem, satellite modem, or a modem to provide a data communication connection to a corresponding type of telephone line. As another example, communication interface 1718 may be a local area network (LAN) card to provide a data communication connection to a compatible LAN (or WAN component to communicated with a WAN). Wireless links may also be implemented. In any such implementation, communication interface 1718 sends and receives electrical, electromagnetic or optical signals that carry digital data streams representing various types of information.
Network link 1720 typically provides data communication through one or more networks to other data devices. For example, network link 1720 may provide a connection through local network 1722 to a host computer 1724 or to data equipment operated by an Internet Service Provider (ISP) 1726. ISP 1726 in turn provides data communication services through the world wide packet data communication network now commonly referred to as the “Internet” 1728. Local network 1722 and Internet 1728 both use electrical, electromagnetic or optical signals that carry digital data streams. The signals through the various networks and the signals on network link 1720 and through communication interface 1718, which carry the digital data to and from computer system 1700, are example forms of transmission media.
Computer system 1700 can send messages and receive data, including program code, through the network(s), network link 1720 and communication interface 1718. In the Internet example, a server 1730 might transmit a requested code for an application program through Internet 1728, ISP 1726, local network 1722 and communication interface 1718.
The received code may be executed by processor 1704 as it is received, and/or stored in storage device 1710, or other non-volatile storage for later execution.
Each of the processes, methods, and algorithms described in the preceding sections may be embodied in, and fully or partially automated by, code modules executed by one or more computer systems or computer processors comprising computer hardware. The processes and algorithms may be implemented partially or wholly in application-specific circuitry.
The various features and processes described above may be used independently of one another, or may be combined in various ways. All possible combinations and subcombinations are intended to fall within the scope of this disclosure. In addition, certain method or process blocks may be omitted in some implementations. The methods and processes described herein are also not limited to any particular sequence, and the blocks or states relating thereto can be performed in other sequences that are appropriate. For example, described blocks or states may be performed in an order other than that specifically disclosed, or multiple blocks or states may be combined in a single block or state. The example blocks or states may be performed in serial, in parallel, or in some other manner. Blocks or states may be added to or removed from the disclosed example embodiments. The example systems and components described herein may be configured differently than described. For example, elements may be added to, removed from, or rearranged compared to the disclosed example embodiments.
Conditional language, such as, among others, “can,” “could,” “might,” or “may,” unless specifically stated otherwise, or otherwise understood within the context as used, is generally intended to convey that certain embodiments include, while other embodiments do not include, certain features, elements and/or steps. Thus, such conditional language is not generally intended to imply that features, elements and/or steps are in any way required for one or more embodiments or that one or more embodiments necessarily include logic for deciding, with or without user input or prompting, whether these features, elements and/or steps are included or are to be performed in any particular embodiment.
Any process descriptions, elements, or blocks in the flow diagrams described herein and/or depicted in the attached figures should be understood as potentially representing modules, segments, or portions of code which include one or more executable instructions for implementing specific logical functions or steps in the process. Alternate implementations are included within the scope of the embodiments described herein in which elements or functions may be deleted, executed out of order from that shown or discussed, including substantially concurrently or in reverse order, depending on the functionality involved, as would be understood by those skilled in the art.
It should be emphasized that many variations and modifications may be made to the above-described embodiments, the elements of which are to be understood as being among other acceptable examples. All such modifications and variations are intended to be included herein within the scope of this disclosure. The foregoing description details certain embodiments of the invention. It will be appreciated, however, that no matter how detailed the foregoing appears in text, the invention can be practiced in many ways. As is also stated above, it should be noted that the use of particular terminology when describing certain features or aspects of the invention should not be taken to imply that the terminology is being re-defined herein to be restricted to including any specific characteristics of the features or aspects of the invention with which that terminology is associated. The scope of the invention should therefore be construed in accordance with the appended claims and any equivalents thereof.
This application is a continuation of U.S. patent application Ser. No. 16/567,540, entitled “Interactive User Interfaces for Location-Based Data Analysis,” filed Sep. 11, 2019, which application is a continuation of U.S. patent application Ser. No. 15/852,613, entitled “Interactive User Interfaces for Location-Based Data Analysis,” filed Dec. 22, 2017, which application is a continuation of U.S. patent application Ser. No. 15/072,133, entitled “Interactive User Interfaces for Location-Based Data Analysis,” filed Mar. 16, 2016, which application claims benefit of U.S. Provisional Patent Application Ser. No. 62/133,857, entitled “Wireline Map and Descent Data Analysis System.” filed Mar. 16, 2015, and U.S. Provisional Patent Application Ser. No. 62/200,565, entitled “Displaying Attribute and Event Data Along Paths.” filed Aug. 3, 2015, each of which is hereby incorporated by reference in its entirety and for all purposes. Any and all applications for which a foreign or domestic priority claim is identified in the Application Data Sheet as filed with the present application are hereby incorporated by reference under 37 CFR 1.57.
Number | Name | Date | Kind |
---|---|---|---|
4899161 | Morin et al. | Feb 1990 | A |
4958305 | Piazza | Sep 1990 | A |
5109399 | Thompson | Apr 1992 | A |
5241625 | Epard et al. | Aug 1993 | A |
5283562 | Kaneko et al. | Feb 1994 | A |
5329108 | Lamoure | Jul 1994 | A |
5444619 | Hoskins | Aug 1995 | A |
5623590 | Becker et al. | Apr 1997 | A |
5632009 | Rao et al. | May 1997 | A |
5670987 | Doi et al. | Sep 1997 | A |
5754182 | Kobayashi | May 1998 | A |
5781195 | Marvin | Jul 1998 | A |
5781704 | Rossmo | Jul 1998 | A |
5798769 | Chiu et al. | Aug 1998 | A |
5845300 | Comer | Dec 1998 | A |
5884217 | Koyanagi | Mar 1999 | A |
5925091 | Ando | Jul 1999 | A |
5936631 | Yano et al. | Aug 1999 | A |
5999911 | Berg et al. | Dec 1999 | A |
6055569 | O'Brien et al. | Apr 2000 | A |
6057757 | Arrowsmith et al. | May 2000 | A |
6065026 | Cornelia et al. | May 2000 | A |
6091956 | Hollenberg | Jul 2000 | A |
6157747 | Szeliski et al. | Dec 2000 | A |
6161098 | Wallman | Dec 2000 | A |
6169552 | Endo et al. | Jan 2001 | B1 |
6173067 | Payton et al. | Jan 2001 | B1 |
6178432 | Cook et al. | Jan 2001 | B1 |
6219053 | Tachibana et al. | Apr 2001 | B1 |
6232971 | Haynes | May 2001 | B1 |
6237138 | Hameluck et al. | May 2001 | B1 |
6243706 | Moreau et al. | Jun 2001 | B1 |
6247019 | Davies | Jun 2001 | B1 |
6279018 | Kudrolli et al. | Aug 2001 | B1 |
6338066 | Martin et al. | Jan 2002 | B1 |
6341310 | Leshem et al. | Jan 2002 | B1 |
6366933 | Ball et al. | Apr 2002 | B1 |
6369835 | Lin | Apr 2002 | B1 |
6370538 | Lamping et al. | Apr 2002 | B1 |
6389289 | Voce et al. | May 2002 | B1 |
6414683 | Gueziec | Jul 2002 | B1 |
6430305 | Decker | Aug 2002 | B1 |
6456997 | Shukla | Sep 2002 | B1 |
6483509 | Rabenhorst | Nov 2002 | B1 |
6523019 | Borthwick | Feb 2003 | B1 |
6529900 | Patterson et al. | Mar 2003 | B1 |
6549944 | Weinberg et al. | Apr 2003 | B1 |
6560620 | Ching | May 2003 | B1 |
6581068 | Bensoussan et al. | Jun 2003 | B1 |
6584498 | Nguyen | Jun 2003 | B2 |
6594672 | Lampson et al. | Jul 2003 | B1 |
6631496 | Li et al. | Oct 2003 | B1 |
6642945 | Sharpe | Nov 2003 | B1 |
6662103 | Skolnick et al. | Dec 2003 | B1 |
6665683 | Meltzer | Dec 2003 | B1 |
6674434 | Chojnacki et al. | Jan 2004 | B1 |
6714936 | Nevin, III | Mar 2004 | B1 |
6742033 | Smith et al. | May 2004 | B1 |
6757445 | Knopp | Jun 2004 | B1 |
6775675 | Nwabueze et al. | Aug 2004 | B1 |
6792422 | Stride et al. | Sep 2004 | B1 |
6820135 | Dingman | Nov 2004 | B1 |
6828920 | Owen et al. | Dec 2004 | B2 |
6839745 | Dingari et al. | Jan 2005 | B1 |
6850317 | Mullins et al. | Feb 2005 | B2 |
6877137 | Rivette et al. | Apr 2005 | B1 |
6944821 | Bates et al. | Sep 2005 | B1 |
6967589 | Peters | Nov 2005 | B1 |
6976210 | Silva et al. | Dec 2005 | B1 |
6978419 | Kantrowitz | Dec 2005 | B1 |
6980984 | Huffman et al. | Dec 2005 | B1 |
6983203 | Wako | Jan 2006 | B1 |
6985950 | Hanson et al. | Jan 2006 | B1 |
7003566 | Codella et al. | Feb 2006 | B2 |
7036085 | Barros | Apr 2006 | B2 |
7043702 | Chi et al. | May 2006 | B2 |
7055110 | Kupka et al. | May 2006 | B2 |
7086028 | Davis et al. | Aug 2006 | B1 |
7103852 | Kairis, Jr. | Sep 2006 | B2 |
7139800 | Bellotti et al. | Nov 2006 | B2 |
7149366 | Sun | Dec 2006 | B1 |
7158878 | Rasmussen et al. | Jan 2007 | B2 |
7162475 | Ackerman | Jan 2007 | B2 |
7168039 | Bertram | Jan 2007 | B2 |
7171427 | Witkowski | Jan 2007 | B2 |
7174377 | Bernard et al. | Feb 2007 | B2 |
7194680 | Roy et al. | Mar 2007 | B1 |
7213030 | Jenkins | May 2007 | B1 |
7269786 | Malloy et al. | Sep 2007 | B1 |
7278105 | Kitts | Oct 2007 | B1 |
7290698 | Poslinski et al. | Nov 2007 | B2 |
7333998 | Heckerman et al. | Feb 2008 | B2 |
7370047 | Gorman | May 2008 | B2 |
7375732 | Arcas | May 2008 | B2 |
7379811 | Rasmussen et al. | May 2008 | B2 |
7379903 | Joseph | May 2008 | B2 |
7392254 | Jenkins | Jun 2008 | B1 |
7426654 | Adams et al. | Sep 2008 | B2 |
7441182 | Beilinson et al. | Oct 2008 | B2 |
7441219 | Perry et al. | Oct 2008 | B2 |
7454466 | Bellotti et al. | Nov 2008 | B2 |
7457706 | Malero et al. | Nov 2008 | B2 |
7467375 | Tondreau et al. | Dec 2008 | B2 |
7487139 | Fraleigh et al. | Feb 2009 | B2 |
7502786 | Liu et al. | Mar 2009 | B2 |
7519470 | Brasche et al. | Apr 2009 | B2 |
7525422 | Bishop et al. | Apr 2009 | B2 |
7529195 | Gorman | May 2009 | B2 |
7529727 | Arning et al. | May 2009 | B2 |
7529734 | Dirisala | May 2009 | B2 |
7539666 | Ashworth et al. | May 2009 | B2 |
7558677 | Jones | Jun 2009 | B2 |
7558822 | Fredricksen et al. | Jul 2009 | B2 |
7574409 | Patinkin | Aug 2009 | B2 |
7574428 | Leiserowitz et al. | Aug 2009 | B2 |
7579965 | Bucholz | Aug 2009 | B2 |
7596285 | Brown et al. | Sep 2009 | B2 |
7614006 | Molander | Nov 2009 | B2 |
7617232 | Gabbert et al. | Nov 2009 | B2 |
7617314 | Bansod et al. | Nov 2009 | B1 |
7620628 | Kapur et al. | Nov 2009 | B2 |
7627812 | Chamberlain et al. | Dec 2009 | B2 |
7634717 | Chamberlain et al. | Dec 2009 | B2 |
7653883 | Hotelling et al. | Jan 2010 | B2 |
7663621 | Allen et al. | Feb 2010 | B1 |
7693816 | Nemoto et al. | Apr 2010 | B2 |
7703021 | Flam | Apr 2010 | B1 |
7706817 | Bamrah et al. | Apr 2010 | B2 |
7712049 | Williams et al. | May 2010 | B2 |
7716077 | Mikurak | May 2010 | B1 |
7725530 | Sah et al. | May 2010 | B2 |
7725547 | Albertson et al. | May 2010 | B2 |
7730082 | Sah et al. | Jun 2010 | B2 |
7730109 | Rohrs et al. | Jun 2010 | B2 |
7747749 | Erikson et al. | Jun 2010 | B1 |
7756843 | Palmer | Jul 2010 | B1 |
7765489 | Shah et al. | Jul 2010 | B1 |
7770100 | Chamberlain et al. | Aug 2010 | B2 |
7791616 | Ioup et al. | Sep 2010 | B2 |
7805457 | Viola et al. | Sep 2010 | B1 |
7809703 | Balabhadrapatruni et al. | Oct 2010 | B2 |
7818658 | Chen | Oct 2010 | B2 |
7870493 | Pall et al. | Jan 2011 | B2 |
7872647 | Mayer et al. | Jan 2011 | B2 |
7877421 | Berger et al. | Jan 2011 | B2 |
7880921 | Dattilo et al. | Feb 2011 | B2 |
7890850 | Bryar et al. | Feb 2011 | B1 |
7894984 | Rasmussen et al. | Feb 2011 | B2 |
7899611 | Downs et al. | Mar 2011 | B2 |
7899796 | Borthwick et al. | Mar 2011 | B1 |
7917376 | Bellin et al. | Mar 2011 | B2 |
7920963 | Jouline et al. | Apr 2011 | B2 |
7933862 | Chamberlain et al. | Apr 2011 | B2 |
7941321 | Greenstein et al. | May 2011 | B2 |
7941336 | Robin-Jan | May 2011 | B1 |
7945852 | Pilskains | May 2011 | B1 |
7949960 | Roessler et al. | May 2011 | B2 |
7966199 | Frasher | May 2011 | B1 |
7958147 | Turner et al. | Jun 2011 | B1 |
7962281 | Rasmussen et al. | Jun 2011 | B2 |
7962495 | Jain et al. | Jun 2011 | B2 |
7962848 | Bertram | Jun 2011 | B2 |
7970240 | Chao et al. | Jun 2011 | B1 |
7971150 | Raskutti et al. | Jun 2011 | B2 |
7984374 | Caro et al. | Jul 2011 | B2 |
8001465 | Kudrolli et al. | Aug 2011 | B2 |
8001482 | Bhattiprolu et al. | Aug 2011 | B2 |
8010507 | Poston et al. | Aug 2011 | B2 |
8010545 | Stefik et al. | Aug 2011 | B2 |
8015487 | Roy et al. | Sep 2011 | B2 |
8024778 | Cash et al. | Sep 2011 | B2 |
8036632 | Cona et al. | Oct 2011 | B1 |
8036971 | Aymeloglu et al. | Oct 2011 | B2 |
8046283 | Burns | Oct 2011 | B2 |
8054756 | Chand et al. | Nov 2011 | B2 |
8065080 | Koch | Nov 2011 | B2 |
8073857 | Sreekanth | Dec 2011 | B2 |
8085268 | Carrino et al. | Dec 2011 | B2 |
8095434 | Puttick et al. | Jan 2012 | B1 |
8103543 | Zwicky | Jan 2012 | B1 |
8134457 | Velipasalar et al. | Mar 2012 | B2 |
8145703 | Frishert et al. | Mar 2012 | B2 |
8185819 | Sah et al. | May 2012 | B2 |
8191005 | Baier | May 2012 | B2 |
8200676 | Frank | Jun 2012 | B2 |
8214361 | Sandler et al. | Jul 2012 | B1 |
8214490 | Vos et al. | Jul 2012 | B1 |
8214764 | Gemmell et al. | Jul 2012 | B2 |
8225201 | Michael | Jul 2012 | B2 |
8229902 | Vishniac et al. | Jul 2012 | B2 |
8229947 | Fujinaga | Jul 2012 | B2 |
8230333 | Decherd et al. | Jul 2012 | B2 |
8271461 | Pike et al. | Sep 2012 | B2 |
8280880 | Aymeloglu et al. | Oct 2012 | B1 |
8290838 | Thakur et al. | Oct 2012 | B1 |
8290926 | Ozzie et al. | Oct 2012 | B2 |
8290942 | Jones et al. | Oct 2012 | B2 |
8290943 | Carbone et al. | Oct 2012 | B2 |
8301464 | Cave et al. | Oct 2012 | B1 |
8301904 | Gryaznov | Oct 2012 | B1 |
8302855 | Ma et al. | Nov 2012 | B2 |
8312367 | Foster | Nov 2012 | B2 |
8312546 | Alme | Nov 2012 | B2 |
8325178 | Doyle, Jr. | Dec 2012 | B1 |
8352881 | Champion et al. | Jan 2013 | B2 |
8368695 | Howell et al. | Feb 2013 | B2 |
8386377 | Xiong | Feb 2013 | B1 |
8396740 | Watson | Mar 2013 | B1 |
8397171 | Klassen et al. | Mar 2013 | B2 |
8400448 | Doyle, Jr. | Mar 2013 | B1 |
8407180 | Ramesh et al. | Mar 2013 | B1 |
8412234 | Gatmir-Motahari et al. | Apr 2013 | B1 |
8412707 | Mianji | Apr 2013 | B1 |
8422825 | Neophytou et al. | Apr 2013 | B1 |
8447722 | Ahuja et al. | May 2013 | B1 |
8452790 | Mianji | May 2013 | B1 |
8463036 | Ramesh et al. | Jun 2013 | B1 |
8473454 | Evanitsky et al. | Jun 2013 | B2 |
8484115 | Aymeloglu et al. | Jul 2013 | B2 |
8489331 | Kopf et al. | Jul 2013 | B2 |
8489641 | Seefeld et al. | Jul 2013 | B1 |
8498984 | Hwang et al. | Jul 2013 | B1 |
8508533 | Cervelli et al. | Aug 2013 | B2 |
8510743 | Hackborn et al. | Aug 2013 | B2 |
8514082 | Cova et al. | Aug 2013 | B2 |
8514229 | Cervelli et al. | Aug 2013 | B2 |
8515207 | Chau | Aug 2013 | B2 |
8527949 | Pleis | Sep 2013 | B1 |
8554579 | Tribble et al. | Oct 2013 | B2 |
8554653 | Falkenborg et al. | Oct 2013 | B2 |
8554709 | Goodson et al. | Oct 2013 | B2 |
8560413 | Quarterman | Oct 2013 | B1 |
8564596 | Carrino et al. | Oct 2013 | B2 |
8576229 | Dykes | Nov 2013 | B2 |
8577911 | Stepinski et al. | Nov 2013 | B1 |
8589273 | Creeden et al. | Nov 2013 | B2 |
8595234 | Siripurapu et al. | Nov 2013 | B2 |
8599203 | Horowitz et al. | Dec 2013 | B2 |
8620641 | Farnsworth et al. | Dec 2013 | B2 |
8646080 | Williamson et al. | Feb 2014 | B2 |
8639757 | Adams et al. | Mar 2014 | B1 |
8676857 | Adams et al. | Mar 2014 | B1 |
8682696 | Shanmugam | Mar 2014 | B1 |
8688573 | Rukonic et al. | Apr 2014 | B1 |
8689108 | Duffield et al. | Apr 2014 | B1 |
8713467 | Goldenberg et al. | Apr 2014 | B1 |
8726379 | Stiansen et al. | May 2014 | B1 |
8732574 | Burr et al. | May 2014 | B2 |
8739278 | Varghese | May 2014 | B2 |
8799799 | Cervelli et al. | May 2014 | B1 |
8742934 | Sarpy et al. | Jun 2014 | B1 |
8744890 | Bernier | Jun 2014 | B1 |
8745516 | Mason et al. | Jun 2014 | B2 |
8781169 | Jackson et al. | Jul 2014 | B2 |
8787939 | Papakipos et al. | Jul 2014 | B2 |
8788407 | Singh et al. | Jul 2014 | B1 |
8799313 | Satlow | Aug 2014 | B2 |
8807948 | Luo et al. | Aug 2014 | B2 |
8812960 | Sun et al. | Aug 2014 | B1 |
8830322 | Nerayoff et al. | Sep 2014 | B2 |
8832594 | Thompson et al. | Sep 2014 | B1 |
8868537 | Colgrove et al. | Oct 2014 | B1 |
8917274 | Ma et al. | Dec 2014 | B2 |
8924388 | Elliot et al. | Dec 2014 | B2 |
8924389 | Elliot et al. | Dec 2014 | B2 |
8924872 | Bogomolov et al. | Dec 2014 | B1 |
8930874 | Duff et al. | Jan 2015 | B2 |
8937619 | Sharma et al. | Jan 2015 | B2 |
8938434 | Jain et al. | Jan 2015 | B2 |
8938686 | Erenrich et al. | Jan 2015 | B1 |
8949164 | Mohler | Feb 2015 | B1 |
8983494 | Onnen et al. | Mar 2015 | B1 |
8984390 | Aymeloglu et al. | Mar 2015 | B2 |
9009171 | Grossman et al. | Apr 2015 | B1 |
9009177 | Zheng et al. | Apr 2015 | B2 |
9009827 | Albertson et al. | Apr 2015 | B1 |
9021260 | Falk et al. | Apr 2015 | B1 |
9021384 | Beard et al. | Apr 2015 | B1 |
9043696 | Meiklejohn et al. | May 2015 | B1 |
9043894 | Dennison et al. | May 2015 | B1 |
9058315 | Burr et al. | Jun 2015 | B2 |
9100428 | Visbal | Aug 2015 | B1 |
9104293 | Kornfeld et al. | Aug 2015 | B1 |
9104695 | Cervelli et al. | Aug 2015 | B1 |
9111380 | Piemonte et al. | Aug 2015 | B2 |
9116975 | Shankar et al. | Aug 2015 | B2 |
9129219 | Robertson et al. | Sep 2015 | B1 |
9146125 | Vulcano et al. | Sep 2015 | B2 |
9165100 | Begur et al. | Oct 2015 | B2 |
9182517 | Selman | Nov 2015 | B1 |
9280618 | Bruce et al. | Mar 2016 | B1 |
9501740 | Hiu | Nov 2016 | B2 |
9600146 | Cervelli et al. | Mar 2017 | B2 |
9696442 | Li | Jul 2017 | B2 |
9734217 | Kara et al. | Aug 2017 | B2 |
9852373 | De Stefano | Dec 2017 | B2 |
9891808 | Wilson et al. | Feb 2018 | B2 |
9953445 | Cervelli et al. | Apr 2018 | B2 |
10444940 | Cervelli et al. | Oct 2019 | B2 |
10444941 | Cervelli et al. | Oct 2019 | B2 |
10459619 | Wilson et al. | Oct 2019 | B2 |
10949071 | Wilson et al. | Mar 2021 | B2 |
20010021936 | Bertram | Sep 2001 | A1 |
20010030667 | Kelts | Oct 2001 | A1 |
20020003539 | Abe | Jan 2002 | A1 |
20020032677 | Moregenthaler et al. | Mar 2002 | A1 |
20020033848 | Sciammarella et al. | Mar 2002 | A1 |
20020065708 | Senay et al. | May 2002 | A1 |
20020091707 | Keller | Jul 2002 | A1 |
20020095360 | Joao | Jul 2002 | A1 |
20020095658 | Shulman | Jul 2002 | A1 |
20020103705 | Brady | Aug 2002 | A1 |
20020116120 | Ruiz et al. | Aug 2002 | A1 |
20020130867 | Yang et al. | Sep 2002 | A1 |
20020130906 | Miyaki | Sep 2002 | A1 |
20020130907 | Chi et al. | Sep 2002 | A1 |
20020147805 | Leshem et al. | Oct 2002 | A1 |
20020174201 | Ramer et al. | Nov 2002 | A1 |
20020194119 | Wright et al. | Dec 2002 | A1 |
20020196229 | Chen et al. | Dec 2002 | A1 |
20030028560 | Kudrolli et al. | Feb 2003 | A1 |
20030036848 | Sheha et al. | Feb 2003 | A1 |
20030036927 | Bowen | Feb 2003 | A1 |
20030039948 | Donahue | Feb 2003 | A1 |
20030052896 | Higgins et al. | Mar 2003 | A1 |
20030093755 | O'Carroll | May 2003 | A1 |
20030103049 | Kindratenko et al. | Jun 2003 | A1 |
20030126102 | Borthwick | Jul 2003 | A1 |
20030140106 | Raguseo | Jul 2003 | A1 |
20030144868 | MacIntyre et al. | Jul 2003 | A1 |
20030163352 | Surpin et al. | Aug 2003 | A1 |
20030200217 | Ackerman | Oct 2003 | A1 |
20030225755 | Iwayama et al. | Dec 2003 | A1 |
20030229848 | Arend et al. | Dec 2003 | A1 |
20040030492 | Fox et al. | Feb 2004 | A1 |
20040032432 | Baynger | Feb 2004 | A1 |
20040034570 | Davis | Feb 2004 | A1 |
20040039498 | Ollis et al. | Feb 2004 | A1 |
20040044648 | Anfindsen et al. | Mar 2004 | A1 |
20040064256 | Barinek et al. | Apr 2004 | A1 |
20040085318 | Hassler et al. | May 2004 | A1 |
20040095349 | Bito et al. | May 2004 | A1 |
20040098236 | Mayer et al. | May 2004 | A1 |
20040111410 | Burgoon et al. | Jun 2004 | A1 |
20040111480 | Yue | Jun 2004 | A1 |
20040123135 | Goddard | Jun 2004 | A1 |
20040126840 | Cheng et al. | Jul 2004 | A1 |
20040143602 | Ruiz et al. | Jul 2004 | A1 |
20040143796 | Lerner et al. | Jul 2004 | A1 |
20040153418 | Hanweck | Aug 2004 | A1 |
20040163039 | McPherson et al. | Aug 2004 | A1 |
20040175036 | Graham | Sep 2004 | A1 |
20040181554 | Heckerman et al. | Sep 2004 | A1 |
20040193600 | Kaasten et al. | Sep 2004 | A1 |
20040205492 | Newsome | Oct 2004 | A1 |
20040217884 | Samadani et al. | Nov 2004 | A1 |
20040221223 | Yu et al. | Nov 2004 | A1 |
20040236688 | Bozeman | Nov 2004 | A1 |
20040236711 | Nixon et al. | Nov 2004 | A1 |
20040260702 | Cragun et al. | Dec 2004 | A1 |
20040267746 | Marcjan et al. | Dec 2004 | A1 |
20050010472 | Quatse et al. | Jan 2005 | A1 |
20050027705 | Sadri et al. | Feb 2005 | A1 |
20050028094 | Allyn | Feb 2005 | A1 |
20050028191 | Sullivan et al. | Feb 2005 | A1 |
20050031197 | Knopp | Feb 2005 | A1 |
20050034062 | Bufkin et al. | Feb 2005 | A1 |
20050039116 | Slack-Smith | Feb 2005 | A1 |
20050039119 | Parks et al. | Feb 2005 | A1 |
20050065811 | Chu et al. | Mar 2005 | A1 |
20050080769 | Gemmell | Apr 2005 | A1 |
20050086207 | Heuer et al. | Apr 2005 | A1 |
20050091186 | Elish | Apr 2005 | A1 |
20050125715 | Franco et al. | Jun 2005 | A1 |
20050154628 | Eckart et al. | Jul 2005 | A1 |
20050154769 | Eckart et al. | Jul 2005 | A1 |
20050162523 | Darrell et al. | Jul 2005 | A1 |
20050166144 | Gross | Jul 2005 | A1 |
20050180330 | Shapiro | Aug 2005 | A1 |
20050182502 | Iyengar | Aug 2005 | A1 |
20050182793 | Keenan et al. | Aug 2005 | A1 |
20050183005 | Denoue et al. | Aug 2005 | A1 |
20050210409 | Jou | Sep 2005 | A1 |
20050223044 | Ashworth et al. | Oct 2005 | A1 |
20050246327 | Yeung et al. | Nov 2005 | A1 |
20050251786 | Citron et al. | Nov 2005 | A1 |
20050267652 | Allstadt et al. | Dec 2005 | A1 |
20060026120 | Carolan et al. | Feb 2006 | A1 |
20060026170 | Kreitler et al. | Feb 2006 | A1 |
20060026561 | Bauman et al. | Feb 2006 | A1 |
20060031779 | Theurer et al. | Feb 2006 | A1 |
20060045470 | Poslinski et al. | Mar 2006 | A1 |
20060047804 | Fredricksen et al. | Mar 2006 | A1 |
20060053097 | King et al. | Mar 2006 | A1 |
20060053170 | Hill et al. | Mar 2006 | A1 |
20060059139 | Robinson | Mar 2006 | A1 |
20060059423 | Lehmann et al. | Mar 2006 | A1 |
20060074866 | Chamberlain et al. | Apr 2006 | A1 |
20060074881 | Vembu et al. | Apr 2006 | A1 |
20060080139 | Mainzer | Apr 2006 | A1 |
20060080283 | Shipman | Apr 2006 | A1 |
20060080619 | Carlson et al. | Apr 2006 | A1 |
20060093222 | Saffer et al. | May 2006 | A1 |
20060129191 | Sullivan et al. | Jun 2006 | A1 |
20060129746 | Porter | Jun 2006 | A1 |
20060136513 | Ngo et al. | Jun 2006 | A1 |
20060139375 | Rasmussen et al. | Jun 2006 | A1 |
20060142949 | Helt | Jun 2006 | A1 |
20060143034 | Rothermel | Jun 2006 | A1 |
20060143075 | Carr et al. | Jun 2006 | A1 |
20060143079 | Basak et al. | Jun 2006 | A1 |
20060146050 | Yamauchi | Jul 2006 | A1 |
20060149596 | Surpin et al. | Jul 2006 | A1 |
20060155654 | Plessis et al. | Jul 2006 | A1 |
20060178915 | Chao | Aug 2006 | A1 |
20060197763 | Harrison et al. | Sep 2006 | A1 |
20060200384 | Arutunian et al. | Sep 2006 | A1 |
20060203337 | White | Sep 2006 | A1 |
20060218637 | Thomas et al. | Sep 2006 | A1 |
20060241974 | Chao et al. | Oct 2006 | A1 |
20060242040 | Rader | Oct 2006 | A1 |
20060242630 | Koike et al. | Oct 2006 | A1 |
20060251307 | Florin et al. | Nov 2006 | A1 |
20060259527 | Devarakonda et al. | Nov 2006 | A1 |
20060265417 | Amato et al. | Nov 2006 | A1 |
20060271277 | Hu et al. | Nov 2006 | A1 |
20060277460 | Forstall et al. | Dec 2006 | A1 |
20060279630 | Aggarwal et al. | Dec 2006 | A1 |
20060294223 | Glasgow et al. | Dec 2006 | A1 |
20070000999 | Kubo et al. | Jan 2007 | A1 |
20070011150 | Frank | Jan 2007 | A1 |
20070011304 | Error | Jan 2007 | A1 |
20070016363 | Huang et al. | Jan 2007 | A1 |
20070016435 | Bevington | Jan 2007 | A1 |
20070024620 | Muller-Fischer et al. | Feb 2007 | A1 |
20070038646 | Thota | Feb 2007 | A1 |
20070038962 | Fuchs et al. | Feb 2007 | A1 |
20070043686 | Teng et al. | Feb 2007 | A1 |
20070057966 | Ohno et al. | Mar 2007 | A1 |
20070061752 | Cory | Mar 2007 | A1 |
20070078832 | Ott et al. | Apr 2007 | A1 |
20070083541 | Fraleigh et al. | Apr 2007 | A1 |
20070094389 | Nussey et al. | Apr 2007 | A1 |
20070113164 | Hansen et al. | May 2007 | A1 |
20070115373 | Gallagher et al. | May 2007 | A1 |
20070136095 | Weinstein | Jun 2007 | A1 |
20070150369 | Zivin | Jun 2007 | A1 |
20070150801 | Chidlovskii et al. | Jun 2007 | A1 |
20070156673 | Maga | Jul 2007 | A1 |
20070162454 | D'Albora | Jul 2007 | A1 |
20070168871 | Jenkins | Jul 2007 | A1 |
20070174760 | Chamberlain et al. | Jul 2007 | A1 |
20070185850 | Walters et al. | Aug 2007 | A1 |
20070185867 | Maga | Aug 2007 | A1 |
20070185894 | Swain et al. | Aug 2007 | A1 |
20070188516 | Loup et al. | Aug 2007 | A1 |
20070192122 | Routson | Aug 2007 | A1 |
20070192265 | Chopin et al. | Aug 2007 | A1 |
20070198571 | Ferguson et al. | Aug 2007 | A1 |
20070208497 | Downs et al. | Sep 2007 | A1 |
20070208498 | Barker et al. | Sep 2007 | A1 |
20070208736 | Tanigawa et al. | Sep 2007 | A1 |
20070233709 | Abnous | Oct 2007 | A1 |
20070240062 | Christena et al. | Oct 2007 | A1 |
20070245339 | Bauman et al. | Oct 2007 | A1 |
20070258642 | Thota | Nov 2007 | A1 |
20070266336 | Nojima et al. | Nov 2007 | A1 |
20070284433 | Domenica et al. | Dec 2007 | A1 |
20070294643 | Kyle | Dec 2007 | A1 |
20070299697 | Friedlander et al. | Dec 2007 | A1 |
20080010605 | Frank | Jan 2008 | A1 |
20080016155 | Khalatian | Jan 2008 | A1 |
20080016216 | Worley et al. | Jan 2008 | A1 |
20080040275 | Paulsen et al. | Feb 2008 | A1 |
20080040684 | Crump | Feb 2008 | A1 |
20080051989 | Welsh | Feb 2008 | A1 |
20080052142 | Bailey et al. | Feb 2008 | A1 |
20080066052 | Wolfram | Mar 2008 | A1 |
20080069081 | Chand et al. | Mar 2008 | A1 |
20080077597 | Butler | Mar 2008 | A1 |
20080077642 | Carbone et al. | Mar 2008 | A1 |
20080082486 | Lermant et al. | Apr 2008 | A1 |
20080082578 | Hogue et al. | Apr 2008 | A1 |
20080091693 | Murthy | Apr 2008 | A1 |
20080098085 | Krane et al. | Apr 2008 | A1 |
20080103996 | Forman et al. | May 2008 | A1 |
20080104019 | Nath | May 2008 | A1 |
20080109714 | Kumar et al. | May 2008 | A1 |
20080126951 | Sood et al. | May 2008 | A1 |
20080133579 | Lim | Jun 2008 | A1 |
20080148398 | Mezack et al. | Jun 2008 | A1 |
20080155440 | Trevor et al. | Jun 2008 | A1 |
20080162616 | Gross et al. | Jul 2008 | A1 |
20080163073 | Becker et al. | Jul 2008 | A1 |
20080172607 | Baer | Jul 2008 | A1 |
20080177782 | Poston et al. | Jul 2008 | A1 |
20080192053 | Howell et al. | Aug 2008 | A1 |
20080195417 | Surpin et al. | Aug 2008 | A1 |
20080195474 | Lau et al. | Aug 2008 | A1 |
20080195608 | Clover | Aug 2008 | A1 |
20080208735 | Balet | Aug 2008 | A1 |
20080222295 | Robinson et al. | Sep 2008 | A1 |
20080223834 | Griffiths et al. | Sep 2008 | A1 |
20080229056 | Agarwal et al. | Sep 2008 | A1 |
20080243711 | Aymeloglu et al. | Oct 2008 | A1 |
20080249820 | Pathria et al. | Oct 2008 | A1 |
20080249983 | Meisels et al. | Oct 2008 | A1 |
20080255973 | El Wade et al. | Oct 2008 | A1 |
20080263468 | Cappione et al. | Oct 2008 | A1 |
20080267107 | Rosenberg | Oct 2008 | A1 |
20080270468 | Mao | Oct 2008 | A1 |
20080276167 | Michael | Nov 2008 | A1 |
20080278311 | Grange et al. | Nov 2008 | A1 |
20080288306 | MacIntyre et al. | Nov 2008 | A1 |
20080294678 | Gorman et al. | Nov 2008 | A1 |
20080301643 | Appleton et al. | Dec 2008 | A1 |
20080313132 | Hao et al. | Dec 2008 | A1 |
20080313243 | Poston et al. | Dec 2008 | A1 |
20090002492 | Velipasalar et al. | Jan 2009 | A1 |
20090012944 | Rodriguez et al. | Jan 2009 | A1 |
20090026170 | Tanaka et al. | Jan 2009 | A1 |
20090027418 | Maru et al. | Jan 2009 | A1 |
20090030915 | Winter et al. | Jan 2009 | A1 |
20090031401 | Cudich et al. | Jan 2009 | A1 |
20090043801 | LeClair et al. | Feb 2009 | A1 |
20090055251 | Shah et al. | Feb 2009 | A1 |
20090076845 | Bellin et al. | Mar 2009 | A1 |
20090088964 | Schaaf et al. | Apr 2009 | A1 |
20090089651 | Herberger et al. | Apr 2009 | A1 |
20090094166 | Aymeloglu et al. | Apr 2009 | A1 |
20090094187 | Miyaki | Apr 2009 | A1 |
20090094270 | Alirez | Apr 2009 | A1 |
20090094558 | Howard | Apr 2009 | A1 |
20090100018 | Roberts | Apr 2009 | A1 |
20090106178 | Chu | Apr 2009 | A1 |
20090112678 | Luzardo | Apr 2009 | A1 |
20090112745 | Stefanescu | Apr 2009 | A1 |
20090115786 | Shmiasaki et al. | May 2009 | A1 |
20090119309 | Gibson et al. | May 2009 | A1 |
20090125359 | Knapic | May 2009 | A1 |
20090125369 | Kloostra et al. | May 2009 | A1 |
20090125459 | Norton et al. | May 2009 | A1 |
20090132921 | Hwangbo et al. | May 2009 | A1 |
20090132953 | Reed et al. | May 2009 | A1 |
20090143052 | Bates et al. | Jun 2009 | A1 |
20090144262 | White et al. | Jun 2009 | A1 |
20090144274 | Fraleigh et al. | Jun 2009 | A1 |
20090150868 | Chakra et al. | Jun 2009 | A1 |
20090157732 | Hao et al. | Jun 2009 | A1 |
20090158185 | Lacevic et al. | Jun 2009 | A1 |
20090164934 | Bhattiprolu et al. | Jun 2009 | A1 |
20090171939 | Athsani et al. | Jul 2009 | A1 |
20090172511 | Decherd et al. | Jul 2009 | A1 |
20090172821 | Daira et al. | Jul 2009 | A1 |
20090177962 | Gusmorino et al. | Jul 2009 | A1 |
20090179892 | Tsuda et al. | Jul 2009 | A1 |
20090187447 | Cheng et al. | Jul 2009 | A1 |
20090187464 | Bai et al. | Jul 2009 | A1 |
20090187546 | Whyte et al. | Jul 2009 | A1 |
20090187548 | Ji et al. | Jul 2009 | A1 |
20090199106 | Jonsson et al. | Aug 2009 | A1 |
20090222400 | Kupershmidt et al. | Sep 2009 | A1 |
20090222759 | Drieschner | Sep 2009 | A1 |
20090222760 | Halverson et al. | Sep 2009 | A1 |
20090234720 | George et al. | Sep 2009 | A1 |
20090248593 | Putzolu et al. | Oct 2009 | A1 |
20090248757 | Havewala et al. | Oct 2009 | A1 |
20090249178 | Ambrosino et al. | Oct 2009 | A1 |
20090249244 | Robinson et al. | Oct 2009 | A1 |
20090254970 | Agarwal et al. | Oct 2009 | A1 |
20090271343 | Vaiciulis et al. | Oct 2009 | A1 |
20090281839 | Lynn et al. | Nov 2009 | A1 |
20090282068 | Shockro et al. | Nov 2009 | A1 |
20090287470 | Farnsworth et al. | Nov 2009 | A1 |
20090292626 | Oxford | Nov 2009 | A1 |
20090307049 | Elliott et al. | Dec 2009 | A1 |
20090313463 | Pang et al. | Dec 2009 | A1 |
20090319418 | Herz | Dec 2009 | A1 |
20090319891 | MacKinlay et al. | Dec 2009 | A1 |
20100011282 | Dollard et al. | Jan 2010 | A1 |
20100016910 | Sullivan et al. | Jan 2010 | A1 |
20100030722 | Goodson et al. | Feb 2010 | A1 |
20100031141 | Summers et al. | Feb 2010 | A1 |
20100031183 | Kang | Feb 2010 | A1 |
20100042922 | Bradateanu et al. | Feb 2010 | A1 |
20100049872 | Roskind | Feb 2010 | A1 |
20100057622 | Faith et al. | Mar 2010 | A1 |
20100057716 | Stefik et al. | Mar 2010 | A1 |
20100063961 | Guiheneuf et al. | Mar 2010 | A1 |
20100070523 | Delgo et al. | Mar 2010 | A1 |
20100070842 | Aymeloglu et al. | Mar 2010 | A1 |
20100070844 | Aymeloglu et al. | Mar 2010 | A1 |
20100070845 | Facemire et al. | Mar 2010 | A1 |
20100070897 | Aymeloglu et al. | Mar 2010 | A1 |
20100076968 | Boyns et al. | Mar 2010 | A1 |
20100088304 | Jackson | Apr 2010 | A1 |
20100088398 | Plamondon | Apr 2010 | A1 |
20100094548 | Tadman et al. | Apr 2010 | A1 |
20100098318 | Anderson | Apr 2010 | A1 |
20100100963 | Mahaffey | Apr 2010 | A1 |
20100103124 | Kruzeniski et al. | Apr 2010 | A1 |
20100106420 | Mattikalli et al. | Apr 2010 | A1 |
20100114887 | Conway et al. | May 2010 | A1 |
20100122152 | Chamberlain et al. | May 2010 | A1 |
20100131457 | Heimendinger | May 2010 | A1 |
20100131502 | Fordham | May 2010 | A1 |
20100161735 | Sharma | Jun 2010 | A1 |
20100162176 | Dunton | Jun 2010 | A1 |
20100185692 | Zhang et al. | Jul 2010 | A1 |
20100191563 | Schlaifer et al. | Jul 2010 | A1 |
20100198684 | Eraker et al. | Aug 2010 | A1 |
20100199225 | Coleman et al. | Aug 2010 | A1 |
20100223260 | Wu | Sep 2010 | A1 |
20100228812 | Uomini | Sep 2010 | A1 |
20100235915 | Memon et al. | Sep 2010 | A1 |
20100238174 | Haub et al. | Sep 2010 | A1 |
20100250412 | Wagner | Sep 2010 | A1 |
20100262688 | Hussain et al. | Oct 2010 | A1 |
20100262901 | DiSalvo | Oct 2010 | A1 |
20100277611 | Holt et al. | Nov 2010 | A1 |
20100280851 | Merkin | Nov 2010 | A1 |
20100280857 | Liu et al. | Nov 2010 | A1 |
20100293174 | Bennett et al. | Nov 2010 | A1 |
20100306713 | Geisner et al. | Dec 2010 | A1 |
20100306722 | LeHoty | Dec 2010 | A1 |
20100312837 | Bodapati et al. | Dec 2010 | A1 |
20100312858 | Mickens et al. | Dec 2010 | A1 |
20100313119 | Baldwin et al. | Dec 2010 | A1 |
20100313239 | Chakra et al. | Dec 2010 | A1 |
20100318924 | Frankel et al. | Dec 2010 | A1 |
20100321399 | Ellren et al. | Dec 2010 | A1 |
20100321871 | Diebel et al. | Dec 2010 | A1 |
20100325526 | Ellis et al. | Dec 2010 | A1 |
20100325581 | Finkelstein et al. | Dec 2010 | A1 |
20100328112 | Liu | Dec 2010 | A1 |
20100330801 | Rouh | Dec 2010 | A1 |
20100332324 | Khosravy et al. | Dec 2010 | A1 |
20110004498 | Readshaw | Jan 2011 | A1 |
20110022312 | McDonough et al. | Jan 2011 | A1 |
20110029526 | Knight et al. | Feb 2011 | A1 |
20110029641 | Fainberg et al. | Feb 2011 | A1 |
20110047159 | Baid et al. | Feb 2011 | A1 |
20110047540 | Williams et al. | Feb 2011 | A1 |
20110060753 | Shaked et al. | Mar 2011 | A1 |
20110061013 | Bilicki et al. | Mar 2011 | A1 |
20110066933 | Ludwig | Mar 2011 | A1 |
20110074788 | Regan et al. | Mar 2011 | A1 |
20110074811 | Hanson et al. | Mar 2011 | A1 |
20110078055 | Faribault et al. | Mar 2011 | A1 |
20110078173 | Seligmann et al. | Mar 2011 | A1 |
20110090085 | Belz et al. | Apr 2011 | A1 |
20110090254 | Carrino et al. | Apr 2011 | A1 |
20110093327 | Fordyce, III et al. | Apr 2011 | A1 |
20110099046 | Weiss et al. | Apr 2011 | A1 |
20110099133 | Chang et al. | Apr 2011 | A1 |
20110117878 | Barash et al. | May 2011 | A1 |
20110119100 | Ruhl et al. | May 2011 | A1 |
20110125372 | Ito | May 2011 | A1 |
20110131232 | Hill | Jun 2011 | A1 |
20110137766 | Rasmussen et al. | Jun 2011 | A1 |
20110153368 | Pierre et al. | Jun 2011 | A1 |
20110153384 | Horne et al. | Jun 2011 | A1 |
20110161096 | Buehler et al. | Jun 2011 | A1 |
20110161409 | Nair et al. | Jun 2011 | A1 |
20110167105 | Ramakrishnan et al. | Jul 2011 | A1 |
20110170799 | Carrino et al. | Jul 2011 | A1 |
20110173032 | Payne et al. | Jul 2011 | A1 |
20110173093 | Psota et al. | Jul 2011 | A1 |
20110179048 | Satlow | Jul 2011 | A1 |
20110185316 | Reid et al. | Jul 2011 | A1 |
20110208565 | Ross et al. | Aug 2011 | A1 |
20110208724 | Jones et al. | Aug 2011 | A1 |
20110213655 | Henkin | Sep 2011 | A1 |
20110218934 | Elser | Sep 2011 | A1 |
20110218955 | Tang | Sep 2011 | A1 |
20110219450 | McDougal et al. | Sep 2011 | A1 |
20110225198 | Edwards et al. | Sep 2011 | A1 |
20110225482 | Chan et al. | Sep 2011 | A1 |
20110238495 | Kang | Sep 2011 | A1 |
20110238553 | Raj et al. | Sep 2011 | A1 |
20110238690 | Arrasvuori et al. | Sep 2011 | A1 |
20110251951 | Kolkowtiz | Oct 2011 | A1 |
20110258158 | Resende et al. | Oct 2011 | A1 |
20110270604 | Qi et al. | Nov 2011 | A1 |
20110270705 | Parker | Nov 2011 | A1 |
20110270834 | Sokolan et al. | Nov 2011 | A1 |
20110289397 | Eastmond et al. | Nov 2011 | A1 |
20110289407 | Naik et al. | Nov 2011 | A1 |
20110289420 | Morioka et al. | Nov 2011 | A1 |
20110291851 | Whisenant | Dec 2011 | A1 |
20110295649 | Fine | Dec 2011 | A1 |
20110310005 | Chen et al. | Dec 2011 | A1 |
20110314007 | Dassa et al. | Dec 2011 | A1 |
20110314024 | Chang et al. | Dec 2011 | A1 |
20120004894 | Butler et al. | Jan 2012 | A1 |
20120011238 | Rathod | Jan 2012 | A1 |
20120011245 | Gillette et al. | Jan 2012 | A1 |
20120019559 | Siler et al. | Jan 2012 | A1 |
20120022945 | Falkenborg et al. | Jan 2012 | A1 |
20120036013 | Neuhaus et al. | Feb 2012 | A1 |
20120036434 | Oberstein | Feb 2012 | A1 |
20120050293 | Carlhian et al. | Mar 2012 | A1 |
20120054284 | Rakshit | Mar 2012 | A1 |
20120059853 | Jagota | Mar 2012 | A1 |
20120066166 | Curbera et al. | Mar 2012 | A1 |
20120066296 | Appleton et al. | Mar 2012 | A1 |
20120072825 | Sherkin et al. | Mar 2012 | A1 |
20120079363 | Folting et al. | Mar 2012 | A1 |
20120084117 | Tavares et al. | Apr 2012 | A1 |
20120084118 | Bai et al. | Apr 2012 | A1 |
20120084184 | Raleigh et al. | Apr 2012 | A1 |
20120084287 | Lakshminarayan et al. | Apr 2012 | A1 |
20120102013 | Martini | Apr 2012 | A1 |
20120106801 | Jackson | May 2012 | A1 |
20120117082 | Koperda et al. | May 2012 | A1 |
20120123989 | Yu et al. | May 2012 | A1 |
20120131512 | Takeuchi et al. | May 2012 | A1 |
20120137235 | Ts et al. | May 2012 | A1 |
20120144325 | Mital | Jun 2012 | A1 |
20120144335 | Abeln et al. | Jun 2012 | A1 |
20120158527 | Cannelongo et al. | Jun 2012 | A1 |
20120159307 | Chung et al. | Jun 2012 | A1 |
20120159362 | Brown et al. | Jun 2012 | A1 |
20120159363 | DeBacker et al. | Jun 2012 | A1 |
20120159399 | Bastide et al. | Jun 2012 | A1 |
20120170847 | Tsukidate | Jul 2012 | A1 |
20120173381 | Smith | Jul 2012 | A1 |
20120173985 | Peppel | Jul 2012 | A1 |
20120180002 | Campbell et al. | Jul 2012 | A1 |
20120188252 | Law | Jul 2012 | A1 |
20120196557 | Reich et al. | Aug 2012 | A1 |
20120196558 | Reich et al. | Aug 2012 | A1 |
20120197651 | Robinson et al. | Aug 2012 | A1 |
20120197657 | Prodanovic | Aug 2012 | A1 |
20120197660 | Prodanovich | Aug 2012 | A1 |
20120203708 | Psota et al. | Aug 2012 | A1 |
20120206469 | Hulubei et al. | Aug 2012 | A1 |
20120208636 | Feige | Aug 2012 | A1 |
20120215784 | King et al. | Aug 2012 | A1 |
20120221511 | Gibson et al. | Aug 2012 | A1 |
20120221553 | Wittmer et al. | Aug 2012 | A1 |
20120221580 | Barney | Aug 2012 | A1 |
20120226523 | Weiss | Sep 2012 | A1 |
20120226590 | Love et al. | Sep 2012 | A1 |
20120245976 | Kumar et al. | Sep 2012 | A1 |
20120246148 | Dror | Sep 2012 | A1 |
20120254129 | Wheeler et al. | Oct 2012 | A1 |
20120284345 | Costenaro et al. | Nov 2012 | A1 |
20120284670 | Kashik et al. | Nov 2012 | A1 |
20120290879 | Shibuya et al. | Nov 2012 | A1 |
20120296907 | Long et al. | Nov 2012 | A1 |
20120311684 | Paulsen et al. | Dec 2012 | A1 |
20120323888 | Osann, Jr. | Dec 2012 | A1 |
20120330801 | McDougal et al. | Dec 2012 | A1 |
20120330973 | Ghuneim et al. | Dec 2012 | A1 |
20130006426 | Healey et al. | Jan 2013 | A1 |
20130006725 | Simanek et al. | Jan 2013 | A1 |
20130006916 | McBride et al. | Jan 2013 | A1 |
20130016106 | Yip et al. | Jan 2013 | A1 |
20130018796 | Kolhatkar et al. | Jan 2013 | A1 |
20130021445 | Cossette-Pacheco et al. | Jan 2013 | A1 |
20130024268 | Manickavelu | Jan 2013 | A1 |
20130035863 | Selman | Feb 2013 | A1 |
20130039546 | Bae | Feb 2013 | A1 |
20130046635 | Grigg et al. | Feb 2013 | A1 |
20130046842 | Muntz et al. | Feb 2013 | A1 |
20130054306 | Bhalla | Feb 2013 | A1 |
20130057551 | Ebert et al. | Mar 2013 | A1 |
20130060786 | Serrano et al. | Mar 2013 | A1 |
20130061169 | Pearcy et al. | Mar 2013 | A1 |
20130073377 | Heath | Mar 2013 | A1 |
20130073454 | Busch | Mar 2013 | A1 |
20130076732 | Cervelli et al. | Mar 2013 | A1 |
20130078943 | Biage et al. | Mar 2013 | A1 |
20130086482 | Parsons | Apr 2013 | A1 |
20130096988 | Grossman et al. | Apr 2013 | A1 |
20130097482 | Marantz et al. | Apr 2013 | A1 |
20130100134 | Cervelli et al. | Apr 2013 | A1 |
20130110746 | Ahn | May 2013 | A1 |
20130110822 | Ikeda et al. | May 2013 | A1 |
20130110877 | Bonham et al. | May 2013 | A1 |
20130111320 | Campbell et al. | May 2013 | A1 |
20130117651 | Waldman et al. | May 2013 | A1 |
20130132398 | Pfiefle | May 2013 | A1 |
20130101159 | Rosen | Jun 2013 | A1 |
20130150004 | Rosen | Jun 2013 | A1 |
20130151148 | Parundekar et al. | Jun 2013 | A1 |
20130151305 | Akinola et al. | Jun 2013 | A1 |
20130151388 | Falkenborg et al. | Jun 2013 | A1 |
20130151453 | Bhanot et al. | Jun 2013 | A1 |
20130157234 | Gulli et al. | Jun 2013 | A1 |
20130166348 | Scotto | Jun 2013 | A1 |
20130166480 | Popescu et al. | Jun 2013 | A1 |
20130166550 | Buchmann et al. | Jun 2013 | A1 |
20130176321 | Mitchell et al. | Jul 2013 | A1 |
20130179420 | Park et al. | Jul 2013 | A1 |
20130185245 | Anderson | Jul 2013 | A1 |
20130185307 | El-Yaniv et al. | Jul 2013 | A1 |
20130208565 | Castellanos et al. | Aug 2013 | A1 |
20130224696 | Wolfe et al. | Aug 2013 | A1 |
20130225212 | Khan | Aug 2013 | A1 |
20130226318 | Procyk | Aug 2013 | A1 |
20130226953 | Markovich et al. | Aug 2013 | A1 |
20130232045 | Tai et al. | Sep 2013 | A1 |
20130238616 | Rose et al. | Sep 2013 | A1 |
20130246170 | Gross et al. | Sep 2013 | A1 |
20130246537 | Gaddala | Sep 2013 | A1 |
20130246597 | Iizawa et al. | Sep 2013 | A1 |
20130251233 | Yang et al. | Sep 2013 | A1 |
20130254900 | Sathish et al. | Sep 2013 | A1 |
20130262527 | Hunter et al. | Oct 2013 | A1 |
20130263019 | Castellanos et al. | Oct 2013 | A1 |
20130267207 | Hao et al. | Oct 2013 | A1 |
20130268520 | Fisher et al. | Oct 2013 | A1 |
20130279757 | Kephart | Oct 2013 | A1 |
20130282696 | John et al. | Oct 2013 | A1 |
20130282723 | Petersen et al. | Oct 2013 | A1 |
20130290011 | Lynn et al. | Oct 2013 | A1 |
20130290825 | Arndt et al. | Oct 2013 | A1 |
20130297619 | Chandarsekaran et al. | Nov 2013 | A1 |
20130298083 | Bertoldo et al. | Nov 2013 | A1 |
20130304770 | Boero et al. | Nov 2013 | A1 |
20130311375 | Priebatsch | Nov 2013 | A1 |
20130339891 | Blumenberg et al. | Dec 2013 | A1 |
20140000964 | Selman | Jan 2014 | A1 |
20140002489 | Sauder et al. | Jan 2014 | A1 |
20140012796 | Petersen et al. | Jan 2014 | A1 |
20140019936 | Cohanoff | Jan 2014 | A1 |
20140032506 | Hoey et al. | Jan 2014 | A1 |
20140033010 | Richardt et al. | Jan 2014 | A1 |
20140033120 | Bental et al. | Jan 2014 | A1 |
20140036621 | Lewis | Feb 2014 | A1 |
20140040371 | Gurevich et al. | Feb 2014 | A1 |
20140043337 | Cardno | Feb 2014 | A1 |
20140047319 | Eberlein | Feb 2014 | A1 |
20140047357 | Alfaro et al. | Feb 2014 | A1 |
20140048542 | Wakita et al. | Feb 2014 | A1 |
20140058914 | Song et al. | Feb 2014 | A1 |
20140059038 | McPherson et al. | Feb 2014 | A1 |
20140063020 | Den Herder | Mar 2014 | A1 |
20140067611 | Adachi et al. | Mar 2014 | A1 |
20140068487 | Steiger et al. | Mar 2014 | A1 |
20140074855 | Zhao et al. | Mar 2014 | A1 |
20140095273 | Tang et al. | Apr 2014 | A1 |
20140095509 | Patton | Apr 2014 | A1 |
20140108068 | Williams | Apr 2014 | A1 |
20140108380 | Gotz et al. | Apr 2014 | A1 |
20140108985 | Scott et al. | Apr 2014 | A1 |
20140123279 | Bishop et al. | May 2014 | A1 |
20140129261 | Bothwell et al. | May 2014 | A1 |
20140129936 | Richards | May 2014 | A1 |
20140136285 | Carvalho | May 2014 | A1 |
20140143009 | Brice et al. | May 2014 | A1 |
20140149436 | Bahrami et al. | May 2014 | A1 |
20140156194 | Lupin | Jun 2014 | A1 |
20140156527 | Grigg et al. | Jun 2014 | A1 |
20140157172 | Peery et al. | Jun 2014 | A1 |
20140164502 | Khodorenko et al. | Jun 2014 | A1 |
20140176606 | Narayan et al. | Jun 2014 | A1 |
20140189536 | Lange et al. | Jul 2014 | A1 |
20140195515 | Baker et al. | Jul 2014 | A1 |
20140195887 | Ellis et al. | Jul 2014 | A1 |
20140208281 | Ming | Jul 2014 | A1 |
20140214579 | Shen et al. | Jul 2014 | A1 |
20140218400 | O'Toole et al. | Aug 2014 | A1 |
20140222403 | Lepage et al. | Aug 2014 | A1 |
20140222521 | Chait | Aug 2014 | A1 |
20140222793 | Sadkin et al. | Aug 2014 | A1 |
20140229554 | Grunin et al. | Aug 2014 | A1 |
20140244284 | Smith | Aug 2014 | A1 |
20140244388 | Manouchehri et al. | Aug 2014 | A1 |
20140258246 | Lo Faro et al. | Sep 2014 | A1 |
20140267294 | Ma | Sep 2014 | A1 |
20140267295 | Sharma | Sep 2014 | A1 |
20140278106 | Mallet | Sep 2014 | A1 |
20140279824 | Tamayo | Sep 2014 | A1 |
20140310266 | Greenfield | Oct 2014 | A1 |
20140316911 | Gross | Oct 2014 | A1 |
20140333651 | Cervelli et al. | Nov 2014 | A1 |
20140337772 | Cervelli et al. | Nov 2014 | A1 |
20140344230 | Krause et al. | Nov 2014 | A1 |
20140351070 | Christner et al. | Nov 2014 | A1 |
20140358829 | Hurwitz | Dec 2014 | A1 |
20140361899 | Layson | Dec 2014 | A1 |
20140365965 | Bray et al. | Dec 2014 | A1 |
20140366132 | Stiansen et al. | Dec 2014 | A1 |
20150019394 | Unser et al. | Jan 2015 | A1 |
20150026622 | Roaldson et al. | Jan 2015 | A1 |
20150029176 | Baxter et al. | Jan 2015 | A1 |
20150046870 | Goldenberg et al. | Feb 2015 | A1 |
20150073929 | Psota et al. | Mar 2015 | A1 |
20150073954 | Braff | Mar 2015 | A1 |
20150088424 | Burlakov | Mar 2015 | A1 |
20150089353 | Folkening | Mar 2015 | A1 |
20150089424 | Duffield et al. | Mar 2015 | A1 |
20150095773 | Gonsalves et al. | Apr 2015 | A1 |
20150100897 | Sun et al. | Apr 2015 | A1 |
20150100907 | Erenrich et al. | Apr 2015 | A1 |
20150106170 | Bonica | Apr 2015 | A1 |
20150106379 | Elliot et al. | Apr 2015 | A1 |
20150112963 | Mojtahedi et al. | Apr 2015 | A1 |
20150134666 | Gattiker et al. | May 2015 | A1 |
20150135256 | Hoy et al. | May 2015 | A1 |
20150169694 | Longo et al. | Jun 2015 | A1 |
20150169709 | Kara et al. | Jun 2015 | A1 |
20150169726 | Kara et al. | Jun 2015 | A1 |
20150170077 | Kara et al. | Jun 2015 | A1 |
20150172396 | Longo et al. | Jun 2015 | A1 |
20150178825 | Huerta | Jun 2015 | A1 |
20150178877 | Bogomolov et al. | Jun 2015 | A1 |
20150186483 | Tappan | Jul 2015 | A1 |
20150186821 | Wang et al. | Jul 2015 | A1 |
20150187036 | Wang et al. | Jul 2015 | A1 |
20150187100 | Berry et al. | Jul 2015 | A1 |
20150188872 | White | Jul 2015 | A1 |
20150212663 | Papale et al. | Jul 2015 | A1 |
20150227295 | Meiklejohn et al. | Aug 2015 | A1 |
20150254220 | Burr et al. | Sep 2015 | A1 |
20150262396 | Devarajan | Sep 2015 | A1 |
20150287117 | Tan | Oct 2015 | A1 |
20150309719 | Ma et al. | Oct 2015 | A1 |
20150310645 | Baumecker | Oct 2015 | A1 |
20150312323 | Peterson | Oct 2015 | A1 |
20150317342 | Grossman et al. | Nov 2015 | A1 |
20150324868 | Kaftan et al. | Nov 2015 | A1 |
20150338233 | Cervelli et al. | Nov 2015 | A1 |
20150379413 | Robertson et al. | Dec 2015 | A1 |
20160004764 | Chakerian et al. | Jan 2016 | A1 |
20160026923 | Erenrich et al. | Jan 2016 | A1 |
20160055501 | Mukherjee et al. | Feb 2016 | A1 |
20160062555 | Ward et al. | Mar 2016 | A1 |
20160124116 | Souche | May 2016 | A1 |
20160274781 | Wilson et al. | Sep 2016 | A1 |
20170052654 | Cervelli et al. | Feb 2017 | A1 |
20170052655 | Cervelli et al. | Feb 2017 | A1 |
20170052747 | Cervelli et al. | Feb 2017 | A1 |
20180136831 | Wilson et al. | May 2018 | A1 |
20200042163 | Wilson et al. | Feb 2020 | A1 |
Number | Date | Country |
---|---|---|
2012216622 | May 2015 | AU |
2013251186 | Nov 2015 | AU |
2753946 | Sep 2010 | CA |
102546446 | Jul 2012 | CN |
103167093 | Jun 2013 | CN |
102054015 | May 2014 | CN |
113153882 | Jul 2021 | CN |
102014103482 | Sep 2014 | DE |
102014204827 | Sep 2014 | DE |
102014204830 | Sep 2014 | DE |
102014204834 | Sep 2014 | DE |
102013222023 | Jan 2015 | DE |
102014215621 | Feb 2015 | DE |
0763201 | Mar 1997 | EP |
1672527 | Jun 2006 | EP |
2487610 | Aug 2012 | EP |
2551799 | Jan 2013 | EP |
2560134 | Feb 2013 | EP |
2575107 | Apr 2013 | EP |
2778977 | Sep 2014 | EP |
2835745 | Feb 2015 | EP |
2835770 | Feb 2015 | EP |
2838039 | Feb 2015 | EP |
2846241 | Mar 2015 | EP |
2851852 | Mar 2015 | EP |
2858014 | Apr 2015 | EP |
2858018 | Apr 2015 | EP |
2863326 | Apr 2015 | EP |
2863346 | Apr 2015 | EP |
2869211 | May 2015 | EP |
2881868 | Jun 2015 | EP |
2884439 | Jun 2015 | EP |
2884440 | Jun 2015 | EP |
2889814 | Jul 2015 | EP |
2891992 | Jul 2015 | EP |
2892197 | Jul 2015 | EP |
2911078 | Aug 2015 | EP |
2911100 | Aug 2015 | EP |
2940603 | Nov 2015 | EP |
2940609 | Nov 2015 | EP |
2963595 | Jan 2016 | EP |
2988258 | Feb 2016 | EP |
2993595 | Mar 2016 | EP |
3070622 | Sep 2016 | EP |
3133510 | Feb 2017 | EP |
3139333 | Mar 2017 | EP |
3611632 | Feb 2020 | EP |
2516155 | Jan 2015 | GB |
2518745 | Apr 2015 | GB |
2012778 | Nov 2014 | NL |
2013306 | Feb 2015 | NL |
624557 | Dec 2014 | NZ |
WO 95032424 | Nov 1995 | WO |
WO 2000009529 | Feb 2000 | WO |
WO 01025906 | Apr 2001 | WO |
WO 01088750 | Nov 2001 | WO |
WO 2001098925 | Dec 2001 | WO |
WO 2002065353 | Aug 2002 | WO |
WO 2004057268 | Jul 2004 | WO |
WO 2005013200 | Feb 2005 | WO |
WO 2005104736 | Nov 2005 | WO |
WO 2005116851 | Dec 2005 | WO |
WO 2007133206 | Nov 2007 | WO |
WO 2008064207 | May 2008 | WO |
WO 2009061501 | May 2009 | WO |
WO 2009123975 | Oct 2009 | WO |
WO 2010000014 | Jan 2010 | WO |
WO 2010030913 | Mar 2010 | WO |
WO 2010030914 | Mar 2010 | WO |
WO 2011058507 | May 2011 | WO |
WO 2012119008 | Sep 2012 | WO |
WO 2013010157 | Jan 2013 | WO |
WO 2013102892 | Jul 2013 | WO |
Entry |
---|
Official Communication for European Patent Application No. 19186114.5 dated Sep. 1, 2021, 5 pages. |
“A First Look: Predicting Market Demand for Food Retail using a Huff Analysis,” TRF Policy Solutions, Jul. 2012, pp. 30. |
“A Quick Guide to UniProtKB Swiss-Prot & TrEMBL,” Sep. 2011, pp. 2. |
“Andy Turner's Gisruk 2012 Notes” <https://docs.google.com/document/d/1cTmxg7mVx5gd89lqblCYvCEnHA4QAivH4l4WpyPsqE4/edit?pli=1> printed Sep. 16, 2013 in 15 pages. |
“GrabUp—What a Timesaver!” http://atlchris.com/191/grabup/, Aug. 11, 2008, pp. 3. |
“HunchLab: Heat Map and Kernel Density Calculation for Crime Analysis,” Azavea Journal, printed from www.azavea.com/blogs/newsletter/v4i4/kernel-density-capabilities-added-to-hunchlab/ on Sep. 9, 2014, 2 pages. |
“Money Laundering Risks and E-Gaming: a European Overview and Assessment,” 2009, http://www.cf.ac.uk/socsi/resources/Levi_Final_Money_Laundering_Risks_egaming.pdf. |
“Potential Money Laundering Warning Signs,” snapshot taken 2003, https://web.archive.org/web/20030816090055/http:/finsolinc.com/ANTI-MONEY%20LAUNDERING%20TRAINING%20GUIDES.pdf. |
“Refresh CSS Ellipsis When Resizing Container—Stack Overflow,” Jul. 31, 2013, retrieved from internet http://stackoverflow.com/questions/17964681/refresh-css-ellipsis-when-resizing-container, retrieved on May 18, 2015. |
“The Fasta Program Package,” fasta-36.3.4, Mar. 25, 2011, pp. 29. |
“Using Whois Based Geolocation and Google Maps API for Support Cybercrime Investigations,” http://wseas.us/e-library/conferences/2013/Dubrovnik/TELECIRC/TELECIRC-32.pdf. |
“What Was It Again? Ways to Make Feature Tile Layers Interactive,” WordPress.com, published Jun. 12, 2011, retrieved from https://whatwasitagain.wordpress.com/2011/06/12/interactive-feature-tile-layers/, 7 pages. |
Abbey, Kristen, “Review of Google Docs,” May 1, 2007, pp. 2. |
About 80 Minutes, “Palantir in a Number of Parts—Part 6—Graph,” Mar. 21, 2013, pp. 1-6. |
Acklen, Laura, “Absolute Beginner's Guide to Microsoft Word 2003,” Dec. 24, 2003, pp. 15-18, 34-41, 308-316. |
Adams et al., “Worklets: a Service-Oriented Implementation of Dynamic Flexibility in Workflows,” R. Meersman, Z. Tari et al. (Eds.): OTM 2006, LNCS, 4275, pp. 291-308, 2006. |
Alur et al., “Chapter 2: IBM InfoSphere DataStage Stages,” IBM InfoSphere DataStage Data Flow and Job Design, Jul. 1, 2008, pp. 35-137. |
Amnet, “5 Great Tools for Visualizing Your Twitter Followers,” posted Aug. 4, 2010, http://www.amnetblog.com/component/content/article/115-5-grate-tools-for-visualizing-your-twitter-followers.html. |
Ananiev et al., “The New Modality API,” http://web.archive.org/web/20061211011958/http://java.sun.com/developer/technicalArticles/J2SE/Desktop/javase6/modality/ Jan. 21, 2006, pp. 8. |
Appacts, “Smart Thinking for Super Apps,” <http://www.appacts.com> Printed Jul. 18, 2013 in 4 pages. |
Apsalar, “Data Powered Mobile Advertising,” “Free Mobile App Analytics” and various analytics related screen shots <http://apsalar.com> Printed Jul. 18, 2013 in 8 pages. |
AskDrexel, “How to: Auto Save a Document Before Printing in Word 2007,” http://askdrexel.drexel.edu/app/answers/detail/a_id/2353/˜/how-to%3A-auto-save-a-document-before-printing-in-word-2007, Published Nov. 13, 2007, pp. 1. |
Barnes et al., “Viewshed Analysis”, GIS-ARC/INFO 2001, <www.evsc.virginia.edu/˜jhp7e/evsc466/student_pres/Rounds.pdf>. |
Bivand et al., “Bindings for the Geospatial Data Abstraction Library—Package ‘rgdal’,” Mar. 15, 2015, retrieved from the Internet: URL: https://mran.microsoft.com/snapshot/2015-03-29/web/packages/rgdal/rgdal.pdf, 49 pages. |
Bluttman et al., “Excel Formulas and Functions for Dummies,” 2005, Wiley Publishing, Inc., pp. 280, 284-286. |
Boyce, Jim, “Microsoft Outlook 2010 Inside Out,” Aug. 1, 2010, retrieved from the internet https://capdtron.files.wordpress.com/2013/01/outlook-2010-inside_out.pdf. |
Bugzilla@Mozilla, “Bug 18726—[feature] Long-click means of invoking contextual menus not supported,” http://bugzilla.mozilla.org/show_bug.cgi?id=18726 printed Jun. 13, 2013 in 11 pages. |
Canese et al., “Chapter 2: PubMed: the Bibliographic Database,” The NCBI Handbook, Oct. 2002, pp. 1-10. |
Capptain—Pilot Your Apps, <http://www.capptain.com> Printed Jul. 18, 2013 in 6 pages. |
Carver et al., “Real-Time Visibility Analysis and Rapid Viewshed Calculation Using a Voxel-Based Modelling Approach,” Gisruk 2012 Conference, April 11-13, Lancaster UK, Apr. 13, 2012, pp. 6. |
Celik, Tantek, “CSS Basic User Interface Module Level 3 (CSS3 UI),” Section 8 Resizing and Overflow, Jan. 17, 2012, retrieved from internet http://www.w3.org/TR/2012/WD-css3-ui-20120117/#resizing-amp-overflow retrieved on May 18, 2015. |
Chaudhuri et al., “An Overview of Business Intelligence Technology,” Communications of the ACM, Aug. 2011, vol. 54, No. 8. |
Chen et al., “Bringing Order to the Web: Automatically Categorizing Search Results,” CHI 2000, Proceedings of the SIGCHI conference on Human Factors in Computing Systems, Apr. 1-6, 2000, the Hague, the Netherlands, pp. 145-152. |
Chung, Chin-Wan, “Dataplex: an Access to Heterogeneous Distributed Databases,” Communications of the ACM, Association for Computing Machinery, Inc., vol. 33, No. 1, Jan. 1, 1990, pp. 70-80. |
Cohn, et al., “Semi-supervised clustering with user feedback,” Constrained Clustering: Advances in Algorithms, Theory, and Applications 4.1 (2003): 17-32. |
Conner, Nancy, “Google Apps: the Missing Manual,” May 1, 2008, pp. 15. |
Countly Mobile Analytics, <http://count.ly/> Printed Jul. 18, 2013 in 9 pages. |
Definition “Identify”, downloaded Jan. 22, 2015, 1 page. |
Definition “Overlay”, downloaded Jan. 22, 2015, 1 page. |
Delcher et al., “Identifying Bacterial Genes and Endosymbiont DNA with Glimmer,” BioInformatics, vol. 23, No. 6, 2007, pp. 673-679. |
Distimo—App Analytics, <http://www.distimo.com/app-analytics> Printed Jul. 18, 2013 in 5 pages. |
Dramowicz, Ela, “Retail Trade Area Analysis Using the Huff Model,” Directions Magazine, Jul. 2, 2005 in 10 pages, http://www.directionsmag.com/articles/retail-trade-area-analysis-using-the-huff-model/123411. |
Flurry Analytics, <http://www.flurry.com/> Printed Jul. 18, 2013 in 14 pages. |
Galliford, Miles, “Snaglt Versus Free Screen Capture Software: Critical Tools for Website Owners,” http://www.subhub.com/articles/free-screen-capture-software, Mar. 27, 2008, pp. 11. |
Gesher, Ari, “Palantir Screenshots in the Wild: Swing Sightings,” The Palantir Blog, Sep. 11, 2007, pp. 1-12. |
Ghosh, P., “A Solution of Polygon Containment, Spatial Planning, and Other Related Problems Using Minkowski Operations,” Computer Vision, Graphics, and Image Processing, 1990, vol. 49, pp. 1-35. |
GIS-NET 3 Public _ Department of Regional Planning. Planning & Zoning Information for Unincorporated LA County. Retrieved Oct. 2, 2013 from http://gis.planning.lacounty.gov/GIS-NET3_Public/Viewer.html. |
Golem XIV, “A Word About Banks and the Laundering of Drug Money,” Aug. 18, 2012, http://www.golemxiv.co.uk/2012/08/a-word-about-banks-and-the-laundering-of-drug-money/, 21 pages. |
Google Analytics Official Website—Web Analytics & Reporting, <http://www.google.com/analytics.index.html> Printed Jul. 18, 2013 in 22 pages. |
Gorr et al., “Crime Hot Spot Forecasting: Modeling and Comparative Evaluation”, Grant 98-IJ-CX-K005, May 6, 2002, 37 pages. |
Goswami, Gautam, “Quite Writly Said!,” One Brick at a Time, Aug. 21, 2005, pp. 7. |
Griffith, Daniel A., “A Generalized Huff Model,” Geographical Analysis, Apr. 1982, vol. 14, No. 2, pp. 135-144. |
Gu et al., “Record Linkage: Current Practice and Future Directions,” Jan. 15, 2004, pp. 32. |
Hansen et al., “Analyzing Social Media Networks with NodeXL: Insights from a Connected World”, Chapter 4, pp. 53-67 and Chapter 10, pp. 143-164, published Sep. 2010. |
Haralick et al., “Image Analysis Using Mathematical Morphology,” Pattern Analysis and Machine Intelligence, IEEE Transactions, Jul. 1987, vol. PAMI-9, No. 4, pp. 532-550. |
Hardesty, “Privacy Challenges: Analysis: It's Surprisingly Easy to Identify Individuals from Credit-Card Metadata,” MIT News on Campus and Around the World, MIT News Office, Jan. 29, 2015, 3 pages. |
Harville et al., “Mediabeads: an Architecture for Path-Enhanced Media Applications,” 2004 IEEE International Conference on Multimedia and Expo, Jun. 27-30, 2004, Taipei, Taiwan, vol. 1, pp. 455-458. |
Hibbert et al., “Prediction of Shopping Behavior Using a Huff Model Within a GIS Framework,” Healthy Eating in Context, Mar. 18, 2011, pp. 16. |
Hogue et al., “Thresher: Automating the Unwrapping of Semantic Content from the World Wide Web,” 14th International Conference on World Wide Web, WWW 2005: Chiba, Japan, May 10-14, 2005, pp. 86-95. |
Hua et al., “A Multi-attribute Data Structure with Parallel Bloom Filters for Network Services” HiPC 2006, LNCS 4297, pp. 277-288, 2006. |
Huang et al., “Systematic and Integrative Analysis of Large Gene Lists Using David Bioinformatics Resources,” Nature Protocols, 4.1, 2008, 44-57. |
Huff et al., “Calibrating the Huff Model Using ArcGIS Business Analyst,” ESRI, Sep. 2008, pp. 33. |
Huff, David L., “Parameter Estimation in the Huff Model,” ESRI, ArcUser, Oct.-Dec. 2003, pp. 34-36. |
International Search Report and Written Opinion in Application No. PCT/US2009/056703 dated Mar. 15, 2010. |
Ipbucker, C., “Inverse Transformation for Several Pseudo-cylindrical Map Projections Using Jacobian Matrix,” ICCSA 2009, Part 1 LNCS 5592, pp. 553-564. |
Jetscreenshot.com, “Share Screenshots via Internet in Seconds,” http://web.archive.org/web/20130807164204/http://www.jetscreenshot.com/, Aug. 7, 2013, pp. 1. |
Kahan et al., “Annotea: an Open RDF Infrastructure for Shared Web Annotations”, Computer Networks, Elsevier Science Publishers B.V., vol. 39, No. 5, dated Aug. 5, 2002, pp. 589-608. |
Keylines.com, “An Introduction to KeyLines and Network Visualization,” Mar. 2014, <http://keylines.com/wp-content/uploads/2014/03/KeyLines-White-Paper.pdf> downloaded May 12, 2014 in 8 pages. |
Keylines.com, “KeyLines Datasheet,” Mar. 2014, <http://keylines.com/wp-content/uploads/2014/03/KeyLines-datasheet.pdf> downloaded May 12, 2014 in 2 pages. |
Keylines.com, “Visualizing Threats: Improved Cyber Security Through Network Visualization,” Apr. 2014, <http://keylines.com/wp-content/uploads/2014/04/Visualizing-Threats1.pdf> downloaded May 12, 2014 in 10 pages. |
Kitts, Paul, “Chapter 14: Genome Assembly and Annotation Process,” The NCBI Handbook, Oct. 2002, pp. 1-21. |
Kontagent Mobile Analytics, <http://www.kontagent.com/> Printed Jul. 18, 2013 in 9 pages. |
Kwout, http://web.archive.org/web/20080905132448/http://www.kwout.com/ Sep. 5, 2008, pp. 2. |
LeSage, “Lecture 2: Mapping in Matlab,” Mar. 2004, retrieved from the Internet: URL: http://www4.fe.uc.pt/spatial/doc/lecture2.pdf, 40 pages. |
Levine, N., “Crime Mapping and the Crimestat Program,” Geographical Analysis, 2006, vol. 38, pp. 41-56. |
Li et al., “Interactive Multimodal Visual Search on Mobile Device,” IEEE Transactions on Multimedia, vol. 15, No. 3, Apr. 1, 2013, pp. 594-607. |
Liu, Tianshun, “Combining GIS and the Huff Model to Analyze Suitable Locations for a New Asian Supermarket in the Minneapolis and St. Paul, Minnesota USA,” Papers in Resource Analysis, 2012, vol. 14, pp. 8. |
Localytics—Mobile App Marketing & Analytics, <http://www.localytics.com/> Printed Jul. 18, 2013 in 12 pages. |
Lovelace et al., “Introduction to visualizing spatial data in R,” Jun. 25, 2014, retrieved from the Internet: URL: https://cran.microsoft.com/snapshot/2014-09-30/doc/contrib/intro-spatial-rl.pdf, 24 pages. |
MacWright, Tom, “Announcing MapBOX.JS 1.0 with Leaflet,” Mapbox.com blog, Apr. 18, 2013, retrieved from https://www.mapbox.com/blog/mapbox-js-with-leaflet/. |
Madden, Tom, “Chapter 16: The Blast Sequence Analysis Tool,” The NCBI Handbook, Oct. 2002, pp. 1-15. |
Mandagere, Nagapramod, “Buffer Operations in GIS,” <http://www-users.cs.umn.edu/˜npramod/enc_pdf.pdf> retrieved Jan. 28, 2010, pp. 7. |
Manno et al., “Introducing Collaboration in Single-user Applications through the Centralized Control Architecture,” 2010, pp. 10. |
Manske, “File Saving Dialogs,” <http://www.mozilla.org/editor/ui_specs/FileSaveDialogs.html>, Jan. 20, 1999, pp. 7. |
Map Builder, “Rapid Mashup Development Tool for Google and Yahoo Maps!” <http://web.archive.org/web/20090626224734/http://www.mapbuilder.net/> printed Jul. 20, 2012 in 2 pages. |
Map of San Jose, CA. Retrieved Oct. 2, 2013 from http://maps.yahoo.com. |
Map of San Jose, CA. Retrieved Oct. 2, 2013 from http://maps.bing.com. |
Map of San Jose, CA. Retrieved Oct. 2, 2013 from http://maps.google.com. |
Microsoft—Developer Network, “Getting Started with VBA in Word 2010,” Apr. 2010, <http://msdn.microsoft.com/en-us/library/ff604039%28v=office.14%29.aspx> as printed Apr. 4, 2014 in 17 pages. |
Microsoft Office—Visio, “About connecting shapes,” <http://office.microsoft.com/en-US/visio-help/about-connecting-shapes-HP085050369.aspx> printed Aug. 4, 2011 in 6 pages. |
Microsoft Office—Visio, “Add and glue connectors with the Connector tool,” <http://office.microsoft.com/en-us/visio-help/add-and-glue-connectors-with-the-connector-tool-HA010048532.aspx?CTT=1> printed Aug. 4, 2011 in 1 page. |
Microsoft Windows, “Microsoft Windows Version 2002 Print Out 2,” 2002, pp. 1-6. |
Microsoft, “Registering an Application to a URI Scheme,” http://msdn.microsoft.com/en-us/library/aa767914.aspx, printed Apr. 4, 2009 in 4 pages. |
Microsoft, “Using the Clipboard,” http://msdn.microsoft.com/en-us/library/ms649016.aspx, printed Jun. 8, 2009 in 20 pages. |
Mixpanel—Mobile Analytics, <https://mixpanel.com/> Printed Jul. 18, 2013 in 13 pages. |
Mizrachi, Ilene, “Chapter 1: GenBank: the Nuckeotide Sequence Database,” the NCBI Handbook, Oct. 2002, pp. 1-14. |
Murray, C., Oracle Spatial Developer's Guide—6 Coordinate Systems (Spatial Reference Systems), <http://docs.oracle.com/cd/B28359_01/appdev.111/b28400.pdf>, Jun. 2009. |
Nierman, “Evaluating Structural Similarity in XML Documents”, 6 pages, 2002. |
Nitro, “Trick: How to Capture a Screenshot as PDF, Annotate, Then Share It,” http://blog.nitropdf.com/2008/03/04/trick-how-to-capture-a-screenshot-as-pdf-annotate-it-then-share/, Mar. 4, 2008, pp. 2. |
Nolan et al., “McArta: a Malicious Code Automated Run-Time Analysis Framework,” Homeland Security, 2012 IEEE Conference on Technologies for, Nov. 13, 2012, pp. 13-17. |
Notice of Acceptance for Australian Patent Application No. 2012216622 dated Jan. 6, 2015. |
Notice of Acceptance for Australian Patent Application No. 2013251186 dated Nov. 6, 2015. |
Notice of Acceptance for Australian Patent Application No. 2014250678 dated Oct. 7, 2015. |
Notice of Allowance for U.S. Appl. No. 12/556,318 dated Nov. 2, 2015. |
Notice of Allowance for U.S. Appl. No. 12/840,673 dated Apr. 6, 2015. |
Notice of Allowance for U.S. Appl. No. 13/728,879 dated Jun. 21, 2016. |
Notice of Allowance for U.S. Appl. No. 13/948,859 dated Dec. 10, 2014. |
Notice of Allowance for U.S. Appl. No. 14/102,394 dated Aug. 25, 2014. |
Notice of Allowance for U.S. Appl. No. 14/108,187 dated Aug. 29, 2014. |
Notice of Allowance for U.S. Appl. No. 14/135,289 dated Oct. 14, 2014. |
Notice of Allowance for U.S. Appl. No. 14/148,568 dated Aug. 26, 2015. |
Notice of Allowance for U.S. Appl. No. 14/192,767 dated Dec. 16, 2014. |
Notice of Allowance for U.S. Appl. No. 14/225,084 dated May 4, 2015. |
Notice of Allowance for U.S. Appl. No. 14/265,637 dated Feb. 13, 2015. |
Notice of Allowance for U.S. Appl. No. 14/268,964 dated Dec. 3, 2014. |
Notice of Allowance for U.S. Appl. No. 14/294,098 dated Dec. 29, 2014. |
Notice of Allowance for U.S. Appl. No. 14/319,161 dated May 4, 2015. |
Notice of Allowance for U.S. Appl. No. 14/319,765 dated Nov. 25, 2016. |
Notice of Allowance for U.S. Appl. No. 14/323,881 dated Jun. 30, 2017. |
Notice of Allowance for U.S. Appl. No. 14/323,935 dated Oct. 1, 2015. |
Notice of Allowance for U.S. Appl. No. 14/326,738 dated Nov. 18, 2015. |
Notice of Allowance for U.S. Appl. No. 14/473,552 dated Jul. 24, 2015. |
Notice of Allowance for U.S. Appl. No. 14/473,860 dated Jan. 5, 2015. |
Notice of Allowance for U.S. Appl. No. 14/479,863 dated Mar. 31, 2015. |
Notice of Allowance for U.S. Appl. No. 14/486,991 dated May 1, 2015. |
Notice of Allowance for U.S. Appl. No. 14/504,103 dated May 18, 2015. |
Notice of Allowance for U.S. Appl. No. 14/552,336 dated Nov. 3, 2015. |
Notice of Allowance for U.S. Appl. No. 14/616,080 dated Apr. 2, 2015. |
Notice of Allowance for U.S. Appl. No. 14/730,123 dated Apr. 12, 2016. |
Notice of Allowance for U.S. Appl. No. 14/746,671 dated Jan. 21, 2016. |
Notice of Allowance for U.S. Appl. No. 14/934,004 dated Nov. 4, 2016. |
Notice of Allowance for U.S. Appl. No. 15/072,133 dated Jun. 23, 2017. |
Notice of Allowance for U.S. Appl. No. 15/072,133 dated Sep. 25, 2017. |
Notice of Allowance for U.S. Appl. No. 14/323,878 dated Mar. 14, 2019. |
Notice of Allowance for U.S. Appl. No. 15/146,841 dated Jun. 21, 2019. |
Notice of Allowance for U.S. Appl. No. 15/146,842 dated Jun. 12, 2019. |
Official Communication for Australian Patent Application No. 2010227081 dated Mar. 18, 2011. |
Official Communication for Australian Patent Application No. 2010257305 dated Apr. 12, 2011. |
Official Communication for Australian Patent Application No. 2010257305 dated Sep. 22, 2011. |
Official Communication for Australian Patent Application No. 2012216622 dated Jan. 6, 2015. |
Official Communication for Australian Patent Application No. 2013251186 dated Mar. 12, 2015. |
Official Communication for Australian Patent Application No. 2014201511 dated Feb. 27, 2015. |
Official Communication for Australian Patent Application No. 2014202442 dated Mar. 19, 2015. |
Official Communication for Australian Patent Application No. 2014210604 dated Jun. 5, 2015. |
Official Communication for Australian Patent Application No. 2014210614 dated Jun. 5, 2015. |
Official Communication for Australian Patent Application No. 2014213553 dated May 7, 2015. |
Official Communication for Australian Patent Application No. 2014250678 dated Jun. 17, 2015. |
Official Communication for Canadian Patent Application No. 2831660 dated Jun. 9, 2015. |
Official Communication for European Patent Application No. 10195798.3 dated May 17, 2011. |
Official Communication for European Patent Application No. 12181585.6 dated Sep. 4, 2015. |
Official Communication for European Patent Application No. 12186236.1 dated May 17, 2013. |
Official Communication for European Patent Application No. 14158861.6 dated Jun. 16, 2014. |
Official Communication for European Patent Application No. 14159464.8 dated Jul. 31, 2014. |
Official Communication for European Patent Application No. 14180142.3 dated Feb. 6, 2015. |
Official Communication for European Patent Application No. 14180281.9 dated Jan. 26, 2015. |
Official Communication for European Patent Application No. 14180321.3 dated Apr. 17, 2015. |
Official Communication for European Patent Application No. 14180432.8 dated Jun. 23, 2015. |
Official Communication for European Patent Application No. 14186225.0 dated Feb. 13, 2015. |
Official Communication for European Patent Application No. 14187739.9 dated Jul. 6, 2015. |
Official Communication for European Patent Application No. 14187996.5 dated Feb. 12, 2015. |
Official Communication for European Patent Application No. 14189344.6 dated Feb. 20, 2015. |
Official Communication for European Patent Application No. 14189347.9 dated Mar. 4, 2015. |
Official Communication for European Patent Application No. 14189802.3 dated May 11, 2015. |
Official Communication for European Patent Application No. 14191540.5 dated May 27, 2015. |
Official Communication for European Patent Application No. 14197879.1 dated Apr. 28, 2015. |
Official Communication for European Patent Application No. 14197895.7 dated Apr. 28, 2015. |
Official Communication for European Patent Application No. 14197938.5 dated Apr. 28, 2015. |
Official Communication for European Patent Application No. 14199182.8 dated Mar. 13, 2015. |
Official Communication for European Patent Application No. 14200246.8 dated May 29, 2015. |
Official Communication for European Patent Application No. 14200298.9 dated May 13, 2015. |
Official Communication for European Patent Application No. 15155845.9 dated Oct. 6, 2015. |
Official Communication for European Patent Application No. 15155846.7 dated Jul. 8, 2015. |
Official Communication for European Patent Application No. 15165244.3 dated Aug. 27, 2015. |
Official Communication for European Patent Application No. 15175106.2 dated Nov. 5, 2015. |
Official Communication for European Patent Application No. 15175151.8 dated Nov. 25, 2015. |
Official Communication for European Patent Application No. 15181419.1 dated Sep. 29, 2015. |
Official Communication for European Patent Application No. 15183721.8 dated Nov. 23, 2015. |
Official Communication for European Patent Application No. 15184764.7 dated Dec. 14, 2015. |
Official Communication for European Patent Application No. 15188106.7 dated Feb. 3, 2016. |
Official Communication for European Patent Application No. 15190307.7 dated Feb. 19, 2016. |
Official Communication for European Patent Application No. 16160781.7 dated May 27, 2016. |
Official Communication for European Patent Application No. 16160781.7 dated Jan. 3, 2019. |
Official Communication for European Patent Application No. 16184373.5 dated Jan. 17, 2017. |
Official Communication for European Patent Application No. 16184373.5 dated May 28, 2018. |
Official Communication for European Patent Application No. 16186622.3 dated Jan. 18, 2017. |
Official Communication for European Patent Application No. 19186114.5 dated Jan. 16, 2020. |
Official Communication for Great Britain Patent Application No. 1319225.7 dated May 2, 2014. |
Official Communication for Great Britain Patent Application No. 1404457.2 dated Aug. 14, 2014. |
Official Communication for Great Britain Patent Application No. 1404486.1 dated May 21, 2015. |
Official Communication for Great Britain Patent Application No. 1404486.1 dated Aug. 27, 2014. |
Official Communication for Great Britain Patent Application No. 1404489.4 dated May 21, 2015. |
Official Communication for Great Britain Patent Application No. 1404489.5 dated May 21, 2015. |
Official Communication for Great Britain Patent Application No. 1404489.5 dated Aug. 27, 2014. |
Official Communication for Great Britain Patent Application No. 1404499.4 dated Jun. 11, 2015. |
Official Communication for Great Britain Patent Application No. 1404499.4 dated Aug. 20, 2014. |
Official Communication for Great Britain Patent Application No. 1404574.4 dated Dec. 18, 2014. |
Official Communication for Great Britain Patent Application No. 1408025.3 dated Nov. 6, 2014. |
Official Communication for Great Britain Patent Application No. 1411984.6 dated Dec. 22, 2014. |
Official Communication for Great Britain Patent Application No. 1413935.6 dated Jan. 27, 2015. |
Official Communication for Great Britain Patent Application No. 1620827.4 dated Jan. 12, 2017. |
Official Communication for Great Britain Patent Application No. 1620827.4 dated Nov. 13, 2017. |
Official Communication for Great Britain Patent Application No. 1620827.4 dated Sep. 21, 2017. |
Official Communication for Great Britain Patent Application No. 1620827.4 dated Jun. 28, 2017. |
Official Communication for Netherlands Patent Application No. 2011632 dated Feb. 8, 2016. |
Official Communication for Netherlands Patent Application No. 2011729 dated Aug. 13, 2015. |
Official Communication for Netherlands Patent Application No. 2012417 dated Sep. 18, 2015. |
Official Communication for Netherlands Patent Application No. 2012421 dated Sep. 18, 2015. |
Official Communication for Netherlands Patent Application No. 2012437 dated Sep. 18, 2015. |
Official Communication for Netherlands Patent Application No. 2012438 dated Sep. 21, 2015. |
Official Communication for Netherlands Patent Application No. 2012778 dated Sep. 22, 2015. |
Official Communication for Netherlands Patent Application No. 2013306 dated Apr. 24, 2015. |
Official Communication for New Zealand Patent Application No. 616167 dated Oct. 10, 2013. |
Official Communication for New Zealand Patent Application No. 622473 dated Jun. 19, 2014. |
Official Communication for New Zealand Patent Application No. 622473 dated Mar. 27, 2014. |
Official Communication for New Zealand Patent Application No. 622513 dated Apr. 3, 2014. |
Official Communication for New Zealand Patent Application No. 622517 dated Apr. 3, 2014. |
Official Communication for New Zealand Patent Application No. 624557 dated May 14, 2014. |
Official Communication for New Zealand Patent Application No. 627962 dated Aug. 5, 2014. |
Official Communication for New Zealand Patent Application No. 628161 dated Aug. 25, 2014. |
Official Communication for New Zealand Patent Application No. 628263 dated Aug. 12, 2014. |
Official Communication for New Zealand Patent Application No. 628495 dated Aug. 19, 2014. |
Official Communication for New Zealand Patent Application No. 628585 dated Aug. 26, 2014. |
Official Communication for New Zealand Patent Application No. 628840 dated Aug. 28, 2014. |
Official Communication for U.S. Appl. No. 12/556,318 dated Jul. 2, 2015. |
Official Communication for U.S. Appl. No. 12/556,321 dated Feb. 25, 2016. |
Official Communication for U.S. Appl. No. 12/556,321 dated Jun. 6, 2012. |
Official Communication for U.S. Appl. No. 12/556,321 dated Dec. 7, 2011. |
Official Communication for U.S. Appl. No. 12/556,321 dated Jul. 7, 2015. |
Official Communication for U.S. Appl. No. 12/840,673 dated Sep. 17, 2014. |
Official Communication for U.S. Appl. No. 12/840,673 dated Jan. 2, 2015. |
Official Communication for U.S. Appl. No. 12/840,673 dated Jul. 25, 2012. |
Official Communication for U.S. Appl. No. 12/840,673 dated Jan. 4, 2013. |
Official Communication for U.S. Appl. No. 13/247,987 dated Apr. 2, 2015. |
Official Communication for U.S. Appl. No. 13/247,987 dated Sep. 22, 2015. |
Official Communication for U.S. Appl. No. 13/669,274 dated Aug. 26, 2015. |
Official Communication for U.S. Appl. No. 13/669,274 dated May 6, 2015. |
Official Communication for U.S. Appl. No. 13/728,879 dated Aug. 12, 2015. |
Official Communication for U.S. Appl. No. 13/728,879 dated Mar. 17, 2015. |
Official Communication for U.S. Appl. No. 13/728,879 dated Nov. 20, 2015. |
Official Communication for U.S. Appl. No. 13/728,879 dated Jan. 27, 2015. |
Official Communication for U.S. Appl. No. 13/827,491 dated Dec. 1, 2014. |
Official Communication for U.S. Appl. No. 13/827,491 dated Jun. 22, 2015. |
Official Communication for U.S. Appl. No. 13/827,491 dated Oct. 9, 2015. |
Official Communication for U.S. Appl. No. 13/831,791 dated Mar. 4, 2015. |
Official Communication for U.S. Appl. No. 13/831,791 dated Aug. 6, 2015. |
Official Communication for U.S. Appl. No. 13/835,688 dated Jun. 17, 2015. |
Official Communication for U.S. Appl. No. 13/839,026 dated Aug. 4, 2015. |
Official Communication for U.S. Appl. No. 14/134,558 dated Oct. 7, 2015. |
Official Communication for U.S. Appl. No. 14/141,252 dated Oct. 8, 2015. |
Official Communication for U.S. Appl. No. 14/148,568 dated Oct. 22, 2014. |
Official Communication for U.S. Appl. No. 14/148,568 dated Mar. 26, 2015. |
Official Communication for U.S. Appl. No. 14/196,814 dated May 5, 2015. |
Official Communication for U.S. Appl. No. 14/222,364 dated Dec. 9, 2015. |
Official Communication for U.S. Appl. No. 14/225,006 dated Sep. 10, 2014. |
Official Communication for U.S. Appl. No. 14/225,006 dated Sep. 2, 2015. |
Official Communication for U.S. Appl. No. 14/225,006 dated Dec. 21, 2015. |
Official Communication for U.S. Appl. No. 14/225,006 dated Feb. 27, 2015. |
Official Communication for U.S. Appl. No. 14/225,084 dated Sep. 11, 2015. |
Official Communication for U.S. Appl. No. 14/225,084 dated Sep. 2, 2014. |
Official Communication for U.S. Appl. No. 14/225,084 dated Feb. 20, 2015. |
Official Communication for U.S. Appl. No. 14/225,084 dated Jan. 4, 2016. |
Official Communication for U.S. Appl. No. 14/225,160 dated Feb. 11, 2015. |
Official Communication for U.S. Appl. No. 14/225,160 dated Aug. 12, 2015. |
Official Communication for U.S. Appl. No. 14/225,160 dated May 20, 2015. |
Official Communication for U.S. Appl. No. 14/225,160 dated Oct. 22, 2014. |
Official Communication for U.S. Appl. No. 14/225,160 dated Jul. 29, 2014. |
Official Communication for U.S. Appl. No. 14/265,637 dated Sep. 26, 2014. |
Official Communication for U.S. Appl. No. 14/268,964 dated Sep. 3, 2014. |
Official Communication for U.S. Appl. No. 14/289,596 dated Jul. 18, 2014. |
Official Communication for U.S. Appl. No. 14/289,596 dated Jan. 26, 2015. |
Official Communication for U.S. Appl. No. 14/289,596 dated Apr. 30, 2015. |
Official Communication for U.S. Appl. No. 14/289,596 dated Aug. 5, 2015. |
Official Communication for U.S. Appl. No. 14/289,596 dated May 9, 2016. |
Official Communication for U.S. Appl. No. 14/289,599 dated Jul. 22, 2014. |
Official Communication for U.S. Appl. No. 14/289,599 dated May 29, 2015. |
Official Communication for U.S. Appl. No. 14/289,599 dated Sep. 4, 2015. |
Official Communication for U.S. Appl. No. 14/294,098 dated Aug. 15, 2014. |
Official Communication for U.S. Appl. No. 14/294,098 dated Nov. 6, 2014. |
Official Communication for U.S. Appl. No. 14/306,138 dated Sep. 14, 2015. |
Official Communication for U.S. Appl. No. 14/306,138 dated Mar. 17, 2016. |
Official Communication for U.S. Appl. No. 14/306,138 dated Feb. 18, 2015. |
Official Communication for U.S. Appl. No. 14/306,138 dated Sep. 23, 2014. |
Official Communication for U.S. Appl. No. 14/306,138 dated Dec. 24, 2015. |
Official Communication for U.S. Appl. No. 14/306,138 dated May 26, 2015. |
Official Communication for U.S. Appl. No. 14/306,138 dated Dec. 3, 2015. |
Official Communication for U.S. Appl. No. 14/306,147 dated Feb. 19, 2015. |
Official Communication for U.S. Appl. No. 14/306,147 dated Dec. 24, 2015. |
Official Communication for U.S. Appl. No. 14/306,147 dated Mar. 4, 2016. |
Official Communication for U.S. Appl. No. 14/306,147 dated Aug. 7, 2015. |
Official Communication for U.S. Appl. No. 14/306,147 dated Sep. 9, 2014. |
Official Communication for U.S. Appl. No. 14/306,154 dated Feb. 1, 2016. |
Official Communication for U.S. Appl. No. 14/306,154 dated Mar. 11, 2015. |
Official Communication for U.S. Appl. No. 14/306,154 dated May 15, 2015. |
Official Communication for U.S. Appl. No. 14/306,154 dated Nov. 16, 2015. |
Official Communication for U.S. Appl. No. 14/306,154 dated Mar. 17, 2016. |
Official Communication for U.S. Appl. No. 14/306,154 dated Jul. 6, 2015. |
Official Communication for U.S. Appl. No. 14/306,154 dated Sep. 9, 2014. |
Official Communication for U.S. Appl. No. 14/319,161 dated Jan. 23, 2015. |
Official Communication for U.S. Appl. No. 14/319,765 dated Sep. 10, 2015. |
Official Communication for U.S. Appl. No. 14/319,765 dated Jun. 16, 2015. |
Official Communication for U.S. Appl. No. 14/319,765 dated Nov. 25, 2014. |
Official Communication for U.S. Appl. No. 14/319,765 dated Feb. 4, 2015. |
Official Communication for U.S. Appl. No. 14/323,878 dated Jul. 27, 2017. |
Official Communication for U.S. Appl. No. 14/323,878 dated Sep. 28, 2017. |
Official Communication for U.S. Appl. No. 14/323,878 dated Mar. 30, 2017. |
Official Communication for U.S. Appl. No. 14/323,881 dated Nov. 1, 2017. |
Official Communication for U.S. Appl. No. 14/323,881 dated Apr. 18, 2017. |
Official Communication for U.S. Appl. No. 14/323,935 dated Jun. 22, 2015. |
Official Communication for U.S. Appl. No. 14/323,935 dated Nov. 28, 2014. |
Official Communication for U.S. Appl. No. 14/323,935 dated Mar. 31, 2015. |
Official Communication for U.S. Appl. No. 14/326,738 dated Dec. 2, 2014. |
Official Communication for U.S. Appl. No. 14/326,738 dated Jul. 31, 2015. |
Official Communication for U.S. Appl. No. 14/326,738 dated Mar. 31, 2015. |
Official Communication for U.S. Appl. No. 14/451,221 dated Oct. 21, 2014. |
Official Communication for U.S. Appl. No. 14/463,615 dated Sep. 10, 2015. |
Official Communication for U.S. Appl. No. 14/463,615 dated May 12, 2016. |
Official Communication for U.S. Appl. No. 14/463,615 dated Nov. 13, 2014. |
Official Communication for U.S. Appl. No. 14/463,615 dated Mar. 21, 2016. |
Official Communication for U.S. Appl. No. 14/463,615 dated May 21, 2015. |
Official Communication for U.S. Appl. No. 14/463,615 dated Jan. 28, 2015. |
Official Communication for U.S. Appl. No. 14/463,615 dated Dec. 9, 2015. |
Official Communication for U.S. Appl. No. 14/473,552 dated Feb. 24, 2015. |
Official Communication for U.S. Appl. No. 14/479,863 dated Dec. 26, 2014. |
Official Communication for U.S. Appl. No. 14/483,527 dated Jun. 22, 2015. |
Official Communication for U.S. Appl. No. 14/483,527 dated Jan. 28, 2015. |
Official Communication for U.S. Appl. No. 14/483,527 dated Oct. 28, 2015. |
Official Communication for U.S. Appl. No. 14/486,991 dated Mar. 10, 2015. |
Official Communication for U.S. Appl. No. 14/490,612 dated Aug. 18, 2015. |
Official Communication for U.S. Appl. No. 14/490,612 dated Jan. 27, 2015. |
Official Communication for U.S. Appl. No. 14/490,612 dated Mar. 31, 2015. |
Official Communication for U.S. Appl. No. 14/504,103 dated Mar. 31, 2015. |
Official Communication for U.S. Appl. No. 14/504,103 dated Feb. 5, 2015. |
Official Communication for U.S. Appl. No. 14/552,336 dated Jul. 20, 2015. |
Official Communication for U.S. Appl. No. 14/562,524 dated Nov. 10, 2015. |
Official Communication for U.S. Appl. No. 14/562,524 dated Sep. 14, 2015. |
Official Communication for U.S. Appl. No. 14/562,524 dated Feb. 18, 2016. |
Official Communication for U.S. Appl. No. 14/571,098 dated Nov. 10, 2015. |
Official Communication for U.S. Appl. No. 14/571,098 dated Mar. 11, 2015. |
Official Communication for U.S. Appl. No. 14/571,098 dated Feb. 23, 2016. |
Official Communication for U.S. Appl. No. 14/571,098 dated Aug. 24, 2015. |
Official Communication for U.S. Appl. No. 14/571,098 dated Aug. 5, 2015. |
Official Communication for U.S. Appl. No. 14/579,752 dated Aug. 19, 2015. |
Official Communication for U.S. Appl. No. 14/579,752 dated May 26, 2015. |
Official Communication for U.S. Appl. No. 14/631,633 dated Sep. 10, 2015. |
Official Communication for U.S. Appl. No. 14/639,606 dated Oct. 16, 2015. |
Official Communication for U.S. Appl. No. 14/639,606 dated May 18, 2015. |
Official Communication for U.S. Appl. No. 14/639,606 dated Jul. 24, 2015. |
Official Communication for U.S. Appl. No. 14/676,621 dated Oct. 29, 2015. |
Official Communication for U.S. Appl. No. 14/676,621 dated Jul. 30, 2015. |
Official Communication for U.S. Appl. No. 14/715,834 dated Feb. 19, 2016. |
Official Communication for U.S. Appl. No. 14/726,353 dated Sep. 10, 2015. |
Official Communication for U.S. Appl. No. 14/730,123 dated Sep. 21, 2015. |
Official Communication for U.S. Appl. No. 14/746,671 dated Nov. 12, 2015. |
Official Communication for U.S. Appl. No. 14/746,671 dated Sep. 28, 2015. |
Official Communication for U.S. Appl. No. 14/800,447 dated Dec. 10, 2015. |
Official Communication for U.S. Appl. No. 14/800,447 dated Mar. 3, 2016. |
Official Communication for U.S. Appl. No. 14/813,749 dated Sep. 28, 2015. |
Official Communication for U.S. Appl. No. 14/841,338 dated Feb. 18, 2016. |
Official Communication for U.S. Appl. No. 14/842,734 dated Jun. 1, 2017. |
Official Communication for U.S. Appl. No. 14/842,734 dated Nov. 19, 2015. |
Official Communication for U.S. Appl. No. 14/842,734 dated Dec. 7, 2017. |
Official Communication for U.S. Appl. No. 14/871,465 dated Feb. 9, 2016. |
Official Communication for U.S. Appl. No. 14/883,498 dated Mar. 17, 2016. |
Official Communication for U.S. Appl. No. 14/883,498 dated Dec. 24, 2015. |
Official Communication for U.S. Appl. No. 14/929,584 dated May 25, 2016. |
Official Communication for U.S. Appl. No. 14/929,584 dated Feb. 4, 2016. |
Official Communication for U.S. Appl. No. 14/934,004 dated Feb. 16, 2016. |
Official Communication for U.S. Appl. No. 14/934,004 dated Jul. 29, 2016. |
Official Communication for U.S. Appl. No. 15/072,133 dated Nov. 10, 2016. |
Official Communication for U.S. Appl. No. 15/072,133 dated Mar. 17, 2017. |
Official Communication for U.S. Appl. No. 14/323,878 dated Feb. 28, 2018. |
Official Communication for U.S. Appl. No. 14/323,878 dated Sep. 7, 2018. |
Official Communication for U.S. Appl. No. 15/146,841 dated Nov. 28, 2018. |
Official Communication for U.S. Appl. No. 15/146,841 dated Mar. 8, 2018. |
Official Communication for U.S. Appl. No. 15/146,842 dated Nov. 28, 2018. |
Official Communication for U.S. Appl. No. 15/146,842 dated Mar. 30, 2018. |
Official Communication for U.S. Appl. No. 15/146,842 dated Mar. 7, 2018. |
Olanoff, Drew, “Deep Dive with the New Google Maps for Desktop with Google Earth Integration, It's More than Just a Utility,” May 15, 2013, retrieved from the internet: http://web.archive.org/web/20130515230641/http://techcrunch.com/2013/05/15/deep-dive-with-the-new-google-maps-for-desktop-with-google-earth-integration-its-more-than-just-a-utility/, 7 pages. |
Online Tech Tips, “Clip2Net—Share files, folders and screenshots easily,” http://www.online-tech-tips.com/free-software-downloads/share-files-folders-screenshots/, Apr. 2, 2008, pp. 5. |
Open Street Map, “Amm's Diary: Unconnected ways and other data quality issues,” http://www.openstreetmap.org/user/amm/diary printed Jul. 23, 2012 in 3 pages. |
Open Web Analytics (OWA), <http://www.openwebanalytics.com/> Printed Jul. 19, 2013 in 5 pages. |
O'Reilly.com, http://oreilly.com/digitalmedia/2006/01/01/mac-os-x-screenshot-secrets.html published Jan. 1, 2006 in 10 pages. |
Palantir Technologies, “Palantir Labs_Timeline,” Oct. 1, 2010, retrieved from the internet https://www.youtube.com/watch?v=JCgDW5bru9M. |
Palantir Technologies, “Palantir Labs-13 Timeline,” Oct. 1, 2010, retrieved from the internet https://www.youtube.com/watch?v=JCgDW5bru9M retrieved on Aug. 19, 2015. |
Palantir, “Basic Map Searches,” YouTube, Sep. 12, 2013, retrieved from https://www.youtube.com/watch?v=UC-1x44xFRO. |
Palantir, “Intelligence Integration in Palantir: an Open-Source View of the Afghan Conflict,” YouTube, Jul. 5, 2012, retrieved from https://www.youtube.com/watch?v=FXTxs2YqHY4. |
Palmas et al., “An Edge-Bunding Layout for Interactive Parallel Coordinates” 2014 IEEE Pacific Visualization Symposium, pp. 57-64. |
Perdisci et al., “Behavioral Clustering of HTTP-Based Malware and Signature Generation Using Malicious Network Traces,” USENIX, Mar. 18, 2010, pp. 1-14. |
Piwik—Free Web Analytics Software. < http://piwik.org/> Printed Jul. 19, 2013 in18 pages. |
POI Editor, “How to: Create Your Own Points of Interest,” <http://www.poieditor.com/articles/how_to create_your_own_points_of_interest/> printed Jul. 22, 2012 in 4 pages. |
Pozzi et al., Vegetation and Population Density in Urban and Suburban Areas in. |
Qiu, Fang, “3d Analysis and Surface Modeling”, <http://web.archive.org/web/20091202221925/http://www.utsa.edu/lrsg/Teaching/EES6513/08-3D.pdf> printed Sep. 16, 2013 in 26 pages. |
Quest, “Toad for Oracle 11.6—Guide to Using Toad,” Sep. 24, 2012, pp. 1-162. |
Reddy et al., “Under the hood of GeoVRML 1.0,” SRI International, Proceedings of the fifth symposium on Vurtual Reality Modeling Language (Web3D-VRML), New York, NY, Feb. 2000, pp. 23-28. <http://pdf.aminer.org/000/648/038/under_the_hood_of_geovrml.pdf>. |
Reibel et al., “Areal Interpolation of Population Counts Using Pre-classi_ed Land Cover Data,” Population Research and Policy Review, 2007, vol. 26, pp. 619-633. |
Reibel, M., “Geographic Information Systems and Spatial Data Processing in Demography: a Review,” Population Research and Policy Review, 2007, vol. 26, pp. 601-618. |
Restriction Requirement for U.S. Appl. No. 13/839,026 dated Apr. 2, 2015. |
Rizzardi et al., “Interfacing U.S. Census Map Files with Statistical Graphics Software: Application and Use in Epidemiology,” Statistics in Medicine, Oct. 1993, vol. 12, No. 19-20, pp. 1953-1964. |
Rouse, Margaret, “OLAP Cube,” <http://searchdatamanagement.techtarget.com/definition/OLAP-cube>, Apr. 28, 2012, pp. 16. |
Schroder, Stan, “15 Ways To Create Website Screenshots,” http://mashable.com/2007/08/24/web-screenshots/, Aug. 24, 2007, pp. 2. |
Shi et al., “A Scalable Implementation of Malware Detection Based on Network Connection Behaviors,” 2013 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery, IEEE, Oct. 10, 2013, pp. 59-66. |
Sigrist, et al., “Prosite, a Protein Domain Database for Functional Characterization and Annotation,” Nucleic Acids Research, 2010, vol. 38, pp. D161-D166. |
Sirotkin et al., “Chapter 13: the Processing of Biological Sequence Data at NCBI,” the NCBI Handbook, Oct. 2002, pp. 1-11. |
Snaglt, “Snaglt 8.1.0 Print Out 2,” Software release date Jun. 15, 2006, pp. 1-3. |
Snaglt, “Snaglt 8.1.0 Print Out,” Software release date Jun. 15, 2006, pp. 6. |
Snaglt, “Snaglt Online Help Guide,” http://download.techsmith.com/snagit/docs/onlinehelp/enu/snagit_help.pdf, TechSmith Corp., Version 8.1, printed Feb. 7, 2007, pp. 284. |
Snyder, “Map Projections—a Working Manual,” U.S. Geological Survey Professional paper 1395, United States Government Printing Office, Washington: 1987, pp. 11-21 and 60-70. |
Sonris, “Using the Area of Interest Tools,” <http://web.archive.org/web/20061001053327/http://sonris-www.dnr.state.la.US/gis/instruct_files/tutslide12> printed Jan. 3, 2013 in 1 page. |
StatCounter—Free Invisible Web Tracker, Hit Counter and Web Stats, <http://statcounter.com/> Printed Jul. 19, 2013 in 17 pages. |
Symantec Corporation, “E-Security Begins with Sound Security Policies,” Announcement Symantec, Jun. 14, 2001. |
Tangelder et al., “Freeform Shape Matching Using Minkowski Operations,” The Netherlands, Jun. 1996, pp. 12. |
TestFlight—Beta Testing on the Fly, <http://testflightapp.com/> Printed Jul. 18, 2013 in 3 pages. |
Thompson, Mick, “Getting Started with GEO,” Getting Started with GEO, Jul. 26, 2011. |
Trak.io, Analytics For Data Driven Startups, <http://trak.io/> printed Jul. 18, 2013 in 3 pages. |
Umagandhi et al., “Search Query Recommendations Using Hybrid User Profile with Query Logs,” International Journal of Computer Applications, vol. 80, No. 10, Oct. 1, 2013, pp. 7-18. |
Usermetrix, <http://usermetrix.com/android-analytics> printed Jul. 18, 2013 in 3 pages. |
Valentini et al., “Ensembles of Learning Machines”, M. Marinaro and R. Tagliaferri (Eds.): Wirn Vietri 2002, LNCS 2486, pp. 3-20. |
VB Forums, “Buffer a Polygon,” Internet Citation, <http://www.vbforums.com/showthread.php?198436-Buffer-a-Polygon>, Specifically Thread #1, #5 & #11 retrieved on May 2, 2013, pp. 8. |
Vivid Solutions, “JTS Topology Suite: Technical Specifications,” <http://www.vividsolutions.com/jts/bin/JTS%20Technical%20Specs.pdf> Version 1.4, 2003, pp. 36. |
Vose et al., “Help File for ModelRisk Version 5,” 2007, Vose Software, pp. 349-353. [Uploaded in 2 Parts]. |
Wang et al., “Research on a Clustering Data De-Duplication Mechanism Based on Bloom Filter,” IEEE 2010, 5 pages. |
Warren, Christina, “TUAW Faceoff: Screenshot apps on the firing line,” http://www.tuaw.com/2008/05/05/tuaw-faceoff-screenshot-apps-on-the-firing-line/, May 5, 2008, pp. 11. |
Wikipedia, “Douglas_Peucker-Algorithms,” <http://de.wikipedia.org/w/index.php?title=Douglas-Peucker-Algorithmus&oldid=91846042> printed Jul. 2011, pp. 2. |
Wikipedia, “Federated Database System,” Sep. 7, 2013, retrieved from the internet on Jan. 27, 2015 http://en.wikipedia.org/w/index.php?title=Federated_database_system&oldid=571954221. |
Wikipedia, “Multimap,” Jan. 1, 2013, https://en.wikipedia.org/w/index.php?title=Multimap&oldid=530800748. |
Wikipedia, “Ramer_Douglas_Peucker Algorithm,” <http://en.wikipedia.org/wiki/Ramer%E2%80%93Douglas%E2%80%93Peucker_algorithm> printed Jul. 2011, pp. 3. |
Wongsuphasawat et al., “Visual Analytics for Transportation Incident Data Sets,” Transportation Research Record 2138, 2009, pp. 135-145. |
Woodbridge, Stephen, “[geos-devel] Polygon simplification,” <http://lists.osgeo.org/pipermail/geos-devel/2011-May/005210.html> dated May 8, 2011, pp. 3. |
Wright et al., “Palantir Technologies VAST 2010 Challenge Text Records_Investigations into Arms Dealing,” Oct. 29, 2010, pp. 1-10. |
Yang et al., “HTML Page Analysis Based on Visual Cues”, A129, pp. 859-864, 2001. |
Official Communication for European Patent Application No. 19186114.5 dated Sep. 15, 2023. |
“Finding Files and Content Within Files”, as archived Oct. 1, 2011, https://web.archive.org/web/20111001004604/http://matlab.izmiran.ru/help/techdoc/matlab_env/ws_pat32.html in 2 pages. |
Number | Date | Country | |
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20210157477 A1 | May 2021 | US |
Number | Date | Country | |
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62200565 | Aug 2015 | US | |
62133857 | Mar 2015 | US |
Number | Date | Country | |
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Parent | 16567540 | Sep 2019 | US |
Child | 17168542 | US | |
Parent | 15852613 | Dec 2017 | US |
Child | 16567540 | US | |
Parent | 15072133 | Mar 2016 | US |
Child | 15852613 | US |