Patent Grant
10572496
In the area of computer-based platforms, information about cities may be collected, analyzed, and used to make cities more resilient.
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.
In some embodiments, a system comprises one or more computing devices programmed, via executable code instructions. When executed, the executable code instructions may cause the system to receive resilience data from each of a plurality of entities associated with respective municipalities, each entity comprising at least one computing system. The resilience data from the plurality of entities may include electronic documents regarding actual or potential natural disasters associated with respective municipalities. The resilience data may include first resilience data comprising a first electronic document including information regarding an actual or potential natural disaster associated with a first municipality. The resilience data may further include second resilience data comprising a second electronic document including information regarding an actual or potential natural disaster associated with a second municipality. When further executed, the executable code instructions may cause the system to receive a search keyword from a third entity associated with a third municipality. The search keyword may be received via an interactive user interface displayed on a computer display of the third entity. The interactive user interface may include a reader user interface having: a search area configured to receive search criteria including the search keyword; a results area configured to display summary information regarding any electronic documents of the resilience data matching the search criteria; and a data preview area configured to display at least a portion of an electronic document selected in the results area. When further executed, the executable code instructions may cause the system to search the resilience data, including the first resilience data and the second resilience data, for resilience data including the search keyword. When further executed, the executable code instructions may cause the system to, in response to determining that the first electronic document includes the search keyword, initiate update of the reader user interface to display first summary information regarding the first electronic document in the results area. When further executed, the executable code instructions may cause the system to determine a plurality of attribute values of the first electronic document. The attribute values may include one or more of: author attributes; recipient attributes; named attributes; and/or geolocation attributes. When further executed, the executable code instructions may cause the system to identify respective person objects associated with any identified author attribute values, recipient attribute values, and named attribute values of the first electronic document. When further executed, the executable code instructions may cause the system to initiate update of the interactive user interface to display a clustering user interface. The clustering user interface may display: a document icon representing the first electronic document; one or more person icons each representing corresponding person objects identified as associated with the first electronic document; one or more association lines between pairs of respective person icons and the document icon; and/or textual or graphical indicia associated with each association line indicating respective associations between respect person objects and the first electronic document. The textual or graphical indicia may indicate the person object is at least one of: an author, recipient, or named in the first electronic document. When further executed, the executable code instructions may cause the system to initiate update of the interactive user interface to display an interactive map user interface displaying: a geographic map; and/or graphical indicia of one or more geolocation attribute values associated with the first electronic document.
In some embodiments, a system comprises one or more computing devices programmed, via executable code instructions. When executed, the executable code instructions may cause the system to communicate with a plurality of entities, wherein each entity of the plurality of entities is associated with a municipality, and wherein each entity comprises a network of computing devices. When executed, the executable code instructions may cause the system to receive first resilience data from a first entity of the plurality of entities, the first resilience data comprising information associated with a first municipality and a potential acute shock or chronic stress associated with the first municipality, the first resilience data further comprising a first electronic document. When executed, the executable code instructions may cause the system to receive a search keyword. When executed, the executable code instructions may cause the system to search a plurality of municipality data, the plurality of resilience data comprising the first resilience data, using the search keyword to identify the first electronic document. When executed, the executable code instructions may cause the system to cause presentation on an electronic display, of the first resilience data and the first electronic document in a reader view, the reader view presenting at least some of the first electronic document in the electronic display. When executed, the executable code instructions may cause the system to determine an association between the first electronic document and a person object where a property value of the first electronic document matches a data value of the person object, wherein the property value comprises at least one of: an author, text data, editor, or recipient. When executed, the executable code instructions may cause the system to cause presentation of representations of the first electronic document, the person object, and the association between the electronic document and the person object in a second view, wherein the second view represents at least one of: an author, presence in, contributor, editing, or recipient relationship between the person object and the electronic document.
Certain aspects of the disclosure will become more readily appreciated as those aspects become better understood by reference to the following detailed description, when taken in conjunction with the accompanying drawings.
Disclosed herein are systems for automating processes of identifying related resiliency information between multiple municipalities (referred to as “cities” herein, which also applies to any other municipality or group of individuals) by executing algorithms for analysis of databases of information from various resources and providing information to analysts that enables quick access to strategies and/or documentation regarding relevant resilience data, as well as information on individuals involved in planning resilience efforts in other municipalities that can be contacted to obtain even more assistance in planning efforts.
In one embodiment, a resilience sharing system implements a workflow process for analyst to review, visualize, and investigate the city resiliency information, and/or detection strategies among multiple entities. Using the techniques and systems described herein, city resiliency threats, shocks, and/or stressors may be addressed more preemptively and/or efficiently by utilizing more information and/or analysis from other entities. Those techniques and systems may comprise automatic and/or in an ad hoc manner sharing city resiliency information and/or generic strategies to combat city resiliency threats. Sharing of city resiliency data may prevent, reduce, and/or mitigate the threat of natural disasters, city violence and/or crime, climate change, transportation issues, etc. Furthermore, the city resiliency sharing system may enable users of the system to quickly analyze and/or process city resiliency information from multiple distributed participants to develop city resiliency strategies. For example, an analyst may be able to review or send resilience data in a reader view, analyze relationships among resilience data objects in a clustering view, and/or interact with resilience data in an interactive map.
Many cities have large amounts of data (hundreds of gigabytes, for example) relevant to indicators and/or aspects of city resiliency. However, many entities are unable to synthesize such data into actionable information due to lack of communication. For example, intra-city cooperation may be difficult when data sources are siloed within individual departments. Yet another example is the difficulty of inter-city collaboration due to technological barriers to sharing, data sensitivities, and/or regulations.
The city resiliency sharing system disclosed herein enables participating organizations to exchange critical information and/or context about emerging city resiliency threats in real or near time, subject to highly granular access controls and/or automatic redaction of sensitive data. In some embodiments, secure sharing may be achieved through secure communication protocols (e.g., one or more encryption standards and/or protocols), access controls, access control lists, and/or the redaction of data. In some embodiments, entities can participate in the city resiliency sharing system in multiple ways by sharing only what they are willing to share. For example, in addition to full data sharing, entities can share partial subsets of their data, or receive but not share data. In the example, participating entities specified exactly how they will participate in the city resiliency sharing system: what data they share, what conditions govern data transmission, and what access controls govern entity and/or individual users' data access. The secure sharing of data may enable compliancy with laws governing the handling of personal data. Participating organizations may instantly gain access to real or near time feeds and/or intelligence, which are shared and enriched by participants across multiple industries and/or geographic boundaries. With the city resiliency sharing system, participating organizations may collaboratively improve situational awareness, obtain a comprehensive understanding of threats facing their cities. In some embodiments, the city resiliency sharing system may provide a full suite of data integration and analytical capabilities that allow organizations to quickly pivot from city resiliency identification to incident response and mitigation, all within the same platform.
Aspects of city resiliency, which may be shared as city resiliency data and/or generic strategies by the city resiliency sharing system as described herein, are described in further detail in Jo da Silva & Braulio Morera, Arup, City Resilience Framework (2014), which is hereby incorporated by reference in its entirety and is made a part of this specification. The city resiliency sharing system described herein may allow entities to evaluate and optimize one or more of the following indicators and/or aspects of a resilient city (as described in City Resilience Framework): minimal human vulnerability such as meeting the basic needs of the residents of a city; diverse livelihoods and employment; adequate safeguards to human life and health; strong community networks; social stability and security such as law enforcement, crime prevention, and/or emergency services; availability of financial resources and/or contingency funds; reduced physical exposure and vulnerability such as environmental stewardship, appropriate infrastructure and buildings, effective land use planning, and/or the enforcement of planning regulations; reliable communication networks, and integrated development planning.
Sharing city resiliency information may allow for distributive and/or efficient responses to city resiliency threats, shocks, and/or stressors. As used herein, an “entity” may refer to an institution, organization, local government, city, municipality, territory, federal government, and/or departments thereof. Thus, entities may share city resiliency information automatically and/or in an ad hoc manner to improve resiliency. The city resiliency sharing system may modify city resiliency data to redact confidential, personal, and/or sensitive information for sharing with other entities.
As used herein, “resilience data” may refer to any data that can be shared among entities to improve resiliency. For example, resilience data may be used to improve the resiliency of a city, municipality, territory, jurisdiction, and/or country. Non-limiting examples of resilience data include building data, electronic communications, electronic documents, maps, and/or any other data associated with resiliency of a city, municipality, territory, jurisdiction, and/or country. The resilience data may be in various formats, such as a database format, files, XML, JSON, a file format that is proprietary to the city resiliency sharing system 100, data object format, or any other format, and may be encrypted or have resilience data of any available type.
In some embodiments, the suite of data integration and analytical capabilities of the city resiliency sharing system may allow an analyst to analyze the resilience data and/or to develop long-term city resiliency strategies. For example, the city resiliency sharing system may include a user interface displaying a city map with heat map data, received from one or more entities, regarding building information and/or crime statistics to allow a user to perform city resiliency analyses. In some embodiments, map data may be displayed and/or interactive maps may be presented. In some embodiments, displaying map data and/or presenting interactive maps by the systems, methods, and/or techniques disclosed in the Map reference. The city resiliency sharing system may include a user interface for displaying clusters of resilience data and/or generic strategies. In some embodiments, city resiliency data and/or strategies may be clustered and/or displayed by the systems, methods, and/or techniques disclosed in the Cluster references. In some embodiments, resilience data may be displayed and/or consumed via a reader user interface. In some embodiments, a reader may be implemented and/or resilience data may be displayed by the systems, methods, and/or techniques disclosed in the Reader references. In some embodiments, the city resiliency sharing system may use, receive, and/or share city or socioeconomic related data from data sources separate and/or distinct from the entities of the city resiliency sharing system. For example, the city resiliency sharing system may allow a user to predict the socioeconomic impact of a flood. Thus, the city resiliency sharing system may allow organizations to proactively detect, investigate, and prevent city resiliency.
Sharing of generic strategies through the city resiliency sharing system may efficiently combat city resiliency threats. In some embodiments, a generic strategy may be determined and updated by machine learning software that analysis related resiliency data and/or generated by human analysts or any participating entity and provided to the city resiliency sharing system for use by other participating entities. In some embodiments, a generic strategy may be generated by the city resiliency sharing system following a disaster and/or event against any entity and/or city using the system. A generic strategy may differ from a specific city resiliency event by comprising more abstract characteristics of a city resiliency event that may be used to proactively detect other city resiliency events and/or threats. The generic strategies may be configured to be executed, enabled, and/or implemented on other entities and/or computing systems to defend against and/or combat city resiliency threats from being perpetuated.
Example System Overview
A city event 130 may include a weather event, disease event, crime event, disaster, and/or any event that may affect a city. As used herein, a “city event” may refer to an acute shock and/or major event such as an earthquake, flood, emergency, terrorist attack, a sharp and/or sudden event that threatens a municipality, for example. Example acute shocks include natural disasters such as, but not limited to, hurricanes, earthquakes, tornadoes, volcanic eruptions, tsunamis, floods, wildfires, droughts, avalanches, or landslides. Additionally or alternatively, as used herein, a “city event’ may refer to chronic stresses such as long-term unemployment or poverty, an inefficient public transportation system, endemic violence, water shortage, or any event(s) that weaken a municipality on a day-to-day and/or cyclical basis, for example. Resilience data 140 may include, but is not limited to electronic communications, electronic documents, city reports, building data, etc. for city resiliency.
In some embodiments, such as the example embodiment of
The entities 110 may comprise one or more computing devices. Example entities 110 includes cities, institutions, organizations, local governments, the federal government, and/or departments or agencies thereof. For example, city resiliency sharing system 100 may enable intra-resilience data sharing and/or collaboration. In the intra-city example, departments, agencies, and/or other institutions may use system 100 within a city to eliminate data silos, facilitate data sharing, and/or enhance collaboration. Employees and/or analysts across the city can contribute to and/or leverage system 100 as a knowledge repository and/or workflow system for the city. Additionally or alternatively, city resiliency sharing system 100 may enable inter-resilience data sharing and/or collaboration. For example, entities 130 (that are cities) within system 100 may collaborate to create a shared and/or centralized hub for powerful data analysis across the entities and are cities. The cities may exchange critical information, best practices, and/or strategies in near time to address emerging trends and/or threats to cities to improve city resiliency.
The city resiliency sharing system 100 may operate as a single instance, client server system, or as a distributed system. For example, there may be multiple instances of the city resiliency sharing system 100 running simultaneously that communicate through the network 120, such as on computing systems of each of the entities 110. In some embodiments, each city resiliency sharing system instance operates independently and/or autonomously. In some embodiments, there is a central server of the city resiliency sharing system 100 and individual clients of the city resiliency sharing system communicate with the central server via the network 120. In the central server example, the central server may contain and/or store open source data. Each participant of the city resiliency sharing system 100 may communicate with other participants and/or the central server.
Example Resilience Data Sharing Processes
Beginning in block 202, an event occurs at one of the entities 110. As noted above, various activities may be considered events on an entity 110. Non-limiting examples of events include a major disaster such as an earthquake a flood, new legislation regarding building safety, and/or building inspections.
At block 204, the event is identified and/or resilience data is generated and/or accessed. For example, a draft of a legislative document or form data from a building inspection may be generated, which can be shared via city resiliency sharing system 100 as resilience data. In some embodiments, the event may be identified automatically or the event may be identified by a human analyst, such as a city resiliency analyst. In some embodiments, events are initially detected and/or flagged by one or more systems and/or processes and then a human analyst confirms the detected event before the resilience data is shared, such as according to the process described below. Additionally or alternatively, a city resiliency analyst may indicate resilience data, such as one or more resilience data objects, to be shared via city resiliency sharing system 100 (e.g.
In some embodiments, identification of events occurs by the systems, methods, and/or techniques disclosed in the Cluster references. For example, resilience data objects, events, documents, and/or communications may be clustered as illustrated by U.S. patent application Ser. No. 13/968,265. A human analyst may then view and analyze the cluster of related resilience data objects, events, documents, and/or communications. Clusters of resilience data objects may also receive rankings and/or scorings as illustrated by U.S. patent application Ser. No. 13/968,213.
In some embodiments, resilience data, documents, communications, strategies, and/or other city resiliency information may be data objects that are stored and associated with other data objects in data structures similar to those disclosed in the Ontology reference. For example, resilience data, documents, communications, strategies, and/or other city resiliency information may be included in data objects that are included in an ontology, which may be shared with other entities across the city resiliency sharing system and/or the data objects remain uniform across the entities they are shared with. In other words, the city resiliency sharing system may support a unified data object ontology. Additionally, each entity may support its own data object model and/or ontology that is different from its peer entities. In some embodiments, an ontology may provide a consistent view of resilience data across multiple entities. Another benefit of a unified data object ontology is to prevent duplicate and/or conflicting copies of data objects, and/or to allow for easy de-duplication of data objects.
At block 306, the resilience data may be optionally modified for sharing. For example, information regarding building data, employee information, account numbers, or personal information, such as social security numbers, may be removed from the resilience data before it is shared with the city resiliency sharing system 100. The entity 110 may remove and/or modify data regarding the event and/or the city resiliency sharing system 100 may remove and/or modify data regarding the event once received from the entity 110 (e.g., as discussed below in block 208).
In some embodiments, the city resiliency sharing system 100 uses access control lists and/or sharing rules to share, redact, and/or modify the resilience data. Additional information regarding the sharing, redaction, and/or modify of resilience data is discussed in further detail with reference to
Next, at block 208, the resilience data may be provided by the entity 110 to the city resiliency sharing system 100, such as via the network 120 of
In some embodiments, sharing of resilience data occurs by the systems, methods, and/or techniques disclosed in the Sharing references. For example, resilience data may be shared and/or deconflicted through a replicated database system as illustrated by U.S. Pat. No. 8,515,912, thereby preventing duplicate and/or conflicting copies of data. Resilience data and/or strategies may also be shared through a database system with multiple ontologies as illustrated by U.S. patent application Ser. No. 13/076,804. The sharing of resilience data and/or strategies may also occur via incremental database replication as illustrated by U.S. patent application Ser. No. 13/922,437.
In some embodiments, secure sharing through audited activity logs occurs by the systems, methods, and/or techniques disclosed in the Audit reference. For example, sharing activity may be stored in cryptographically immutable audit logs that can be quickly analyzed for suspicious user behavior.
At block 210, the resilience data that is received at the city resiliency sharing system 100 is wholly or partially shared with one or more entities 110. For example, if the resilience data is received from entity 110A, the city resiliency sharing system 100 may share the resilience data to entities 110B, 110C, and/or external systems, such as in accordance with sharing preferences of the entities. For example, the sharing preferences and/or access control lists of entity 110A may determine the entities and/or users that are permitted to receive the respective resilience data. In some embodiments, the sharing preferences and/or access control lists of entities 110B, and/or 110C determine which resilience data the respective entities receive, for example.
At block 212, the resilience data may be optionally used by the entities with which the resilience data is shared. For example, the resilience data may be used to proactively detect and/or hopefully prevent similar shocks and/or stresses on a city. Other examples include allowing a human analyst to contact the author of a report shared through system 100, generate a map of buildings that have a high risk of being structurally unsafe, and/or create a report using the shared resilience data.
Access Control/Modifying Resilience Data and/or Strategies
At block 302, city resiliency sharing system 100 optionally retrieves an access control list. In some embodiments, an access control list may be associated with a resilience data item and/or strategy. For example, the access control list may indicate entities and/or users that are permitted to receive and/or to view the respective resilience data item and/or strategy, which is described in further detail with reference to block 304.
At block 304, recipients may be specified for resilience data and/or strategies. For example, an entity may only want to send resilience data to other entities it has close relationships with or entities in a particular vertical market or having other attributes. Therefore, the entity may specify one or more criteria for entities with which resilience data and/or strategies may be shared with through the city resiliency sharing system 100. The sharing data may be provided in any available format, and may apply to sharing of resilience data and/or strategy data from the entity that provides the sharing data. In some embodiments, a human analyst approves and/or select the recipients of resilience data and/or strategies. As described herein, the access control lists may specify recipients such as entities and/or users permitted to receive and/or view resilience data and/or strategies.
In some embodiments, access controls for replicating resilience data and/or strategies at block 304 occurs by the systems, methods, and/or techniques disclosed in the Sharing references. For example, asynchronous replication of resilience data and/or strategies occur via access control lists that are described in further detail in U.S. Pat. No. 8,527,461 and in with reference to
At block 306, resilience data and/or strategies may be made anonymous. For example, resilience data and/or strategies may comprise the source entity of the resilience data and/or strategies. Thus, an entity may specify whether the sharing resilience data and/or strategies should be anonymous. In some embodiments, there is a global setting and/or configuration for specifying anonymity. There may be a configurable setting enabling anonymity for some recipients but not others. In some embodiments, a human may approve or specify (or an access control list may specify) anonymity for each resilience data item and/or city that is shared.
At block 308, irrelevant and/or sensitive data may be redacted from resilience data and/or strategies. For example, resilience data may initially comprise sensitive building data such as building identifiers and/or geolocation data. Other example resilience data includes personal information, such as, but not limited to, social security numbers, health records, names, birthdates, addresses, etc. An entity may not want to and/or be legally prohibited from sharing such information. An entity may redact and/or remove particular information. Thus, redaction, removal, and/or de-identification may allow an entity to be in compliance with applicable laws and/or regulations. Removal of sensitive information and/or entity specific information, such as internal identifiers, from resilience data, may abstract the resilience data to increase usability by other entities. In some embodiments, redaction of resilience data and/or strategies is automatic, manual, or some combination thereof. For example, there may be a configurable list of fields, such as, name, account number, etc., to be removed from resilience data and/or strategies. For example, access control lists may indicate resilience data and/or strategies that are to be redacted. Redaction may require approval by a human analyst. In some embodiments, redaction of resilience data and/or strategies may be performed by a human analyst.
At block 408, resilience data and/or strategies may be weighted differently such as based on the entity that provides the resilience data or strategy (e.g., some entities may be more reliable providing resilience data than others) or based on the type of event identified in the resilience data or strategy set, and/or other factors. For example, if resilience data indicates a high risk associated with the event, city resiliency sharing system 100 may assign a high weighting to the resilience data. However, if the reported event is minor and/or from an entity that commonly misreports events, a lower weighting may be assigned to the resilience data, such that sharing of the resilience data doesn't introduce false event alerts in other entities. Thus, in some embodiments, city resiliency sharing system 100 tracks the accuracy, reliability, and/or trustworthiness of reported events and/or data from respective entities and automatically applies weightings and/or prioritizations to future reports from those entities based on the determined accuracy.
The weightings may be assigned manually and/or automatically. For example, in some embodiments a human analyst specifies whether resilience data and/or strategies are important. These weightings may change over time, as the events themselves evolve.
From the perspective of a receiving entity, resilience data and/or strategies may be optionally weighed differently. Thus, if an entity values resilience data and/or strategies from a different entity highly, the entity may set a high level of priority for anything received from that different entity.
Sharing Resilience Data and/or Strategies
As shown in the example of
In this example, city resiliency sharing system 100 generates a strategy 410 and/or modified resilience data 420 based on the resilience data 400 corresponding to the one or more events 130, such as by any one or more processes discussed with reference to
In some embodiments, city resiliency sharing system 100 may be able to automatically generate strategies based on one or more events. Strategies may be automatically output by strategy unit 430. For example, the strategy unit 430 may take as input data regarding events and automatically generate a strategy from patterns recognized in the data.
In some embodiments, a human analyst and/or a team of analysts may review patterns from the one or more events to generate a strategy. City resiliency sharing system 100 may provide user interface tools to humans for analyzing events and/or creating strategies (e.g.,
In some embodiments, strategies may be generated by entities and shared through city resiliency sharing system 100. For example, strategy unit 430 may receive strategies from entities for distribution to other entities through city resiliency sharing system 100.
The shared resilience data and/or strategy may be modified by the entity 110A and/or the city resiliency sharing system 100, such as by any one or more processes discussed with reference to
Sharing Resilience Data and/or Strategies from Multiple and/or Different Entities
In this embodiment, the entity 110B, upon identifying the one or more events (see, e.g.,
Strategy generation and/or sharing in
City resiliency sharing system 100 may process the resilience data from different entities to share strategies, resilience data, and/or modified resilience data. In
Access Control and/or Sharing Rules
Example access control item 520 includes group 521 and permission 522. Example group 521 identifies a set of entities and/or users. Example permission 122 identifies an operation an entity and/or user in the set can perform on resilience data and/or strategy 540. Additionally or alternatively, example permission 122 further identifies an operation the entity and/or user in the set can perform on access control list 500. Non-limiting examples of permission 122 include read, write, owner, create, delete, read only, and/or some combination thereof.
In some embodiments, if access control list 500 has a classification 530, then an entity and/or user must be authorized for the classification 530. Thus, classification 530 may override permission 522 granted to the entity and/or user. For example, one possible set of classification markings as part of classification 530 include “Top Secret,” “Secret,” “Confidential,” “Restricted,” “For Official Use Only,” among others, while another example classification scheme may use the markings: “Public” and “Restricted,” among others. For example, the permissions of an access control list may indicate that a particular data object should not be shared with particular one or more entities and/or users. Additional detail regarding the sharing of resilience data and/or strategies occur via access control lists is described in further detail in U.S. Pat. No. 8,527,461.
As shown in
As shown in the example table of
Sharing rules 550 may also be used to specify recipients for resilience data and/or strategies. For example, as shown in
Example Workflow Systems and/or Methods
Example reader unit 620, cluster unit 630, and/or interactive map unit 640 may cause presentation of user interfaces as part of a workflow process for a human analyst. For example, reader unit 620 may cause presentation of an electronic document and/or communication repository (also referred to herein as a “reader view”) for viewing, editing, and/or sending data within city resiliency sharing system 100. Additional information regarding a reader view is discussed in further detail with reference to
Example workflow unit 428 communicates with other processes and/or services 660 and data stores 670 of city resiliency sharing system 100. For example, reader unit 620, cluster unit 630, and/or interactive map unit 640 can access resilience data from resilience data store 442 and/or strategy data store 432 of city resiliency sharing system 100. Further, reader unit 620, cluster unit 630, and/or interactive map unit 640 can communicate with strategy unit 430 and/or resilience data modification unit 440 of city resiliency sharing system 100.
In some embodiments, electronic communication listener 650 receives electronic communications that can be shared via city resiliency sharing system 100. As described herein, example electronic indication listener 650 is configured to receive electronic communications for particular electronic communication addresses and/or domains (e.g., email addresses and/or email domain)s. Examples of electronic communication addresses and/or domains include: “resilience@sharingsystem.com,” “earthquake.resilience@sharingsystem.com,” “building_inspection.sharingsystem@citysharing.com,” “sharingsystem.com,” “citysharing.com,” a chat message account, or a text message account such as a phone number, etc. The electronic communications sent to specific email addresses and/or domains may be sent from email applications and/or using email protocols known in the art. Electronic indication listener 650 may process the electronic communications and share the electronic communications as resilience data using the processes described herein. For example, recipients of the resilience data including the electronic communications may be determined by electronic communication listener 650 based on the particular email addresses and/or domains that were emailed, access control lists, and/or sharing rules described herein. In effect, city resiliency sharing system 100 may function as a message board for participants to share information and/or communicate. Additional details regarding sharing electronic communications via city resiliency sharing system 100 is described in further detail with reference to
Example Interactive User Interfaces
In the example provided below, a city analyst wants to learn how other cities are handling earthquake legislation, the analyst can use city resiliency sharing system 100 and a workflow process to identify key contacts in a chosen city to discuss data sets and analytical conclusions. The analyst can then cross-reference that information with data specific to a particular city, such as historical earthquake relief statistics and current infrastructure and population vulnerabilities.
Referring to
As illustrated in example results area 710, resilience data is presented in summary form. For example, result data items 712A-712C can include the title, data type, and source of the respective resilience data. In the example, reader view 700 presents results from other entities that have shared earthquake plans, news, communications, and or media regarding earthquake preparation. In some embodiments, reader view 700 presents additional fields associated with results 712A-712C, which may be customizable by a user. Further, results 712A-712C may be selected to present at least some of the data in data preview area 720. For example, data item 712A is shown as selected in reader view 700.
In some embodiments, an analyst may set up a feed through reader view 700 to receive updates and/or notifications regarding particular topics shared through city resiliency sharing system 100. For example, reader view 700 may receive input including keywords and/or predetermined feeds to notify an analyst when new data is received from city resiliency sharing system 100 with the corresponding keyword and/or shared under a predetermined feed. Non-limiting examples of keywords and/or feeds include “Earthquake Legislation,” “Law Enforcement, “Homelessness,” etc.
As illustrated in example data preview area 720, a selected resilience data item may be partially previewed in reader view 700. For example, data content area 726 presents the data item, here a document, in a human readable form. Example data preview area 720 includes a sharing selector 722A, which allows an analyst to share the data item through city resiliency sharing system 100 and/or one or more electronic communication protocols such as, for example, email and/or an instant messenger. Example data preview area 720 further includes pop out selector 722B to present the data item in a separate window. Further, example data preview area 720 includes a citation input area 724 to receive a footnote and/or citation input classification. Additionally or alternatively, data preview area 720 may include functionality regarding snippets as described in further detail in the Reader References, such as U.S. patent application Ser. No. 14/332,306. In some embodiments, data preview area 720 includes additional selectors, any of interface elements 722A, 722B, 724, and/or some combination thereof. Other variations in the reader user interface 700A are included in the Reader references and may implemented by the city resiliency systems discussed herein.
Continuing with the example, the human analyst may have numerous city documents and/or data items to look through. As illustrated, a human analyst may have 305 resilience data items to review related to earthquakes and would like to efficiently locate documents specifically related to earthquake legislation. In some embodiments, resilience data items may be exported to a clustering view to allow a human analyst efficiently analyze the resilience data items.
Referring to
In the example, an analyst may be interested in which cities are associated with one or more data items and/or documents. An example method for searching includes searching around a “city” data object. As illustrated, a user may select a “search around” menu option 820 for a “city” menu item 822.
Referring to
As illustrated, example document 812C is associated with “City 1” 820A. Further, user interface 800B visualizes the association between objects 812C and 820A by the “appears in” association 872B. In the example, City 1 “appears in” the “Building Legislation” document 812C. As described in the Clustering references, associations between data objects may be determined based on common property values between data objects. For example, the string value for the name of data object 820A, “City 1,” may appear in and/or match the text data (a property value) of document 812C. Another example, described below, is the name of a person data object, “Person 1,” matching in whole or in part a property value of a data object, such as “Author.” Any data object supported by the ontology and/or city resiliency sharing system 100 may be presented in cluster view 800A-800B. For example, a person object 830A (e.g., “Person 1,” the Chief Resilience Officer of City 1) is shown as associated with the document 812C (via association 872A illustrating an “appears in” and an “author of” relationship). Thus, an analyst may quickly identify Person 1 as a key person involved with the “Building Legislation” document 812C. In some embodiments, cluster view 800A-800B is capable of presenting property values associated with a presented object. Non-limiting property values associated with objects include object name, date created, last update time, etc. For example, user interface 800B can present property values associated with person object 830A upon selection and/or hovering a cursor over person object 830A. Non-limiting property values associated with an example person object include the person's name, date of birth, known contacts, title, contact information, employer, affiliations with organizations, etc. Non-limiting example property values to identify associations between resilience data include author (including co-authors), editor, recipient, or persons mentioned in data objects. Non-limiting example associations include: resilience data object to document object, person data object to communication object, resilience data object to building data object, etc.
In some embodiments, additional details regarding processes for clustering of data objects, identifying related data objects, and/or user interfaces 800A-800B can be found in the Cluster references.
Referring to
While not illustrated, coordinates and/or geolocation data may be imported into a clustering view (similar to clustering views 800A-800B) to determine the residence of the buildings. For example, analyst may conduct a search in a clustering view to determine the owners of the building, and may further filter the data objects for people that are fifty-five and older to identify a potentially vulnerable set of the population. Thus, an analyst may be to determine who may be vulnerable to an earthquake and/or a major event. Continuing with the example, the filter buildings may then be imported into interactive map 902 to present a subset of the original layers 904. The layers and/or heat map (such as layer 904) may be used in a document and/or report (which may then be shared via city resiliency sharing system 100).
Referring to
Data preview area 1020 includes data content area 1026. As illustrated, by including the email address “resilience@sharingsystem.com” 1030A-1030B (or other predefined electronic communication address), city resiliency sharing system 100 includes the electronic communication into its repository and/or may be viewed by participants of city resiliency sharing system 100 (e.g., participants such as John Doe may view the electronic communication from their electronic account within city resiliency sharing system 100), as described herein. As a result, example reader view 1000 is a message board discussion history. Thus, an analyst may review the discussion history and/or contact specific persons that were participants in the electronic communication. In some embodiments, documents attached to and/or new form resource locators in electronic communications may be automatically ingested by city resiliency sharing system 100 as resilience data. Further, in some embodiments, electronic communication and/or message board discussion 1026 may be permissioned and/or shared using the sharing rules and/or access control lists described herein.
Example Sharing Processes
In some embodiments, city resiliency sharing system 100 may be applicable for various workflow processes. For example, city resiliency sharing system 100 may be compatible and/or communicate with mobile computing devices. For example, mobile computing devices may allow two-way flow of information between users in the field and analysts at a city's headquarters, allowing the city's analysts to enhance situational awareness on the ground; transmit data, messages, and other media such as images and video between headquarters and the field; and monitor the location of all mobile users. In a building inspection example, a building inspector collects building inspection data from a mobile computing device and shares it via the city resiliency sharing system 100. The shared resilience data can build department efficiency for various tasks and/or improve disaster management in times of emergency.
Continuing with the building inspection example, a building inspector may have access to an input application, such as an example electronic form (e.g., a web form), to share data with city resiliency sharing system 100. For example, the example electronic form provides the ability to enter and/or create new data in city resiliency sharing system 100 from the field. Using the example electronic form, a city can develop standardized forms for building inspectors to use for data collection during inspections. Electronic form fields can be configured to include age of structure, materials used, number of units, building owner, building inspection information, business licenses, registration and permit information, fire retardant materials, and hazardous materials stored on site, among others. Electronic forms can also include pictures taken of the structure, geo-tagged to capture a visual of the exact location and the complaint or violation under inspection.
In some embodiments, the building inspection forms completed on a mobile computing device are automatically uploaded into city resiliency sharing system under, where they can be integrated with other information to support resilience metrics for both routine and emergency use. The following descriptions provide examples of these scenarios.
City building inspectors, via city resiliency sharing system 100, can visualize the geographic dispersion of complaints and construction projects, examine event summaries, assess trends across districts, reveal temporal patterns, and compare current building conditions and patterns with historical ones. With this information, a city can more effectively analyze risks—such as susceptibility to potential earthquake damage—and conduct targeted inspections, thereby increasing efficiency and reducing overhead costs when managing building-related issues.
In some embodiments, other city departments can easily leverage building inspection data to inform decisions across the city landscape with the data integrated into city resiliency sharing system 100. For example, city analysts could combine building information with violence reduction data sets to identify the subsets of the population that are most vulnerable to crime. One way of doing this is by using energy distribution and usage as an indicator of economic vitality, and correlating the age of a building to the probable age and vulnerability of its residents. City analysts could use these insights to inform violence reduction and/or other public safety initiatives. For example, the strategies discussed herein may be used to automatically generate clusters directed towards violence reduction and/or other public safety initiatives.
Further, in addition to the earthquake legislation provided herein, city resiliency sharing system 100 can provide reliable data for use in evaluating structures. This may reduce the need for expensive reports conducted by specialized analysts, and the standardized nature of data across all buildings will produce more reliable final results.
In an emergency example, a Chief Resilience Officer (“CRO”) and other resilience professionals can use city resiliency sharing system 100 to enhance response and recovery for major events by pushing critical information to first responders and/or to a department of emergency management.
City analysts can identify the most vulnerable areas in the city by combining open source information, such as building data, natural hazard and weather data, geological data, and census data, with department-specific data sets, including disability population statistics from the Health Department, housing construction data from the Planning Department, and water and gas maintenance project information from the Department of Public Works. This information can be sorted based on fire or police districts, giving first responders an accurate view of potential problem areas before an event strikes.
Continuing with the emergency example, this same information can help city officials identify the most efficient supply drop and distribution locations. For example, certain street corners may be ideal places for supply distribution because they are located on solid ground that is less likely to be adversely affected by an event and that can provide maximum accessibility to nearby residents. Analyses such as overlaying maps of potential supply drop locations with maps of streetlights can ensure that city officials choose well-lit locations, which are safer for residents and less likely to be targeted by criminals.
City resiliency sharing 100 may be useful in many emergency situations. For example, particular areas may be more susceptible to looting and crime if adequate resources are not provided after the disaster. Understanding indicators from historic data and mapping commercial stores in an area is essential in directing supplies to the right locations, which can help curb panic and reduce criminal incidents when law enforcement is already stretched to its limits. In times of emergency, city resiliency sharing system 100 can help city officials place resources and enforcement mechanisms for maximum impact on public safety. For example, the user interfaces and/or strategies described herein can provide city analysts the tools to effectively handle city emergencies.
At block 1102, city resiliency sharing system 100 and/or electronic communication listener 650 optionally receives electronic communication. For example, electronic communication listener 650 receives electronic communication 1026 of
At block 1104, city resiliency sharing system 100 and/or electronic communication listener 650 optionally converts the electronic communication into resilience data. In the example, electronic communication listener 650 converts the electronic communication by generating resilience data from the electronic communication. Example resilience data from an electronic communication includes a communication object with properties and property values from the electronic communication, such as, but not limited to, subject, to, from, cc, bcc, body, text data, and/or other data from electronic communications. Additionally or alternatively, electronic communication listener 650 associates the electronic communication 1026 with an access control list and/or sharing rule. For example, the email address, sender, and or recipients may be used by electronic communication listener 650 in conjunction with an access control lists and sharing rules to determine which entities the electronic communication should be shared with.
At block 1106, city resiliency sharing system 100 receives the resilience data. For example, resilience data may be received and presented in a reader view such as user interface 700 of
At blocks 1108 and 1110 city resiliency sharing system 100 (including reader unit 620, cluster unit 630, and/or interactive map unit 640) may continue in a loop of receiving user input and causing presentation of resilience data. For example, one or more selections in user interface 700 and/or received user input from user interface 700 causes presentation of resilience data (such as searching for “earthquakes,” a search keyword, in search input area 702). In another example, clustering view 800A-800B may receive user selections for “searching around” a resilience data object and/or cause presentation of related resilience data objects (such as presenting documents, person objects, electronic communications related to a city and/or a particular document). In another example, interactive map 900 may receive user input via user navigation input, layer selection, and/or import of data from another user interface such as, for example, the reader view and/or clustering the view.
At block 1112, city resiliency sharing system 100 may generate new resilience data and/or receive new resilience data. For example, new resilience data may be automatically generated by city resiliency sharing system 100 as described herein. Additionally or alternatively, an analyst may generate a new report and/or electronic communication that is uploaded into city resiliency sharing system 100. In the analyst generated resilience data example, the analysts may use data gathered from one or more of the user interfaces 700, 800A-800B, 900, and/or 1400 such as persons referenced in documents shown in reader view 700, data located through clustered associations in clustering view 800A-800B, and/or geolocation data from interactive map 900. Continuing with the example, the user may extract data from user interfaces 700, 800A-800B, 900, and/or 1400 by copying, clipping, citing, and/or otherwise reproducing some of the data from user interfaces 700, 800A-800B, 900, and/or 1400 in new resilience data.
At blocks 1114 and/or 1116, city resiliency sharing system 100 optionally receives a sharing command and shares the new resilience data. A sharing command may be issued through any of the user interfaces 700, 800A, 800B, 900, 1000, and/or 1400. Sharing via city resiliency sharing system 100 at block 1116 may be similar to processes 200 and/or 300 of
Example Resilience Strategies
Beginning at block 1202, resilience data, such as building data, reports, electronic communications, is received from one or more data sources and/or entities. For example, earthquake data may include hundreds or thousands of buildings and or structures that have been affected by an earthquake. The data corresponding to the earthquake may be received by city resiliency sharing system 100. In some embodiments, resilience data may be received from multiple entities such as earthquakes at different cities. Other resilience data may include business and or economic data indicating the number of businesses that are opened and or closed over a period of time within a geographic area.
At block 1204, a pattern may be recognized based on the resilience data. A detected and/or recognized pattern may indicate generalized properties and/or characteristics regarding the event. In the natural disaster example, a detected pattern may indicate the economic impacts of a natural disaster over time, such as the closing of businesses following an earthquake or flood. In some embodiments, pattern recognition is automatic, manual, or some combination thereof.
In some embodiments, recognition of patterns occurs by the systems, methods, and/or techniques disclosed in the Cluster references. For example, resilience data may be visualized by user interface clusters, as discussed below with reference to
At block 1206, a strategy may be generated from the recognized pattern. In some embodiments, generation of strategies is automatic, manual, or some combination thereof.
At block 1208, the strategy may be optionally modified for sharing, such as in the manner discussed with reference to
At block 1210, city resiliency sharing system 100 may share the strategy with one or more other entities or external systems. The strategy may be provided by the entity 110A to city resiliency sharing system 100, such as via the network 120 of
In some embodiments, sharing of the strategy generated at block 1206 occurs by the systems, methods, and/or techniques disclosed in the Sharing references. For example, a strategy may be shared and/or deconflicted through a replicated database system as illustrated by U.S. Pat. No. 8,515,912, thereby preventing duplicate and/or conflicting copies of data. Strategies may also be shared through a database system with multiple ontologies as illustrated by U.S. patent application Ser. No. 13/076,804. The sharing of the strategy may also occur via incremental database replication as illustrated by U.S. patent application Ser. No. 13/922,437.
In some embodiments, secure sharing of strategies may occur through audited activity logs occurs by the systems, methods, and/or techniques disclosed in the Audit reference. For example, sharing activity may be stored in cryptographically immutable audit logs that can be quickly analyzed for suspicious user behavior.
In some embodiments, the clusters generated by the systems, methods, and/or techniques disclosed in the Cluster references and/or other city information may be shared by the systems, methods, and/or techniques disclosed in the Sharing references, other mechanisms illustrated in this disclosure, and/or any other manner.
At block 1212, the strategy that is received at city resiliency sharing system 100 is wholly or partially shared with one or more entities 110. For example, if the strategy is received from entity 110A, city resiliency sharing system 100 may share the strategy to entities 110B, 110C, and/or external systems, such as in accordance with sharing preferences of the entities.
At block 1214, the strategy may be optionally executed by the external system and/or entity as described in further detail herein. For example, execution of the strategy at an entity can access one or more data objects associated with the second entity to identify a potential city resiliency issue (see
Example strategy 1310 includes code instructions to determine potential businesses that may be affected by a flood and/or to estimate the economic impact of a flood in a city. As illustrated, strategy 1310 accesses businesses within a flood area of the city. In the example, city resiliency sharing system 100 accesses resilience data that includes business location data and geographic data associated with the city. Also as described herein, the resilience data may be accessed as data objects, which may be used by strategy 1310. Continuing with the example, strategy 1310 iterates through each business and determines if the business is a size and/or occupies a geographic space below a threshold. For example, businesses of a size within 25 square meters, such as a local convenience store, may satisfy the threshold. Further, strategy 1310 determines whether the business is a small business. For example, city resiliency sharing system 100 may include publicly available small business data (e.g., federal and/or local government loan, grant, tax incentive, and/or venture capital information), which may be used by strategy 1310 to determine whether the business qualifies as a small business. In some embodiments, checking for small businesses in strategy 1310 is optional. If the business satisfies the conditions of strategy 1310, then a cluster may be constructed, such as by using a business identifier and/or geographic location as a seed (as described herein and in the Cluster references) constructing a cluster around the seed. An example cluster generated from a strategy is described in further detail with reference to
Example strategy 1320 includes code instructions to determine geographic areas within the city associated with criminal activity and load streetlight conditions. As illustrated, strategy 1320, accesses known streetlight locations within a city. In the example, city resiliency sharing system 100 includes resilience data regarding the locations of streetlights. As described herein, city resiliency sharing system 100 can be integrated with and/or receive data from a streetlight data store associated with a streetlight department within a city such as a Bureau of Street Lighting. Continuing with the example, strategy 1320 accesses crime reports within the city. The example crime report data objects may include the location of the reported crime, time of the crime, type of crime, etc. Again, similar to receiving data from streetlights, city resiliency sharing system 100 can be integrated with and/or receive data from police departments, which may include police and/or crime reports. Strategy 1320 then iterates through geographic areas within the city, such as city blocks and/or particular predetermined square meter areas (such as 80 m×270 m, for example). For each geographic area, strategy 1320 determines whether the geographic area satisfies crime reporting and low streetlight conditions. For example, the crime reporting condition in strategy 1320 can be satisfied where one or more crime reports (or some other predetermined threshold) are reported within the geographic area and/or other conditions such as severity and/or time of the crime, such as burglaries and/or crimes that occur after sunset (e.g. 6 or 7 P.M.). Further, example strategy 1320 determines whether low streetlight conditions are satisfied where there are no streetlights in the area or a number below a threshold such as one or two streetlights. If the geographic area satisfies the conditions of strategy 1320, then a cluster may be constructed, such as by using the geographic location as a seed (as described herein and in the Cluster references) constructing a cluster around the seed (e.g., adding the crime report to the cluster).
Other strategies may be apparent from the disclosure herein. For example, historical building data may be used to determine a strategy for identify potentially structurally unsafe buildings and/or buildings that may require additional inspections.
In some embodiments, strategies may comprise various formats and/or combinations of formats. For example, a strategy may comprise executable code instructions and/or a parameterized format. In the executable code instructions example, the executable code instructions may comprise programming logic to detect one or more conditions. In the parameterized format, a XML document may comprise parameters and/or configurations. For example, the XML documents may comprise parameters for checking different values above a threshold, e.g., a threshold percentage for a notification and/or generation of a cluster. Thus, both the code instructions and the parameterized format, such as, but not limited to, XML, may be shared through the city resiliency sharing system.
Referring to
As illustrated, data object area 802 includes a cluster of resilience data items and/or objects 1410A-1410C. For example, the cluster including objects 1410A-1410C may be the output of strategy 1310 referenced in
Example Implementation Mechanisms
The various computing device(s) discussed herein, such as the entities 110 and/or city resiliency sharing system 100, are generally controlled and coordinated by operating system software, such as, but not limited to, iOS, Android, Chrome OS, Windows XP, Windows Vista, Windows 7, Windows 8, Windows Server, Windows CE, Unix, Linux, SunOS, Solaris, Macintosh OS X, VxWorks, or other compatible operating systems. In other embodiments, the computing devices 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. The city resiliency sharing system 100 may be hosted and/or executed on one or more computing devices with one or more hardware processors and with any of the previously mentioned operating system software.
The city resiliency sharing system 100 may execute software, e.g., standalone software applications, applications within browsers, network applications, etc., whether by the particular application, the operating system, or otherwise. Any of the systems discussed herein may be performed by the city resiliency sharing system 100 and/or a similar computing system having some or all of the components discussed with reference to
The city resiliency sharing system 100 includes a bus 1502 or other communication mechanism for communicating information, and a hardware processor, or multiple processors, 1504 coupled with bus 1502 for processing information. Hardware processor(s) 1504 may be, for example, one or more general purpose microprocessors.
The city resiliency sharing system 100 also includes a main memory 1506, such as a random access memory (RAM), cache and/or other dynamic storage devices, coupled to bus 1502 for storing information and instructions to be executed by processor(s) 1504. Main memory 1506 also may be used for storing temporary variables or other intermediate information during execution of instructions to be executed by processor(s) 1504. Such instructions, when stored in storage media accessible to processor(s) 1504, render the city resiliency sharing system 100 into a special-purpose machine that is customized to perform the operations specified in the instructions. Such instructions, as executed by hardware processors, may implement the methods and systems described herein for sharing city resiliency information.
The city resiliency sharing system 100 further includes a read only memory (ROM) 1508 or other static storage device coupled to bus 1502 for storing static information and instructions for processor(s) 1504. A storage device 1510, such as a magnetic disk, optical disk, or USB thumb drive (Flash drive), etc., is provided and coupled to bus 1502 for storing information and instructions. The workflow unit 428, strategy unit 430, resilience data modification unit 440, strategy data store 432, and/or resilience data store 442 of
In some embodiments, the strategy data store 432 of
The city resiliency sharing system 100 may be coupled via bus 1502 to a display 1512, such as a cathode ray tube (CRT) or LCD display or touch screen, for displaying information to a computer user. An input device 1514 is coupled to bus 1502 for communicating information and command selections to processor 1504. One type of input device 1514 is a keyboard including alphanumeric and other keys. Another type of input device 1514 is a touch screen. Another type of user input device is cursor control 1516, such as a mouse, a trackball, a touch screen, or cursor direction keys for communicating direction information and command selections to processor 1504 and for controlling cursor movement on display 1512. This input device may have two degrees of freedom in two axes, a first axis (e.g., x) and a second axis (e.g., y), that allows the device to specify positions in a plane. In some embodiments, the same direction information and command selections as cursor control may be implemented via receiving touches on a touch screen without a cursor.
The city resiliency sharing system 100 may include a reader unit 620, cluster unit 630, and/or interactive map unit 640, which may be stored in a mass storage device as executable software codes that are executed by the computing device(s). This and other units 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 “instructions,” “code,” and/or “code instructions,” as used herein, refers to logic embodied in hardware or firmware, or to a collection of software units, possibly having entry and exit points, written in a programming language, such as, but not limited to, Java, Lua, C, C++, or C#. A software unit 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, but not limited to, BASIC, Perl, or Python. It will be appreciated that software units may be callable from other units or from themselves, and/or may be invoked in response to detected events or interrupts. Software units configured for execution on computing devices by their hardware processor(s) 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. Generally, the instructions described herein refer to logical modules that may be combined with other modules or divided into sub-modules despite their physical organization or storage.
The city resiliency sharing system 100, or components of it, such as workflow unit 428, strategy unit 430, resilience data modification unit 440, reader unit 620, cluster unit 630, interactive map unit 640, and/or electronic communication listener 650, may be programmed, via executable code instructions, in a programming language.
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 1510. Volatile media includes dynamic memory, such as main memory 1506. 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 1502. 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(s) 1504 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 may load the instructions into its dynamic memory and send the instructions over a telephone or cable line using a modem. A modem local to the city resiliency sharing system 100 may receive the data on the telephone or cable 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 1502. Bus 1502 carries the data to main memory 1506, from which the processor(s) 1504 retrieves and executes the instructions. The instructions received by main memory 1506 may retrieve and execute the instructions. The instructions received by main memory 1506 may optionally be stored on storage device 1510 either before or after execution by processor(s) 1504.
The city resiliency sharing system 100 also includes a communication interface 1518 coupled to bus 1502. Communication interface 1518 provides a two-way data communication coupling to a network link 1520 that is connected to a local network 1522. For example, communication interface 1518 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 1518 may be a local area network (LAN) card to provide a data communication connection to a compatible LAN (or WAN component to be communicated with a WAN). Wireless links may also be implemented. In any such implementation, communication interface 1518 sends and receives electrical, electromagnetic or optical signals that carry digital data streams representing various types of information.
Network link 1520 typically provides data communication through one or more networks to other data devices. For example, network link 1520 may provide a connection through local network 1522 to a host computer 1524 or to data equipment operated by an Internet Service Provider (ISP) 1526. ISP 1526 in turn provides data communication services through the world wide packet data communication network now commonly referred to as the “Internet” 1528. Local network 1522 and Internet 1528 both use electrical, electromagnetic or optical signals that carry digital data streams. The signals through the various networks and the signals on network link 1520 and through communication interface 1518, which carry the digital data to and from the city resiliency sharing system 100, are example forms of transmission media.
The city resiliency sharing system 100 can send messages and receive data, including program code, through the network(s), network link 1520 and communication interface 1518. In the Internet example, a server 1530 might transmit a requested code for an application program through Internet 1528, ISP 1526, local network 1522 and communication interface 1518.
The received code may be executed by processor(s) 1504 as it is received, and/or stored in storage device 1510, 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 instructions 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 units, 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.
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. This application claims benefit of U.S. Provisional Patent Application Ser. No. 62/020,616 entitled “City Resiliency Data Sharing System” filed Jul. 3, 2014, which is hereby incorporated by reference in its entirety. This application is related to but does not claim priority from U.S. patent application Ser. No. 13/968,265 entitled “Generating Data Clusters With Customizable Analysis Strategies” filed Aug. 15, 2013, and U.S. patent application Ser. No. 13/968,213 entitled “Prioritizing Data Clusters With Customizable Scoring Strategies” filed Aug. 15, 2013, each of which are hereby incorporated by reference in their entireties and collectively referred to herein as the “Cluster references.” This application is related to but does not claim priority from U.S. Pat. No. 8,515,912 entitled “Sharing And Deconflicting Data Changes In A Multimaster Database System” filed Jul. 15, 2010, U.S. Pat. No. 8,527,461 entitled “Cross-ACL Multi-Master Replication” filed Nov. 27, 2012, U.S. patent application Ser. No. 13/076,804 entitled “Cross-Ontology Multi-Master Replication” filed Mar. 31, 2011, U.S. patent application Ser. No. 13/657,684 entitled “Sharing Information Between Nexuses That Use Different Classification Schemes For Information Access Control” filed Oct. 22, 2012, and U.S. patent application Ser. No. 13/922,437 entitled “System And Method For Incrementally Replicating Investigative Analysis Data” filed Jun. 20, 2013, each of which are hereby incorporated by reference in their entireties and collectively referred to herein as the “Sharing references.” This application is related to but does not claim priority from U.S. Pat. No. 8,489,623 entitled “Creating Data In A Data Store Using A Dynamic Ontology” filed May 12, 2011, which is hereby incorporated by reference in its entirety and referred to herein as the “Ontology reference.” This application is related to but does not claim priority from U.S. patent application Ser. No. 14/223,918 entitled “Verifiable Redactable Audit Log” filed Mar. 24, 2014, which is hereby incorporated by reference in its entirety and referred to herein as the “Audit reference.” This application is related to but does not claim priority from U.S. Provisional Patent Application Ser. No. 61/863,792 entitled “Cable Reader Labeling” filed Aug. 8, 2013, U.S. patent application Ser. No. 14/332,312 entitled “Cable Reader Labeling” filed Jul. 15, 2014, U.S. Provisional Patent Application Ser. No. 61/863,814 entitled “Cable Reader Snippets and Postboard” filed Aug. 8, 2013, and U.S. patent application Ser. No. 14/332,306 entitled “Cable Reader Snippets and Postboard” filed Jul. 15, 2014, each of which are hereby incorporated by reference in their entireties and collectively referred to herein as the “Reader references.” This application is related to but does not claim priority from U.S. patent application Ser. No. 13/917,571 entitled “Interactive Geospatial Map” filed Jun. 13, 2013, which is hereby incorporated by reference in its entirety and referred to herein as the “Map reference.” This application is related to but does not claim priority from U.S. Pat. No. 9,009,827 entitled “Security Sharing System” filed May 16, 2014, and U.S. patent application Ser. No. 14/518,757 entitled “Healthcare Fraud Sharing System” filed Oct. 20, 2014, which are hereby incorporated by reference in their entireties.
| Number | Name | Date | Kind |
|---|---|---|---|
| 5109399 | Thompson | Apr 1992 | A |
| 5329108 | Lamoure | Jul 1994 | A |
| 5548749 | Kroenke et al. | Aug 1996 | A |
| 5632009 | Rao et al. | May 1997 | A |
| 5670987 | Doi et al. | Sep 1997 | A |
| 5708828 | Coleman | Jan 1998 | A |
| 5765171 | Gehani et al. | Jun 1998 | A |
| 5781704 | Rossmo | Jul 1998 | A |
| 5845300 | Comer | Dec 1998 | A |
| 5870761 | Demers et al. | Feb 1999 | A |
| 6057757 | Arrowsmith et al. | May 2000 | A |
| 6091956 | Hollenberg | Jul 2000 | A |
| 6098078 | Gehani et al. | Aug 2000 | A |
| 6161098 | Wallman | Dec 2000 | A |
| 6190053 | Stahlecker et al. | Feb 2001 | B1 |
| 6202085 | Benson et al. | Mar 2001 | B1 |
| 6216140 | Kramer | Apr 2001 | B1 |
| 6219053 | Tachibana et al. | Apr 2001 | B1 |
| 6232971 | Haynes | May 2001 | B1 |
| 6240414 | Beizer et al. | May 2001 | B1 |
| 6247019 | Davies | Jun 2001 | B1 |
| 6279018 | Kudrolli et al. | Aug 2001 | B1 |
| 6289338 | Stoffel et al. | Sep 2001 | B1 |
| 6317754 | Peng | Nov 2001 | B1 |
| 6341310 | Leshem et al. | Jan 2002 | B1 |
| 6369835 | Lin | Apr 2002 | B1 |
| 6374252 | Althoff et al. | Apr 2002 | B1 |
| 6456997 | Shukla | Sep 2002 | B1 |
| 6463404 | Appleby | Oct 2002 | B1 |
| 6505196 | Drucker et al. | Jan 2003 | B2 |
| 6523019 | Borthwick | Feb 2003 | B1 |
| 6523172 | Martinez-Guerra et al. | Feb 2003 | B1 |
| 6539381 | Prasad et al. | Mar 2003 | B1 |
| 6549944 | Weinberg et al. | Apr 2003 | B1 |
| 6560620 | Ching | May 2003 | B1 |
| 6567936 | Yang et al. | May 2003 | B1 |
| 6581068 | Bensoussan et al. | Jun 2003 | B1 |
| 6594672 | Lampson et al. | Jul 2003 | B1 |
| 6631496 | Li et al. | Oct 2003 | B1 |
| 6640231 | Andersen et al. | Oct 2003 | B1 |
| 6642945 | Sharpe | Nov 2003 | B1 |
| 6714936 | Nevin, III | Mar 2004 | B1 |
| 6748481 | Parry et al. | Jun 2004 | B1 |
| 6775675 | Nwabueze et al. | Aug 2004 | B1 |
| 6807569 | Bhimani et al. | Oct 2004 | B1 |
| 6816941 | Carlson et al. | Nov 2004 | B1 |
| 6828920 | Owen et al. | Dec 2004 | B2 |
| 6839745 | Dingari et al. | Jan 2005 | B1 |
| 6877137 | Rivette et al. | Apr 2005 | B1 |
| 6938034 | Kraft | Aug 2005 | B1 |
| 6976210 | Silva et al. | Dec 2005 | B1 |
| 6980984 | Huffman et al. | Dec 2005 | B1 |
| 6985950 | Hanson et al. | Jan 2006 | B1 |
| 7027974 | Busch et al. | Apr 2006 | B1 |
| 7036085 | Barros | Apr 2006 | B2 |
| 7043702 | Chi et al. | May 2006 | B2 |
| 7055110 | Kupka et al. | May 2006 | B2 |
| 7072911 | Doman | Jul 2006 | B1 |
| 7139800 | Bellotti et al. | Nov 2006 | B2 |
| 7158878 | Rasmussen et al. | Jan 2007 | B2 |
| 7162475 | Ackerman | Jan 2007 | B2 |
| 7167877 | Balogh et al. | Jan 2007 | B2 |
| 7168039 | Bertram | Jan 2007 | B2 |
| 7171427 | Witowski et al. | Jan 2007 | B2 |
| 7237192 | Stephenson et al. | Jun 2007 | B1 |
| 7240330 | Fairweather | Jul 2007 | B2 |
| 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 |
| 7373669 | Eisen | May 2008 | B2 |
| 7379811 | Rasmussen et al. | May 2008 | B2 |
| 7379903 | Caballero et al. | May 2008 | B2 |
| 7418431 | Nies et al. | Aug 2008 | B1 |
| 7426654 | Adams et al. | Sep 2008 | B2 |
| 7437664 | Borson | Oct 2008 | B2 |
| 7451397 | Weber et al. | Nov 2008 | B2 |
| 7454466 | Bellotti 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 |
| 7525422 | Bishop et al. | Apr 2009 | B2 |
| 7529727 | Arning et al. | May 2009 | B2 |
| 7529734 | Dirisala | May 2009 | B2 |
| 7533069 | Fairweather | May 2009 | B2 |
| 7546245 | Surpin et al. | Jun 2009 | B2 |
| 7558677 | Jones | 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 |
| 7596608 | Alexander | Sep 2009 | B2 |
| 7614006 | Molander | Nov 2009 | B2 |
| 7617232 | Gabbert et al. | Nov 2009 | B2 |
| 7620628 | Kapur et al. | Nov 2009 | B2 |
| 7627812 | Chamberlain et al. | Dec 2009 | B2 |
| 7634717 | Chamberlain et al. | Dec 2009 | B2 |
| 7640173 | Surpin et al. | Dec 2009 | B2 |
| 7676788 | Ousterhout et al. | Mar 2010 | B1 |
| 7685083 | Fairweather | Mar 2010 | B2 |
| 7703021 | Flam | Apr 2010 | B1 |
| 7712049 | Williams et al. | May 2010 | B2 |
| 7716067 | Surpin et al. | May 2010 | B2 |
| 7716077 | Mikurak | May 2010 | B1 |
| 7725547 | Albertson et al. | May 2010 | B2 |
| 7730396 | Chidlovskii et al. | Jun 2010 | B2 |
| 7770100 | Chamberlain et al. | Aug 2010 | B2 |
| 7783658 | Bayliss | Aug 2010 | B1 |
| 7792664 | Crawford | Sep 2010 | B1 |
| 7805457 | Viola et al. | Sep 2010 | B1 |
| 7809703 | Balabhadrapatruni et al. | Oct 2010 | B2 |
| 7813937 | Pathria et al. | Oct 2010 | B1 |
| 7814102 | Miller et al. | Oct 2010 | B2 |
| 7818297 | Peleg et al. | Oct 2010 | B2 |
| 7818658 | Chen | Oct 2010 | B2 |
| 7827045 | Madill et al. | Nov 2010 | B2 |
| 7877421 | Berger et al. | Jan 2011 | B2 |
| 7894984 | Rasmussen et al. | Feb 2011 | B2 |
| 7899611 | Downs et al. | Mar 2011 | B2 |
| 7912837 | Buron | Mar 2011 | B2 |
| 7917376 | Bellin et al. | Mar 2011 | B2 |
| 7920963 | Jouline et al. | Apr 2011 | B2 |
| 7933862 | Chamberlain et al. | Apr 2011 | B2 |
| 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 |
| 8001465 | Kudrolli et al. | Aug 2011 | B2 |
| 8001482 | Bhattiprolu et al. | Aug 2011 | B2 |
| 8010545 | Stefik et al. | Aug 2011 | B2 |
| 8010886 | Gusmorino et al. | Aug 2011 | B2 |
| 8015151 | Lier et al. | Sep 2011 | B2 |
| 8015487 | Roy et al. | Sep 2011 | B2 |
| 8019709 | Norton et al. | Sep 2011 | B2 |
| 8024778 | Cash et al. | Sep 2011 | B2 |
| 8036632 | Cona et al. | Oct 2011 | B1 |
| 8046362 | Bayliss | Oct 2011 | B2 |
| 8082172 | Chao et al. | Dec 2011 | B2 |
| 8095434 | Puttick | Jan 2012 | B1 |
| 8103543 | Zwicky | Jan 2012 | B1 |
| 8117022 | Linker | Feb 2012 | B2 |
| 8132149 | Shenfield et al. | Mar 2012 | B2 |
| 8134457 | Velipasalar et al. | Mar 2012 | B2 |
| 8135679 | Bayliss | Mar 2012 | B2 |
| 8135719 | Bayliss | Mar 2012 | B2 |
| 8145703 | Frishert et al. | Mar 2012 | B2 |
| 8196184 | Amirov et al. | Jun 2012 | B2 |
| 8214232 | Tyler et al. | Jul 2012 | B2 |
| 8214361 | Sandler et al. | Jul 2012 | B1 |
| 8214764 | Gemmell et al. | Jul 2012 | B2 |
| 8225201 | Michael | Jul 2012 | B2 |
| 8229947 | Fujinaga | Jul 2012 | B2 |
| 8230333 | Decherd et al. | Jul 2012 | B2 |
| 8239668 | Chen et al. | Aug 2012 | B1 |
| 8266168 | Bayliss | Sep 2012 | B2 |
| 8271948 | Talozi et al. | Sep 2012 | B2 |
| 8280880 | Aymeloglu et al. | Oct 2012 | B1 |
| 8290942 | Jones et al. | Oct 2012 | B2 |
| 8290990 | Drath et al. | Oct 2012 | B2 |
| 8301464 | Cave et al. | Oct 2012 | B1 |
| 8301904 | Gryaznov | Oct 2012 | B1 |
| 8312367 | Foster | Nov 2012 | B2 |
| 8312546 | Alme | Nov 2012 | B2 |
| 8316060 | Snyder et al. | Nov 2012 | B1 |
| 8321943 | Walters et al. | Nov 2012 | B1 |
| 8347398 | Weber | Jan 2013 | B1 |
| 8352881 | Champion et al. | Jan 2013 | B2 |
| 8368695 | Howell et al. | Feb 2013 | B2 |
| 8380659 | Zunger | Feb 2013 | B2 |
| 8397171 | Klassen et al. | Mar 2013 | B2 |
| 8411046 | Kruzeniski et al. | Apr 2013 | B2 |
| 8412707 | Mianji | Apr 2013 | B1 |
| 8442940 | Faletti et al. | May 2013 | B1 |
| 8447674 | Choudhuri et al. | May 2013 | B2 |
| 8447722 | Ahuja et al. | May 2013 | B1 |
| 8452790 | Mianji | May 2013 | B1 |
| 8463036 | Ramesh et al. | Jun 2013 | B1 |
| 8484168 | Bayliss | Jul 2013 | B2 |
| 8489331 | Kopf et al. | Jul 2013 | B2 |
| 8489623 | Jain et al. | Jul 2013 | B2 |
| 8489641 | Seefeld et al. | Jul 2013 | B1 |
| 8495077 | Bayliss | Jul 2013 | B2 |
| 8498969 | Bayliss | Jul 2013 | B2 |
| 8498984 | Hwang et al. | Jul 2013 | B1 |
| 8514082 | Cova et al. | Aug 2013 | B2 |
| 8515207 | Chau | Aug 2013 | B2 |
| 8515912 | Garrod et al. | Aug 2013 | B2 |
| 8527461 | Ducott, III et al. | Sep 2013 | B2 |
| 8554579 | Tribble et al. | Oct 2013 | B2 |
| 8554653 | Falkenborg et al. | Oct 2013 | B2 |
| 8554709 | Goodson et al. | Oct 2013 | B2 |
| 8577911 | Stepinski et al. | Nov 2013 | B1 |
| 8578500 | Long | Nov 2013 | B2 |
| 8589273 | Creeden et al. | Nov 2013 | B2 |
| 8600872 | Yan | Dec 2013 | B1 |
| 8620641 | Farnsworth et al. | Dec 2013 | B2 |
| 8639522 | Pathria et al. | Jan 2014 | B2 |
| 8646080 | Williamson et al. | Feb 2014 | B2 |
| 8676597 | Buehler et al. | Mar 2014 | B2 |
| 8676857 | Adams et al. | Mar 2014 | B1 |
| 8688749 | Ducott, III et al. | Apr 2014 | B1 |
| 8689108 | Duffield et al. | Apr 2014 | B1 |
| 8689182 | Leithead et al. | Apr 2014 | B2 |
| 8707185 | Robinson et al. | Apr 2014 | B2 |
| 8713467 | Goldenberg et al. | Apr 2014 | B1 |
| 8726379 | Stiansen et al. | May 2014 | B1 |
| 8739278 | Varghese | May 2014 | B2 |
| 8742934 | Sarpy et al. | Jun 2014 | B1 |
| 8745516 | Mason et al. | Jun 2014 | B2 |
| 8781169 | Jackson et al. | Jul 2014 | B2 |
| 8788405 | Sprague et al. | Jul 2014 | B1 |
| 8788407 | Singh et al. | Jul 2014 | B1 |
| 8799799 | Cervelli et al. | Aug 2014 | B1 |
| 8799812 | Parker | Aug 2014 | B2 |
| 8812960 | Sun et al. | Aug 2014 | B1 |
| 8818892 | Sprague et al. | Aug 2014 | B1 |
| 8830322 | Nerayoff et al. | Sep 2014 | B2 |
| 8832594 | Thompson et al. | Sep 2014 | B1 |
| 8832832 | Visbal | Sep 2014 | B1 |
| 8868486 | Tamayo | Oct 2014 | B2 |
| 8917274 | Ma et al. | Dec 2014 | B2 |
| 8924872 | Bogomolov et al. | Dec 2014 | B1 |
| 8937619 | Sharma et al. | Jan 2015 | B2 |
| 9009827 | Albertson et al. | Apr 2015 | B1 |
| 9043894 | Dennison et al. | May 2015 | B1 |
| 9923925 | Albertson et al. | Mar 2018 | B2 |
| 20010021936 | Bertram | Sep 2001 | A1 |
| 20020033848 | Sciammarella et al. | Mar 2002 | A1 |
| 20020065708 | Senay et al. | May 2002 | A1 |
| 20020087328 | Denenberg | Jul 2002 | A1 |
| 20020091707 | Keller | Jul 2002 | A1 |
| 20020095658 | Shulman | Jul 2002 | A1 |
| 20020116120 | Ruiz et al. | Aug 2002 | A1 |
| 20020130907 | Chi et al. | Sep 2002 | A1 |
| 20020174201 | Ramer et al. | Nov 2002 | A1 |
| 20020194119 | Wright et al. | Dec 2002 | A1 |
| 20030028560 | Kudrolli et al. | Feb 2003 | A1 |
| 20030039948 | Donahue | Feb 2003 | A1 |
| 20030084017 | Ordille | May 2003 | A1 |
| 20030088654 | Good et al. | May 2003 | A1 |
| 20030097330 | Hillmer et al. | May 2003 | A1 |
| 20030144868 | MacIntyre et al. | Jul 2003 | A1 |
| 20030163352 | Surpin et al. | Aug 2003 | A1 |
| 20030172053 | Fairweather | Sep 2003 | A1 |
| 20030177112 | Gardner | Sep 2003 | A1 |
| 20030182313 | Federwisch et al. | Sep 2003 | A1 |
| 20030200217 | Ackerman | Oct 2003 | A1 |
| 20030225755 | Iwayama et al. | Dec 2003 | A1 |
| 20030229848 | Arend et al. | Dec 2003 | A1 |
| 20040032432 | Baynger | Feb 2004 | A1 |
| 20040064256 | Barinek et al. | Apr 2004 | A1 |
| 20040083466 | Dapp et al. | Apr 2004 | A1 |
| 20040085318 | Hassler et al. | May 2004 | A1 |
| 20040095349 | Bito et al. | May 2004 | A1 |
| 20040103124 | Kupkova | May 2004 | A1 |
| 20040111390 | Saito et al. | Jun 2004 | A1 |
| 20040111410 | Burgoon et al. | Jun 2004 | A1 |
| 20040143602 | Ruiz et al. | Jul 2004 | A1 |
| 20040153418 | Hanweck | Aug 2004 | A1 |
| 20040181554 | Heckerman et al. | Sep 2004 | A1 |
| 20040193600 | Kaasten et al. | Sep 2004 | A1 |
| 20040205524 | Richter et al. | Oct 2004 | A1 |
| 20040250124 | Chesla et al. | Dec 2004 | A1 |
| 20040250576 | Flanders | Dec 2004 | A1 |
| 20040260702 | Cragun et al. | Dec 2004 | A1 |
| 20050027705 | Sadri et al. | Feb 2005 | A1 |
| 20050028094 | Allyn | Feb 2005 | A1 |
| 20050034107 | Kendall et al. | Feb 2005 | A1 |
| 20050080769 | Gemmell | Apr 2005 | A1 |
| 20050086207 | Heuer et al. | Apr 2005 | A1 |
| 20050091420 | Snover et al. | Apr 2005 | A1 |
| 20050108063 | Madill et al. | May 2005 | A1 |
| 20050125715 | Di Franco et al. | Jun 2005 | A1 |
| 20050162523 | Darrell et al. | Jul 2005 | A1 |
| 20050180330 | Shapiro | Aug 2005 | A1 |
| 20050182793 | Keenan et al. | Aug 2005 | A1 |
| 20050183005 | Denoue et al. | Aug 2005 | A1 |
| 20050193024 | Beyer et al. | Sep 2005 | A1 |
| 20050222928 | Steier et al. | Oct 2005 | A1 |
| 20050229256 | Banzhof | Oct 2005 | A2 |
| 20050246327 | Yeung et al. | Nov 2005 | A1 |
| 20050251786 | Citron et al. | Nov 2005 | A1 |
| 20050262556 | Waisman et al. | Nov 2005 | A1 |
| 20060026120 | Carolan et al. | Feb 2006 | A1 |
| 20060026170 | Kreitler et al. | Feb 2006 | A1 |
| 20060036568 | Moore et al. | Feb 2006 | A1 |
| 20060045470 | Poslinski et al. | Mar 2006 | A1 |
| 20060059139 | Robinson | Mar 2006 | A1 |
| 20060069912 | Zheng et al. | Mar 2006 | A1 |
| 20060074866 | Chamberlain et al. | Apr 2006 | A1 |
| 20060074881 | Vembu et al. | Apr 2006 | A1 |
| 20060080619 | Carlson et al. | Apr 2006 | A1 |
| 20060106879 | Zondervan et al. | May 2006 | A1 |
| 20060129746 | Porter | Jun 2006 | A1 |
| 20060139375 | Rasmussen et al. | Jun 2006 | A1 |
| 20060149596 | Surpin et al. | Jul 2006 | A1 |
| 20060155945 | McGarvey | Jul 2006 | A1 |
| 20060190497 | Inturi et al. | Aug 2006 | A1 |
| 20060203337 | White | Sep 2006 | A1 |
| 20060206866 | Eldrige et al. | Sep 2006 | A1 |
| 20060218637 | Thomas et al. | Sep 2006 | A1 |
| 20060224579 | Zheng | Oct 2006 | A1 |
| 20060224629 | Alexander | Oct 2006 | A1 |
| 20060242040 | Rader et al. | Oct 2006 | A1 |
| 20060242630 | Koike et al. | Oct 2006 | A1 |
| 20060265747 | Judge | Nov 2006 | A1 |
| 20060271277 | Hu et al. | Nov 2006 | A1 |
| 20060273893 | Warner | Dec 2006 | A1 |
| 20060279630 | Aggarwal et al. | Dec 2006 | A1 |
| 20070005707 | Teodosiu et al. | Jan 2007 | A1 |
| 20070011150 | Frank | Jan 2007 | A1 |
| 20070015506 | Hewett, Jr. | Jan 2007 | A1 |
| 20070016363 | Huang et al. | Jan 2007 | A1 |
| 20070026373 | Suriyanarayanan et al. | Feb 2007 | A1 |
| 20070038962 | Fuchs et al. | Feb 2007 | A1 |
| 20070057966 | Ohno et al. | Mar 2007 | A1 |
| 20070074169 | Chess et al. | Mar 2007 | A1 |
| 20070078832 | Ott et al. | Apr 2007 | A1 |
| 20070078872 | Cohen | Apr 2007 | A1 |
| 20070083541 | Fraleigh et al. | Apr 2007 | A1 |
| 20070112714 | Fairweather | May 2007 | A1 |
| 20070112887 | Liu et al. | May 2007 | A1 |
| 20070168516 | Liu et al. | Jul 2007 | A1 |
| 20070174760 | Chamberlain et al. | Jul 2007 | A1 |
| 20070180075 | Chasman et al. | Aug 2007 | A1 |
| 20070192143 | Krishnan et al. | Aug 2007 | A1 |
| 20070192265 | Chopin 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 |
| 20070220067 | Suriyanarayanan et al. | Sep 2007 | A1 |
| 20070220328 | Liu et al. | Sep 2007 | A1 |
| 20070233756 | D'Souza et al. | Oct 2007 | A1 |
| 20070266336 | Nojima et al. | Nov 2007 | A1 |
| 20070294200 | Au | Dec 2007 | A1 |
| 20070294643 | Kyle | Dec 2007 | A1 |
| 20070294766 | Mir et al. | Dec 2007 | A1 |
| 20070299697 | Friedlander et al. | Dec 2007 | A1 |
| 20070299887 | Novik et al. | Dec 2007 | A1 |
| 20080027981 | Wahl | Jan 2008 | A1 |
| 20080033753 | Canda et al. | Feb 2008 | A1 |
| 20080040684 | Crump | Feb 2008 | A1 |
| 20080051989 | Welsh | Feb 2008 | A1 |
| 20080052142 | Bailey et al. | Feb 2008 | A1 |
| 20080077474 | Dumas | Mar 2008 | A1 |
| 20080077597 | Butler | Mar 2008 | A1 |
| 20080077642 | Carbone et al. | Mar 2008 | A1 |
| 20080086718 | Bostick et al. | Apr 2008 | A1 |
| 20080104019 | Nath | May 2008 | A1 |
| 20080109762 | Hundal | May 2008 | A1 |
| 20080126951 | Sood et al. | May 2008 | A1 |
| 20080133567 | Ames et al. | Jun 2008 | A1 |
| 20080140387 | Linker | Jun 2008 | A1 |
| 20080141117 | King et al. | Jun 2008 | A1 |
| 20080148398 | Mezack et al. | Jun 2008 | A1 |
| 20080162616 | Gross et al. | Jul 2008 | A1 |
| 20080189240 | Mullins et al. | Aug 2008 | A1 |
| 20080195417 | Surpin et al. | Aug 2008 | A1 |
| 20080195608 | Clover | Aug 2008 | A1 |
| 20080222295 | Robinson et al. | Sep 2008 | A1 |
| 20080228467 | Womack et al. | Sep 2008 | A1 |
| 20080229422 | Hudis et al. | Sep 2008 | A1 |
| 20080235575 | Weiss | Sep 2008 | A1 |
| 20080243951 | Webman 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 |
| 20080276167 | Michael | Nov 2008 | A1 |
| 20080278311 | Grange et al. | Nov 2008 | A1 |
| 20080281580 | Zabokritski | Nov 2008 | A1 |
| 20080288306 | MacIntyre et al. | Nov 2008 | A1 |
| 20080288425 | Posse et al. | Nov 2008 | A1 |
| 20080301643 | Appleton et al. | Dec 2008 | A1 |
| 20080320299 | Wobber et al. | Dec 2008 | A1 |
| 20090002492 | Velipasalar et al. | Jan 2009 | A1 |
| 20090018940 | Wang et al. | Jan 2009 | A1 |
| 20090027418 | Maru et al. | Jan 2009 | A1 |
| 20090030915 | Winter et al. | Jan 2009 | A1 |
| 20090044279 | Crawford et al. | Feb 2009 | A1 |
| 20090055251 | Shah et al. | Feb 2009 | A1 |
| 20090076845 | Bellin et al. | Mar 2009 | A1 |
| 20090082997 | Tokman et al. | Mar 2009 | A1 |
| 20090083184 | Eisen | Mar 2009 | A1 |
| 20090088964 | Schaaf et al. | Apr 2009 | A1 |
| 20090100165 | Wesley, Sr. | Apr 2009 | A1 |
| 20090103442 | Douville | Apr 2009 | A1 |
| 20090119309 | Gibson et al. | May 2009 | A1 |
| 20090125369 | Kloosstra et al. | May 2009 | A1 |
| 20090132921 | Hwangbo et al. | May 2009 | A1 |
| 20090132953 | Reed et al. | May 2009 | A1 |
| 20090144262 | White et al. | Jun 2009 | A1 |
| 20090144274 | Fraleigh 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 |
| 20090179892 | Tsuda et al. | Jul 2009 | A1 |
| 20090187546 | Whyte et al. | Jul 2009 | A1 |
| 20090192957 | Subramanian et al. | Jul 2009 | A1 |
| 20090199090 | Poston et al. | Aug 2009 | A1 |
| 20090222400 | Kupershmidt et al. | Sep 2009 | A1 |
| 20090222760 | Halverson et al. | Sep 2009 | A1 |
| 20090228507 | Jain et al. | Sep 2009 | A1 |
| 20090234720 | George et al. | Sep 2009 | A1 |
| 20090248828 | Gould | Oct 2009 | A1 |
| 20090254970 | Agarwal et al. | Oct 2009 | A1 |
| 20090271359 | Bayliss | Oct 2009 | A1 |
| 20090281839 | Lynn et al. | Nov 2009 | A1 |
| 20090287470 | Farnsworth et al. | Nov 2009 | A1 |
| 20090292626 | Oxford | Nov 2009 | A1 |
| 20090328222 | Helman et al. | Dec 2009 | A1 |
| 20100011282 | Dollard et al. | Jan 2010 | A1 |
| 20100042922 | Bradateanu et al. | Feb 2010 | A1 |
| 20100057716 | Stefik et al. | Mar 2010 | A1 |
| 20100070523 | Delgo et al. | Mar 2010 | A1 |
| 20100070842 | Aymeloglu et al. | Mar 2010 | A1 |
| 20100070897 | Aymeloglu et al. | Mar 2010 | A1 |
| 20100077481 | Polyakov et al. | Mar 2010 | A1 |
| 20100077483 | Stolfo et al. | Mar 2010 | A1 |
| 20100100963 | Mahaffey | Apr 2010 | A1 |
| 20100114887 | Conway et al. | May 2010 | A1 |
| 20100121803 | Gill | May 2010 | A1 |
| 20100122152 | Chamberlain et al. | May 2010 | A1 |
| 20100125546 | Barrett et al. | May 2010 | A1 |
| 20100131457 | Heimendinger | May 2010 | A1 |
| 20100145909 | Ngo | Jun 2010 | A1 |
| 20100162176 | Dunton | Jun 2010 | A1 |
| 20100169237 | Howard et al. | Jul 2010 | A1 |
| 20100185691 | Irmak 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 |
| 20100204983 | Chung et al. | Aug 2010 | A1 |
| 20100235915 | Memon et al. | Sep 2010 | A1 |
| 20100250412 | Wagner | Sep 2010 | A1 |
| 20100262688 | Hussain et al. | Oct 2010 | A1 |
| 20100280857 | Liu et al. | Nov 2010 | A1 |
| 20100293174 | Bennett et al. | Nov 2010 | A1 |
| 20100306029 | Jolley | Dec 2010 | A1 |
| 20100306285 | Shah et al. | Dec 2010 | A1 |
| 20100306713 | Geisner et al. | Dec 2010 | A1 |
| 20100321399 | Ellren et al. | Dec 2010 | A1 |
| 20100325526 | Ellis et al. | Dec 2010 | A1 |
| 20100325581 | Finkelstein et al. | Dec 2010 | A1 |
| 20100330801 | Rouh | Dec 2010 | A1 |
| 20110010342 | Chen et al. | Jan 2011 | A1 |
| 20110035811 | Rees | Feb 2011 | A1 |
| 20110047159 | Baid et al. | Feb 2011 | A1 |
| 20110060753 | Shaked et al. | Mar 2011 | A1 |
| 20110061013 | Bilicki et al. | Mar 2011 | A1 |
| 20110074811 | Hanson et al. | Mar 2011 | A1 |
| 20110078173 | Seligmann et al. | Mar 2011 | A1 |
| 20110087519 | Fordyce, III et al. | Apr 2011 | A1 |
| 20110093327 | Fordyce, III et al. | Apr 2011 | A1 |
| 20110117878 | Barash et al. | May 2011 | A1 |
| 20110119100 | Ruhl et al. | May 2011 | A1 |
| 20110137766 | Rasmussen et al. | Jun 2011 | A1 |
| 20110153384 | Horne et al. | Jun 2011 | A1 |
| 20110167105 | Ramakrishnan et al. | Jul 2011 | A1 |
| 20110167493 | Song 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 |
| 20110178842 | Rane et al. | Jul 2011 | A1 |
| 20110208724 | Jones et al. | Aug 2011 | A1 |
| 20110218934 | Elser | Sep 2011 | A1 |
| 20110219450 | McDougal et al. | Sep 2011 | A1 |
| 20110225198 | Edwards et al. | Sep 2011 | A1 |
| 20110231223 | Winters | Sep 2011 | A1 |
| 20110238510 | Rowen et al. | Sep 2011 | A1 |
| 20110238553 | Raj et al. | Sep 2011 | A1 |
| 20110238570 | Li et al. | Sep 2011 | A1 |
| 20110246229 | Pacha | Oct 2011 | A1 |
| 20110258216 | Supakkul et al. | Oct 2011 | A1 |
| 20110291851 | Whisenant | Dec 2011 | A1 |
| 20110307382 | Siegel et al. | Dec 2011 | A1 |
| 20110310005 | Chen et al. | Dec 2011 | A1 |
| 20120005159 | Wang et al. | Jan 2012 | A1 |
| 20120016849 | Garrod et al. | Jan 2012 | A1 |
| 20120019559 | Siler et al. | Jan 2012 | A1 |
| 20120022945 | Falkenborg et al. | Jan 2012 | A1 |
| 20120023075 | Pulfer et al. | Jan 2012 | A1 |
| 20120036013 | Neuhaus et al. | Feb 2012 | A1 |
| 20120036106 | Desai et al. | Feb 2012 | A1 |
| 20120036434 | Oberstein | Feb 2012 | A1 |
| 20120064921 | Hernoud | Mar 2012 | A1 |
| 20120066296 | Appleton et al. | Mar 2012 | A1 |
| 20120079363 | Folting et al. | Mar 2012 | A1 |
| 20120084135 | Nissan et al. | Apr 2012 | A1 |
| 20120084866 | Stolfo | Apr 2012 | A1 |
| 20120106801 | Jackson | May 2012 | A1 |
| 20120110633 | An et al. | May 2012 | A1 |
| 20120110674 | Belani et al. | May 2012 | A1 |
| 20120117082 | Koperda et al. | May 2012 | A1 |
| 20120131512 | Takeuchi et al. | May 2012 | A1 |
| 20120144335 | Abeln et al. | Jun 2012 | A1 |
| 20120150446 | Chang | Jun 2012 | A1 |
| 20120159307 | Chung et al. | Jun 2012 | A1 |
| 20120159362 | Brown et al. | Jun 2012 | A1 |
| 20120159399 | Bastide et al. | Jun 2012 | A1 |
| 20120167164 | Burgess | Jun 2012 | A1 |
| 20120173985 | Peppel | Jul 2012 | A1 |
| 20120191446 | Binsztok et al. | Jul 2012 | A1 |
| 20120196557 | Reich et al. | Aug 2012 | A1 |
| 20120196558 | Reich et al. | Aug 2012 | A1 |
| 20120208636 | Feige | Aug 2012 | A1 |
| 20120215898 | Shah et al. | Aug 2012 | A1 |
| 20120221511 | Gibson et al. | Aug 2012 | A1 |
| 20120221553 | Wittmer et al. | Aug 2012 | A1 |
| 20120221580 | Barney | Aug 2012 | A1 |
| 20120245976 | Kumar et al. | Sep 2012 | A1 |
| 20120246148 | Dror | Sep 2012 | A1 |
| 20120254129 | Wheeler et al. | Oct 2012 | A1 |
| 20120266245 | McDougal et al. | Oct 2012 | A1 |
| 20120290879 | Shibuya et al. | Nov 2012 | A1 |
| 20120296907 | Long et al. | Nov 2012 | A1 |
| 20120304150 | Leithead et al. | Nov 2012 | A1 |
| 20120304244 | Xie et al. | Nov 2012 | A1 |
| 20120310831 | Harris et al. | Dec 2012 | A1 |
| 20120310838 | Harris et al. | Dec 2012 | A1 |
| 20120311684 | Paulsen et al. | Dec 2012 | A1 |
| 20120323829 | Stokes 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 |
| 20130006655 | Van Arkel et al. | Jan 2013 | A1 |
| 20130006668 | Van Arkel et al. | Jan 2013 | A1 |
| 20130006725 | Simanek et al. | Jan 2013 | A1 |
| 20130013612 | Fittges | Jan 2013 | A1 |
| 20130018796 | Kolhatkar et al. | Jan 2013 | A1 |
| 20130019306 | Lagar-Cavilla et al. | Jan 2013 | A1 |
| 20130024307 | Fuerstenberg et al. | Jan 2013 | A1 |
| 20130024339 | Choudhuri et al. | Jan 2013 | A1 |
| 20130046842 | Muntz et al. | Feb 2013 | A1 |
| 20130060786 | Serrano et al. | Mar 2013 | A1 |
| 20130061169 | Pearcy et al. | Mar 2013 | A1 |
| 20130067017 | Carriere et al. | Mar 2013 | A1 |
| 20130073377 | Heath | Mar 2013 | A1 |
| 20130078943 | Biage et al. | Mar 2013 | A1 |
| 20130086072 | Peng | Apr 2013 | A1 |
| 20130091084 | Lee | Apr 2013 | A1 |
| 20130097482 | Marantz et al. | Apr 2013 | A1 |
| 20130101159 | Chao et al. | Apr 2013 | A1 |
| 20130111320 | Campbell et al. | May 2013 | A1 |
| 20130117651 | Waldman et al. | May 2013 | A1 |
| 20130124193 | Holmberg | May 2013 | A1 |
| 20130139268 | An et al. | May 2013 | A1 |
| 20130150004 | Rosen | Jun 2013 | A1 |
| 20130151388 | Falkenborg et al. | Jun 2013 | A1 |
| 20130157234 | Gulli et al. | Jun 2013 | A1 |
| 20130160120 | Malaviya et al. | Jun 2013 | A1 |
| 20130166550 | Buchmann et al. | Jun 2013 | A1 |
| 20130173540 | Qian et al. | Jul 2013 | A1 |
| 20130176321 | Mitchell et al. | Jul 2013 | A1 |
| 20130179420 | Park et al. | Jul 2013 | A1 |
| 20130191336 | Ducott et al. | Jul 2013 | A1 |
| 20130191338 | Ducott, III et al. | Jul 2013 | A1 |
| 20130211985 | Clark et al. | Aug 2013 | A1 |
| 20130224696 | Wolfe 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 |
| 20130251233 | Yang et al. | Sep 2013 | A1 |
| 20130262527 | Hunter et al. | Oct 2013 | A1 |
| 20130263019 | Castellanos et al. | Oct 2013 | A1 |
| 20130268520 | Fisher et al. | Oct 2013 | A1 |
| 20130275446 | Jain et al. | Oct 2013 | A1 |
| 20130276799 | Davidson | Oct 2013 | A1 |
| 20130279757 | Kephart | Oct 2013 | A1 |
| 20130282696 | John 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 |
| 20130318594 | Hoy et al. | Nov 2013 | A1 |
| 20130339218 | Subramanian et al. | Dec 2013 | A1 |
| 20130345982 | Liu | Dec 2013 | A1 |
| 20130346444 | Makkar et al. | Dec 2013 | A1 |
| 20130346563 | Huang | Dec 2013 | A1 |
| 20140006109 | Callioni et al. | Jan 2014 | A1 |
| 20140019936 | Cohanoff | Jan 2014 | A1 |
| 20140032506 | Hoey et al. | Jan 2014 | A1 |
| 20140033010 | Richardt et al. | Jan 2014 | A1 |
| 20140040182 | Gilder et al. | Feb 2014 | A1 |
| 20140040371 | Gurevich et al. | Feb 2014 | A1 |
| 20140040714 | Siegel et al. | Feb 2014 | A1 |
| 20140047357 | Alfaro et al. | Feb 2014 | A1 |
| 20140052466 | DeVille et al. | Feb 2014 | A1 |
| 20140058754 | Wild | Feb 2014 | A1 |
| 20140059038 | McPherson et al. | Feb 2014 | A1 |
| 20140059683 | Ashley | Feb 2014 | A1 |
| 20140068487 | Steiger et al. | Mar 2014 | A1 |
| 20140081652 | Klindworth | Mar 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 |
| 20140114972 | Ducott et al. | Apr 2014 | A1 |
| 20140123279 | Bishop et al. | May 2014 | A1 |
| 20140129518 | Ducott et al. | May 2014 | A1 |
| 20140136237 | Anderson et al. | May 2014 | A1 |
| 20140143009 | Brice et al. | May 2014 | A1 |
| 20140149130 | Getchius | May 2014 | A1 |
| 20140149272 | Hirani et al. | May 2014 | A1 |
| 20140149436 | Bahrami et al. | May 2014 | A1 |
| 20140156527 | Grigg et al. | Jun 2014 | A1 |
| 20140157172 | Peery et al. | Jun 2014 | A1 |
| 20140164502 | Khodorenko 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 |
| 20140245210 | Battcher | Aug 2014 | A1 |
| 20140273910 | Ballantyne | Sep 2014 | A1 |
| 20140279824 | Tamayo | Sep 2014 | A1 |
| 20140310282 | Sprague et al. | Oct 2014 | A1 |
| 20140316911 | Gross | Oct 2014 | A1 |
| 20140333651 | Cervelli et al. | Nov 2014 | A1 |
| 20140337772 | Cervelli et al. | Nov 2014 | A1 |
| 20140366132 | Stiansen et al. | Dec 2014 | A1 |
| 20150046791 | Isaacson | Feb 2015 | A1 |
| 20150046844 | Lee et al. | Feb 2015 | A1 |
| 20150046845 | Lee et al. | Feb 2015 | A1 |
| 20150046870 | Goldenberg et al. | Feb 2015 | A1 |
| 20150046876 | Goldenberg | Feb 2015 | A1 |
| 20150074050 | Landau et al. | Mar 2015 | A1 |
| 20150135329 | Aghasaryan et al. | May 2015 | A1 |
| 20150186821 | Wang et al. | Jul 2015 | A1 |
| 20150187036 | Wang et al. | Jul 2015 | A1 |
| 20150212236 | Haas | Jul 2015 | A1 |
| 20150213284 | Birkel | Jul 2015 | A1 |
| 20150230061 | Srivastava | Aug 2015 | A1 |
| 20150235334 | Wang et al. | Aug 2015 | A1 |
| 20150248489 | Solheim | Sep 2015 | A1 |
| 20150311991 | Iwai | Oct 2015 | A1 |
| 20150317285 | Duggal | Nov 2015 | A1 |
| 20150363518 | Edgington | Dec 2015 | A1 |
| 20150379341 | Agrawal | Dec 2015 | A1 |
| 20160065511 | Ganin | Mar 2016 | A1 |
| 20160098493 | Primke | Apr 2016 | A1 |
| 20160112428 | Terleski | Apr 2016 | A1 |
| 20160119424 | Kane | Apr 2016 | A1 |
| 20170098289 | Florance | Apr 2017 | A1 |
| 20170134425 | Albertson et al. | May 2017 | A1 |
| 20180005331 | Wang et al. | Jan 2018 | A1 |
| 20180337952 | Albertson et al. | Nov 2018 | A1 |
| Number | Date | Country |
|---|---|---|
| 101729531 | Jun 2010 | CN |
| 103281301 | Sep 2013 | CN |
| 102014103476 | Sep 2014 | DE |
| 102014103482 | Sep 2014 | DE |
| 0816968 | Jan 1996 | EP |
| 1191463 | Mar 2002 | EP |
| 1672527 | Jun 2006 | EP |
| 2551799 | Jan 2013 | EP |
| 2778914 | Sep 2014 | EP |
| 2778977 | Sep 2014 | EP |
| 2835745 | Feb 2015 | EP |
| 2835770 | Feb 2015 | EP |
| 2911078 | Aug 2015 | EP |
| 2911079 | Aug 2015 | EP |
| 2366498 | Mar 2002 | GB |
| 2514239 | Nov 2014 | GB |
| 2516155 | Jan 2015 | GB |
| WO 2000009529 | Feb 2000 | WO |
| WO 2005104736 | Nov 2005 | WO |
| WO 2008011728 | Jan 2008 | WO |
| WO 2008064207 | May 2008 | WO |
| WO 2008113059 | Sep 2008 | WO |
| WO 2009061501 | May 2009 | WO |
| WO 2010000014 | Jan 2010 | WO |
| WO 2010030913 | Mar 2010 | WO |
| WO 2011071833 | Jun 2011 | WO |
| WO 2011161565 | Dec 2011 | WO |
| WO 2012009397 | Jan 2012 | WO |
| WO 2013126281 | Aug 2013 | WO |
| Entry |
|---|
| US 8,712,906 B1, 04/2014, Sprague et al. (withdrawn) |
| “A First Look: Predicting Market Demand for Food Retail using a Huff Analysis,” TRF Policy Solutions, Jul. 2012, pp. 30. |
| “A Tour of Pinboard,” <http://pinboard.in/tour> as printed May 15, 2014 in 6 pages. |
| “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/. |
| Acklen, Laura, “Absolute Beginner's Guide to Microsoft Word 2003,” Dec. 24, 2003, pp. 15-18, 34-41, 308-316. |
| Alfred, Rayner “Summarizing Relational Data Using Semi-Supervised Genetic Algorithm-Based Clustering Techniques”, Journal of Computer Science, 2010, vol. 6, No. 7, pp. 775-784. |
| 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. |
| Anonymous, “BackTult—JD Edwards One World Version Control System,” printed Jul. 23, 2007 in 1 page. |
| Baker et al., “The Development of a Common Enumeration of Vulnerabilities and Exposures,” Presented at the Second International Workshop on Recent Advances in Intrusion Detection, Sep. 7-9, 1999, pp. 35. |
| Bluttman et al., “Excel Formulas and Functions for Dummies,” 2005, Wiley Publishing, Inc., pp. 280, 284-286. |
| 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. |
| 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. |
| Conner, Nancy, “Google Apps: The Missing Manual,” May 1, 2008, pp. 15. |
| Definition “Identify”, downloaded Jan. 22, 2015, 1 page. |
| Definition “Overlay”, downloaded Jan. 22, 2015, 1 page. |
| Delicious, <http://delicious.com/> as printed May 15, 2014 in 1 page. |
| Dell Latitude D600 2003, Dell Inc., http://www.dell.com/downloads/global/products/latit/en/spec_latit_d600_en.pdf. |
| Dou et al., “Ontology Translation on the Semantic Web 2005,” Springer-Verlag, Journal on Data Semantics II Lecture Notes in Computer Science, vol. 3350, pp. 35-37. |
| 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. |
| “The FASTA Program Package,” fasta-36.3.4, Mar. 25, 2011, pp. 29. |
| Fidge, Colin J., “Timestamps in Message-Passing Systems,” K. Raymond (Ed.) Proc. of the 11th Australian Computer Science Conference (ACSC 1988), pp. 56-66. |
| Geiger, Jonathan G., “Data Quality Management, The Most Critical Initiative You Can Implement”, Data Warehousing, Management and Quality, Paper 098-29, SUGI 29, Intelligent Solutions, Inc., Bounder, CO, pp. 14, accessed Oct. 3, 2013. |
| 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. |
| 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. |
| 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. |
| Hibbert et al., “Prediction of Shopping Behavior Using a Huff Model Within a GIS Framework,” Healthy Eating in Context, Mar. 18, 2011, pp. 16. |
| Holliday, JoAnne, “Replicated Database Recovery using Multicast Communication,” IEEE 2002, pp. 11. |
| 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. |
| 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-datasheetpdf> 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. |
| Klemmer et al., “Where Do Web Sites Come From? Capturing and Interacting with Design History,” Association for Computing Machinery, CHI 2002, Apr. 20-25, 2002, Minneapolis, MN, pp. 8. |
| Kokossi et al., “D7-Dynamic Ontoloty Management System (Design),” Information Societies Technology Programme, Jan. 10, 2002, pp. 1-27. |
| Lamport, “Time, Clocks and the Ordering of Events in a Distributed System,” Communications of the ACM, Jul. 1978, vol. 21, No. 7, pp. 558-565. |
| Lee et al., “A Data Mining and CIDF Based Approach for Detecting Novel and Distributed Intrusions,” Lecture Notes in Computer Science, vol. 1907 Nov. 11, 2000, pp. 49-65. |
| 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. |
| Loeliger, Jon, “Version Control with Git,” O'Reilly, May 2009, pp. 330. |
| 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 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. |
| Mattern, F., “Virtual Time and Global States of Distributed Systems,” Cosnard, M., Proc. Workshop on Parallel and Distributed Algorithms, Chateau de Bonas, France:Elsevier, 1989, pp. 215-226. |
| 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. |
| Miklau et al., “Securing History: Privacy and Accountability in Database Systems,” 3rd Biennial Conference on Innovative Data Systems Research (CIDR), Jan. 7-10, 2007, Asilomar, California, pp. 387-396. |
| Morrison et al., “Converting Users to Testers: An Alternative Approach to Load Test Script Creation, Parameterization and Data Corellation,” CCSC: Southeastern Conference, JCSC 28, Dec. 2, 2012, pp. 188-196. |
| Niepert et al., “A Dynamic Ontology for a Dynamic Reference Work”, Joint Conference on Digital Libraries, Jun. 17-22, 2007, Vancouver, British Columbia, Canada, pp. 1-10. |
| Nivas, Tuli, “Test Harness and Script Design Principles for Automated Testing of non-GUI or Web Based Applications,” Performance Lab, Jun. 2011, pp. 30-37. |
| 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, pp. 1-6, 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/. |
| O'Sullivan, Bryan, “Making Sense of Revision Control Systems,” Communications of the ACM, Sep. 2009, vol. 52, No. 9, pp. 57-62. |
| OWL Web Ontology Language Reference Feb. 2004, W3C, http://www.w3.org/TR/owl-ref/. |
| Palantir, “Extracting and Transforming Data with Kite,” Palantir Technologies, Inc., Copyright 2010, pp. 38. |
| Palantir, “Kite Data-Integration Process Overview,” Palantir Technologies, Inc., Copyright 2010, pp. 48. |
| Palantir, “Kite Operations,” Palantir Technologies, Inc., Copyright 2010, p. 1. |
| Palantir, “Kite,” https://docs.palantir.com/gotham/3.11.1.0/adminreference/datasources.11 printed Aug. 30, 2013 in 2 pages. |
| Palantir, “The Repository Element,” https://docs.palantir.com/gotham/3.11.1.0/dataguide/kite_config_file.04 printed Aug. 30, 2013 in 2 pages. |
| Palantir, “Write a Kite Configuration File in Eclipse,” Palantir Technologies, Inc., Copyright 2010, pp. 2. |
| Palantir, “Kite Schema,” https://docs.palantir.com/gotham/3.11.1.0/dataguide/baggage/KiteSchema.xsd printed Apr. 4, 2014 in 4 pages. |
| Palermo, Christopher J., “Memorandum,” [Disclosure relating to U.S. Appl. No. 13/916,447, filed Jun. 12, 2013, and related applications], Jan. 31, 2014 in 3 pages. |
| Palmas et al. “An Edge-Bunding Layout for Interactive Parallel Coordinates” 2014 IEEE Pacific Visualization Symposium, pp. 57-64. |
| Parker, Jr. et al., “Detection of Mutual Inconsistency in Distributed Systems,” IEEE Transactions in Software Engineering, May 1983, vol. SE-9, No. 3, pp. 241-247. |
| “Potential Money Laundering Warning Signs,” snapshot taken 2003, https://web.archive.org/web/20030816090055/http:/finsolinc.com/ANTI-MONEY%20LAUNDERING%20TRAINING%20GUIDES.pdf. |
| Rouse, Margaret, “OLAP Cube,” <http://searchdatamanagement.techtarget.com/definition/OLAP-cube>, Apr. 28, 2012, pp. 16. |
| Shah, Chintan, “Periodic Connections to Control Server Offer New Way to Detect Botnets,” Oct. 24, 2013 in 6 pages, <http://www.blogs.mcafee.com/mcafee-labs/periodic-links-to-control-server-offer-new-way-to-detect-botnets>. |
| Symantec Corporation, “E-Security Begins with Sound Security Policies,” Announcement Symantec, Jun. 14, 2001. |
| Wiggerts, T.A., “Using Clustering Algorithms in Legacy Systems Remodularization,” Reverse Engineering, Proceedings of the Fourth Working Conference, Netherlands, Oct. 6-8, 1997, IEEE Computer Soc., pp. 33-43. |
| Wollrath et al., “A Distributed Object Model for the Java System,” Conference on Object-Oriented Technologies and Systems, Jun. 17-21, 1996, pp. 219-231. |
| Notice of Allowance for U.S. Appl. No. 13/657,684 dated Mar. 2, 2015. |
| Notice of Allowance for U.S. Appl. No. 14/139,628 dated Jun. 24, 2015. |
| Notice of Allowance for U.S. Appl. No. 14/139,640 dated Jun. 17, 2015. |
| Notice of Allowance for U.S. Appl. No. 14/139,713 dated Jun. 12, 2015. |
| Notice of Allowance for U.S. Appl. No. 14/264,445 dated May 14, 2015. |
| Notice of Allowance for U.S. Appl. No. 14/286,485 dated Jul. 29, 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. 14/486,991 dated May 1, 2015. |
| Notice of Allowance for U.S. Appl. No. 14/616,080 dated Apr. 2, 2015. |
| Notice of Allowance for U.S. Appl. No. 14/684,231 dated Jul. 17, 2017. |
| Official Communication for European Patent Application No. 14158861.6 dated Jun. 16, 2014. |
| Official Communication for European Patent Application No. 14158977.0 dated Jun. 10, 2014. |
| Official Communication for European Patent Application No. 14159464.8 dated Jul. 31, 2014. |
| Official Communication for European Patent Application No. 14159535.5 dated May 22, 2014. |
| Official Communication for European Patent Application No. 14180281.9 dated Jan. 26, 2015. |
| Official Communication for European Patent Application No. 14187996.5 dated Feb. 12, 2015. |
| Official Communication for European Patent Application No. 15155845.9 dated Oct. 6, 2015. |
| Official Communication for European Patent Application No. 15156004.2 dated Aug. 24, 2015. |
| Official Communication for Great Britain Patent Application No. 1404457.2 dated Aug. 14, 2014. |
| Official Communication for Great Britain Patent Application No. 1404573.6 dated Sep. 10, 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 New Zealand Patent Application No. 622389 dated Mar. 20, 2014. |
| Official Communication for New Zealand Patent Application No. 622404 dated Mar. 20, 2014. |
| Official Communication for New Zealand Patent Application No. 622484 dated Apr. 2, 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. 13/657,684 dated Aug. 28, 2014. |
| Official Communication for U.S. Appl. No. 13/949,043 dated May 7, 2015. |
| Official Communication for U.S. Appl. No. 14/076,385 dated Jun. 2, 2015. |
| Official Communication for U.S. Appl. No. 14/076,385 dated Jan. 22, 2015. |
| Official Communication for U.S. Appl. No. 14/156,208 dated Aug. 11, 2015. |
| Official Communication for U.S. Appl. No. 14/156,208 dated Mar. 9, 2015. |
| Official Communication for U.S. Appl. No. 14/170,562 dated Jul. 17, 2015. |
| Official Communication for U.S. Appl. No. 14/170,562 dated Sep. 25, 2014. |
| Official Communication for U.S. Appl. No. 14/264,445 dated Apr. 17, 2015. |
| Official Communication for U.S. Appl. No. 14/278,963 dated Jan. 30, 2015. |
| Official Communication for U.S. Appl. No. 14/280,490 dated Jul. 24, 2014. |
| Official Communication for U.S. Appl. No. 14/286,485 dated Mar. 12, 2015. |
| Official Communication for U.S. Appl. No. 14/286,485 dated Apr. 30, 2015. |
| 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. 14/289,599 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. 14/334,232 dated Jul. 10, 2015. |
| Official Communication for U.S. Appl. No. 14/449,083 dated Mar. 12, 2015. |
| Official Communication for U.S. Appl. No. 14/449,083 dated Oct. 2, 2014. |
| Official Communication for U.S. Appl. No. 14/473,552 dated Feb. 24, 2015. |
| Official Communication for U.S. Appl. No. 14/486,991 dated Mar. 10, 2015. |
| Official Communication for U.S. Appl. No. 14/518,757 dated Dec. 1, 2015. |
| Official Communication for U.S. Appl. No. 14/518,757 dated Dec. 10, 2014. |
| Official Communication for U.S. Appl. No. 14/518,757 dated Sep. 19, 2016. |
| Official Communication for U.S. Appl. No. 14/518,757 dated Apr. 2, 2015. |
| Official Communication for U.S. Appl. No. 14/518,757 dated Jul. 20, 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. 14/639,606 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. 14/684,231 dated Jan. 23, 2017. |
| Official Communication for U.S. Appl. No. 14/684,231 dated Oct. 31, 2016. |
| Crosby et al., “Efficient Data Structures for Tamper-Evident Logging,” Department of Computer Science, Rice University, 2009, pp. 17. |
| Notice of Allowance for U.S. Appl. No. 14/684,231 dated Nov. 17, 2017. |
| Official Communication for New Zealand Patent Application No. 622181 dated Mar. 24, 2014. |
| Official Communication for New Zealand Patent Application No. 628150 dated Aug. 15, 2014. |
| Official Communication for European Patent Application No. 15155845.9 dated Nov. 9, 2018. |
| Official Communication for European Patent Application No. 15156004.2 dated Nov. 16, 2018. |
| Number | Date | Country | |
|---|---|---|---|
| 62020616 | Jul 2014 | US |
