Patent Application
20110050702
A recent development in electronics industry and use of electronic devices by consumers is the proliferation of handheld computing devices with wireless communication capabilities. Smaller and relatively low-powered transceivers are integrated into a wide variety of devices to enable the automatic exchange of information, and to simplify many processes such as user authentication, contact information exchange between mobile devices, and other similar scenarios.
With the increasing computing power of these smaller devices, a number of applications, typically executed in desktop computing devices, are now available to users in a portable mode. An example group of such applications include those providing charting functionality such as spreadsheet applications. Professions such as sales people can download up-to-date data into their handheld (or vehicle-mount) device, analyze, and view various charts based on the analysis.
One inherent shortcoming of portable computing devices is the relatively small size of their displays. For example, visual media is available to many portable devices such as smart phones. However, the small display size prevents widespread use of video streaming. The experience of watching a movie on a large screen is after all not the same as watching the same on a 2.5 inch by 2.5 inch phone display. Similarly, charts tend to lose their granularity and detail when displayed on a small portable device screen. When translated into a small device display, charts are either visible in segments or scaled down. Segmented charts are difficult to view, while data may lose its meaning in scaled down charts. Thus, user experience is degraded in either case.
This summary is provided to introduce a selection of concepts in a simplified form that are further described below in the Detailed Description. This summary is not intended to exclusively identify key features or essential features of the claimed subject matter, nor is it intended as an aid in determining the scope of the claimed subject matter.
Embodiments are directed to providing automatic scaling of charts based on contributing data members. A relatable context of scale is provided by presenting a select group of lowest data members as a combined group such as a combination bar in a bar chart, a histogram, and comparable forms. According to some embodiments, the automatic chart scaling (e.g. condensing) may be provided in response to user actions on an interactive display.
These and other features and advantages will be apparent from a reading of the following detailed description and a review of the associated drawings. It is to be understood that both the foregoing general description and the following detailed description are explanatory and do not restrict aspects as claimed.
As briefly described above, a user's experience in viewing a chart on a smaller display may be enhanced by automatically scaling the chart based on its contributing data members. In the following detailed description, references are made to the accompanying drawings that form a part hereof, and in which are shown by way of illustrations specific embodiments or examples. These aspects may be combined, other aspects may be utilized, and structural changes may be made without departing from the spirit or scope of the present disclosure. The following detailed description is therefore not to be taken in a limiting sense, and the scope of the present invention is defined by the appended claims and their equivalents.
While the embodiments will be described in the general context of program modules that execute in conjunction with an application program that runs on an operating system on a personal computer, those skilled in the art will recognize that aspects may also be implemented in combination with other program modules.
Generally, program modules include routines, programs, components, data structures, and other types of structures that perform particular tasks or implement particular abstract data types. Moreover, those skilled in the art will appreciate that embodiments may be practiced with other computer system configurations, including hand-held devices, multiprocessor systems, microprocessor-based or programmable consumer electronics, minicomputers, mainframe computers, and comparable computing devices. Embodiments may also be practiced in distributed computing environments where tasks are performed by remote processing devices that are linked through a communications network. In a distributed computing environment, program modules may be located in both local and remote memory storage devices.
Embodiments may be implemented as a computer-implemented process (method), a computing system, or as an article of manufacture, such as a computer program product or computer readable media. The computer program product may be a computer storage medium readable by a computer system and encoding a computer program that comprises instructions for causing a computer or computing system to perform example process(es). The computer-readable storage medium can for example be implemented via one or more of a volatile computer memory, a non-volatile memory, a hard drive, a flash drive, a floppy disk, or a compact disk, and comparable media. The computer program product may also be a propagated signal on a carrier (e.g. a frequency or phase modulated signal) or medium readable by a computing system and encoding a computer program of instructions for executing a computer process.
Throughout this specification, the term “platform” may be a combination of software and hardware components for providing chart applications. Examples of platforms include, but are not limited to, a hosted service executed over a plurality of servers, an application executed on a single server, and comparable systems. The term “server” refers to a computing device executing one or more software programs typically in a networked environment. The term “client” refers to a computing device or software application that provides a user access to data and other software applications through a network connection with other clients and/or servers. More detail on these technologies and example operations is provided below.
Some charts, like the example bar chart 104, may include a number of significant elements and a number of smaller, less significant elements. For example, data elements 106 may have higher values compared to data elements 108. Using a relatively large computer display, all of the data elements in the chart may be displayed without degrading visibility and detail of the chart.
Display 222 in diagram 220 may be a mobile computing device screen or similar display with controls 228. When charts are scaled down to fit small screen resolutions or constrained to a smaller region such as on a dashboard page, visibility and detail of data is degraded. While higher value (vertical axis) data elements such as data elements 206 are can still be distinguished along the vertical axis 224, it is relatively difficult to distinguish the smaller data elements (208). Thus, the overall value of the chart is degraded due to scaling, when the whole chart is scaled uniformly.
In contrast to the chart 204 of diagram 220, chart 232 of diagram 230 illustrates a bar chart with relatively small number of data elements 238. Thus, the data elements are clearly visible and a user can easily distinguish vertical axis (234) values of the data elements. Furthermore, the data elements 238 are also spread out along the horizontal axis 236 further enabling the user to view the elements with ease.
As show in the diagram, a number of states have relatively higher expenditures (306), while a group of states have smaller expenditures (308). Due to the large number of data elements (states) differences between the expenditures of the states with smaller expenditures (308) is practically invisible in the chart, even though the chart is shown in a large scale. When the same chart is scaled to fit into a smaller display, not only would the states with smaller expenditures (308) become indistinguishable, but those data elements would push the first group of data elements (states with higher expenditures 306) together causing a degradation of visibility for those elements as well. Thus, whole chart scaling is not a practical solution for a diagram like the example chart shown in this figure.
As shown in diagram 400 according one embodiment, data elements 442 to be shown individually in the automatically scaled chart are determined based on displayable length of the horizontal axis 426, resolution of the screen, user preferences, or similar factors. Then, a bucket element 446 is created representing the bottom “n” data elements that are to be removed from the horizontal axis. The bucket element represents the combined contribution of the bottom “n” elements. According to another embodiment, further information about the bottom “n” elements may be presented as a histogram 448 next to the bucket element or employing a comparable method in a condensed form.
Right vertical axis 444 may be automatically rescaled such that bucket element 446 can be displayed more visibly (thus, bucket element 446 is according to the scale of the right vertical axis 444 and not according to the left vertical axis 424). Histogram 448 may be displayed according to the left vertical axis 424 or right vertical axis 444. Furthermore, the portion (450) of the horizontal axis 426 corresponding to the histogram may also be resealed to reflect the condensed form of the histogram (or similar representation). Instead of the histogram, a line curve, condensed bars, or similar graphic elements may also be used to represent the bottom “n” elements. Thus, the automatically scaled chart is somewhat similar to two separate charts appended together, but reflecting the same set of data elements.
As mentioned previously, embodiments are not limited to bar charts. Three dimensional column charts (vertical columns), horizontal bar charts, pie charts, donut charts, line graphs, scatter graphs (dots), area charts, surface charts, radar charts (using polar coordinates), and similar ones may also be automatically scaled using the principles described herein.
A general method of automatically scaling charts according to embodiments may begin with determining data elements to be displayed on the chart and ranking them according to their values. Top elements to be displayed individually in the scaled chart may then be determined and a bucket element created combining the remaining data elements. Upon determining the display format of the bucket element, a right vertical axis may be scaled and the bucket element displayed according to the right vertical axis. A condensed representation of the remaining data elements such as a histogram may also be added based on predefined scaling factors such as the left vertical axis (primary value axis) scale, the right vertical axis (secondary value axis) scale, etc. The condensed representation of the remaining elements may be adjacent to the bucket element, overlapping with the bucket element, or separate from the bucket element.
The portion of the horizontal axis corresponding to the histogram may be resealed based on a number of the remaining elements or a size of the horizontal axis. Furthermore, the data elements may be ranked largest to smallest or smallest to largest based on a user preference.
According to an example embodiment, a specific algorithm for automatically scaling charts may include following steps:
n=(w/e)−1
According to a further embodiment, various aspects of the automatic scaling of a chart may be performed or adjusted based on user actions such as input through an interactive display. Interactive displays are commonly used in smaller computing devices such as portable computers, smart phones, automobile computers, etc. A user may provide input by tapping on a displayed graphic element or dragging a graphic element to a position. Thus, information on scaling of the secondary value axis (right vertical axis), display position of the histogram, which data elements to include in the bucket element, display position of the bucket element, and other aspects of the chart may be adjusted based on user input through the interactive display. Of course, similar input may be provided by the user through the use of an input device such as a mouse, a touch pen, a keyboard entry, and the like.
According to yet another embodiment, a preview of the automatically scaled chart may be presented to the user based on predefined parameters such as display size, number of data elements, etc. Changes may be made, thereafter, based on user input while adjusting other aspects of the chart automatically based on the user input. For example, the user may move the placement of the histogram in the chart. The scaling of the histogram and the bucket element may be adjusted automatically based on this change to preserve the overall integrity of the chart.
As mentioned above, charts may be automatically scaled based on user interaction with an interactive display device. One example of such an implementation is a computing device like Microsoft Surface® computer by Microsoft Corporation of Redmond, Wash. On this or a similar device, where users may arrange and scale different visualizations of charts—among other things—on a touchable canvas, the user may make gestures to enlarge or shrink a chart area. A chart scaling algorithm according to embodiments may be executed by the processor of the computing device continuously recalculating scaling parameters and adjusting data element representations as discussed previously.
Thus, the number of data elements to be displayed individually may be reduced depending on the above mentioned factors or user indication such as through an interactive device display. Diagram 500 includes top four elements 542 displayed across axes 524 and 526. Bucket element 546 is displayed along with histogram 548 representing bucket elements in a condensed fashion. The portion of the horizontal axis 550 corresponding to the histogram, as well as the vertical axis 544 corresponding to the bucket element and the histogram, is automatically scaled to match the change in the bucket element and the histogram. The bucket element has a larger value compared to the chart in
Thus, first data element 642 is displayed across axes 624 and 626. Then, bucket element 646 and the histogram 648 are displayed across horizontal axis portion 650 and vertical scaled axis 644.
In addition, placement of the graphical elements representing the combined data elements may also be varied for enhanced user experience. In the example chart of diagram 700, first data element 642 is displayed across axes 624 and 626. Histogram 748 is displayed next to the first data element across axis 624 and portion of horizontal axis 650. Bucket element 646 is displayed behind the histogram. Scaled axis 644 corresponds to the bucket element.
Diagram 800 illustrates an example pie chart 860, where top n elements to be displayed individually (862) are shown in various shades of gray. Bucket element 864, which includes the combination of the remaining elements, is shown in dark grey. Other variations of automatic scaling in pie charts may include adjustment of the radius of the bucket element, use of a gradient color scheme.
While the example charts in
As discussed previously, client devices 911-915 are capable of communicating through a variety of modes between subscribers of a communication service. A chart-capable application executed in one of the client devices or by one of the servers 922 may retrieve data from a number of sources such as data store 926, which may be managed by any one of the servers 922 or by database server 924. The chart may then be scaled based on the client device's display capabilities, user parameters, and similar factors by the application and displayed to the user. The chart may also be dynamically rescaled based on user interaction with the display.
Network(s) 910 may comprise any topology of servers, clients, Internet service providers, and communication media. A system according to embodiments may have a static or dynamic topology. Network(s) 910 may include a secure network such as an enterprise network, an unsecure network such as a wireless open network, or the Internet. Network(s) 910 may also comprise a plurality of distinct networks. Network(s) 910 provides communication between the nodes described herein. By way of example, and not limitation, network(s) 910 may include wireless media such as acoustic, RF, infrared and other wireless media.
Many other configurations of computing devices, applications, data sources, and data distribution systems may be employed to implement a system for automatically scaling charts based on contributing data members. Furthermore, the networked environments discussed in
Application 1022 and charting module 1024 may be separate applications or integral modules of a hosted service that provides computing services to client applications/devices. Application 1022 may provide data organization, analysis, and similar functions (e.g. a spreadsheet application) and provide charts of the organized/analyzed data. Charting module 1024 may, among other things, scale the chart(s) automatically based on contributing data members as discussed in more detail above. Charting module 1024 may further scale chart(s) dynamically in response to user interaction with an interactive display as one of the input devices 1012. This basic configuration is illustrated in
Computer 1000 may have additional features or functionality. For example, the computer 1000 may also include additional data storage devices (removable and/or non-removable) such as, for example, magnetic disks, optical disks, or tape. Such additional storage is illustrated in
Computer 1000 may also contain communication connections 1016 that allow the device to communicate with other devices 1018, such as over a wireless network in a distributed computing environment, a satellite link, a cellular link, and comparable mechanisms. Other devices 1018 may include computer device(s) that execute communication applications, provide data for application 1022, and so on. Communication connection(s) 1016 is one example of communication media. Communication media can include therein computer readable instructions, data structures, program modules, or other data in a modulated data signal, such as a carrier wave or other transport mechanism, and includes any information delivery media. The term “modulated data signal” means a signal that has one or more of its characteristics set or changed in such a manner as to encode information in the signal. By way of example, and not limitation, communication media includes wired media such as a wired network or direct-wired connection, and wireless media such as acoustic, RF, infrared and other wireless media.
Example embodiments also include methods. These methods can be implemented in any number of ways, including the structures described in this document. One such way is by machine operations, of devices of the type described in this document.
Another optional way is for one or more of the individual operations of the methods to be performed in conjunction with one or more human operators performing some. These human operators need not be collocated with each other, but each can be only with a machine that performs a portion of the program.
Process 1100 begins with operation 1110, where data elements to be included in a chart are determined. The data elements may be provided by any application such as a spreadsheet application, an analysis application, a data reporting application, and comparable ones. The data elements may be derived from results of an analysis, from raw data, from user input, and similar sources.
At operation 1120, the data elements to be included in the chart are ranked. The ranking depends on the significance of data such as y-value in a Cartesian coordinate based chart. Other ranking criteria may also be applied. At subsequent operation 1130, top n elements to be displayed individually are determined. This determination may be made automatically based on display capabilities of a device executing the chart application, user preferences, predefined parameters, and similar factors. As discussed previously, top n elements does not limit the chart to one displaying data elements as distinct graphic elements (e.g. a bar chart). A continuous graphic chart such as a line chart or a 3-dimensional surface chart may also be scaled automatically according to embodiments. An example list of charts that may be adjusted automatically has been listed previously.
At operation 1140, a bucket is computed combining data elements not included in the top n. A sum of these remaining data elements determines the value of a bucket element that may be displayed as explained below. At operation 1150, a display format of the data elements in the bucket is determined. The display format may include a single data element representing the bucket value, a histogram representing the remaining data elements in a condensed fashion, a combination of the bucket element and the histogram, or similar formats.
At operation 1160, the axes associated with the bucket (and/or histogram) are scaled automatically to ensure these graphic elements can be displayed without reducing display quality of the top n data elements. Examples of such scaling have been discussed in conjunction with
The operations included in process 1100 are for illustration purposes. Providing automatically scaled charts based on contributing data members may be implemented by similar processes with fewer or additional steps, as well as in different order of operations using the principles described herein.
The above specification, examples and data provide a complete description of the manufacture and use of the composition of the embodiments. Although the subject matter has been described in language specific to structural features and/or methodological acts, it is to be understood that the subject matter defined in the appended claims is not necessarily limited to the specific features or acts described above. Rather, the specific features and acts described above are disclosed as example forms of implementing the claims and embodiments.
