Device, Method and User Interface for Switching between Graphical Representations of Data
A device with one or more processors and memory displays a first representation of a first subset of data from a data set. The first subset of data is associated with a first time period with more than a threshold number of discrete time steps. The first representation shows changes in the first subset of data over time. The device receives a request to view data associated with a second time period with no more than the threshold number of discrete time steps. In response, the device displays a second representation of a second subset of data from the data set. The second subset of data is associated with the second time period. The second representation aggregates the second subset of data over the second time period and shows divisions of the data in a respective set of one or more data-set dimensions.
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This application claims priority to U.S. Provisional Patent Application No. 61/734,927, filed Dec. 7, 2012, entitled “Systems and Methods for Presenting Analytic Data” which is incorporated herein by reference in its entirety.
This application is related to the following applications: U.S. patent application Ser. No. ______, “Device, Method and User Interface for Presenting Analytic Data,” filed ______, (Attorney Docket No. 070407-5001US); U.S. patent application Ser. No. ______, “Device, Method and User Interface for Determining a Correlation between a Received Sequence of Numbers and Data that Corresponds to Metrics,” filed ______, (Attorney Docket No. 070407-5009US); U.S. patent application Ser. No. ______, “Device, Method and User Interface for Displaying Relationships between Different Sets of Data,” filed ______, (Attorney Docket No. 070407-5010US); and U.S. patent application Ser. No. ______, “Device, Method and User Interface for Emphasizing Divisions in Data,” filed ______, (Attorney Docket No. 070407-5012US), which are incorporated by reference herein in their entirety.
TECHNICAL FIELDThe disclosed implementations relate generally to methods of data visualization.
BACKGROUNDAn online community is a website designed for users to interact with each other, usually with some common theme. Unlike a traditional website, in which the website owner controls all of the content, an online community enables and encourages users to participate in the content. Users post comments, replies to comments, questions, and answers to other users' questions; more experienced users develop articles and knowledge bases, and lead forum discussions or blogs.
Business entities now recognize the value of having an online community for the business. In this case, the community focus is on the products or services of the business, and users participate in the community just like any other online community. While online communities can be beneficial for marketing, online communities are not just a marketing gimmick. For example, real users post real questions, and the questions are frequently answered by other users in the community. Of course an online community is much more than just a question and answer board.
SUMMARYIt is import to measure the success and “health” of an online community. To make these measurements, an abundance of data is tracked about user interactions with the community. Every interaction is tracked, as well as information about the interaction, such as where it originated, what time, what type of computing device the user was using, the content of the interaction itself (such as a post), as well as subsequent responses to the interaction, such as other users designating the comment or answer as useful. This abundance of data is almost too much, and previous methods of reviewing the data have been cumbersome or ineffective. Because of the shortcoming of previous attempts, implementations of the present invention provide simpler and more effective ways of reviewing interaction data for an online community.
In some implementations, a method includes, at a computing device with a display, displaying, in a data display panel, a first representation of a first subset of data from a data set. Respective data items in the data set are associated with corresponding discrete time steps of a plurality of time steps. The first subset of data includes data associated with a first time period that includes more than a threshold number of discrete time steps. The first representation is a first type of data visualization that shows changes in the first subset of data over time. The method further includes receiving a first input corresponding to a request to view data associated with a second time period that includes no more than the threshold number of discrete time steps, and, in response to receiving the first input, displaying, in the data display panel, a second representation of a second subset of data from the data set. The second subset of data includes data associated with the second time period. The second representation is a second type of data visualization that aggregates the second subset of data over the second time period and shows divisions of the data in a respective set of one or more data-set dimensions. The second type of data visualization is different from the first type of data visualization.
In accordance with some embodiments, a computer system (e.g., a search client system or search server system) includes one or more processors, memory, and one or more programs; the one or more programs are stored in the memory and configured to be executed by the one or more processors and the one or more programs include instructions for performing the operations of the method described above. In accordance with some embodiments, a non-transitory computer readable storage medium has stored therein instructions which when executed by one or more processors, cause a computer system (e.g., a search client system or search server system) to perform the operations of the methods described above.
Like reference numerals refer to corresponding parts throughout the several views of the drawings.
DESCRIPTION OF IMPLEMENTATIONSReference will now be made in detail to implementations, examples of which are illustrated in the accompanying drawings. In the following detailed description, numerous specific details are set forth in order to provide a thorough understanding of the present invention. However, it will be apparent to one of ordinary skill in the art that the present invention may be practiced without these specific details. In other instances, well-known methods, procedures, components, and circuits have not been described in detail so as not to unnecessarily obscure aspects of the implementations.
Also connected to the communication network 112 is an online community 100 for a business entity. An online community 100 provides public forums, bulletin boards, blogs, and other information. Unlike a traditional business website, an online community is maintained by everyone, including the users 102. Users 102, for example, can post questions about products or services provided by the business entity, or can post answers to other users questions. An online community can increase profitability of the business entity in many ways, including reducing the costs for customer support (users find the information in the community) and reducing the cost of search engine optimization (for example, because search engines review the user generated community content).
An online community 100 includes one or more web servers 114 that handle the incoming web requests, and one or more application server 116 that provide the user interface functionality for the community. The online community 100 also includes one or more database servers 118 that store the data for the community, including logs of user interactions. In some implementations, the database servers 118 also store binary files, image files, video files, and so on. In some implementations, binary, image, and video files are stored on the application servers 116, of other file servers (not shown).
In addition to the users 102 who interact directly with the online community 100, managers, stakeholders, and executives 108 of the business entity review the community interaction data. As described in more detail below, some people (e.g., managers, stakeholders and/or executives) 108 review the raw data, and other people 108 review analytic computed data. The people 108 utilize client devices 110 to access the interaction data over the communication network 112. Like a user device, a client devices can be desktop computers, laptop computers, tablet computers, smartphones, PDA's, etc.
Although
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- an operating system 216 (e.g., Windows, Mac OS X, iOS, Android, or Linux) that generally includes procedures for handling various basic system services and for performing hardware dependent tasks;
- a network communications module 218 that is used for connecting the client device 110 to servers or other computing devices via one or more communication networks, such as the Internet, other wide area networks, local area networks, metropolitan area networks, and the like;
- a web browser 220 (e.g., Internet Explorer, Safari, Chrome) that is used to access web pages, web applications, and other resources over a communication network, such as the Internet, other wide area networks, local area networks, metropolitan area networks, and the like;
- a metric explorer interface 5000, enabling a user to graphically view data from user interaction with an online community or other social media, and to select many different aspects (or dimensions) of what data is viewed, and how the data is viewed. The metric explorer interface is described in more detail with reference to
FIGS. 5A-5X below and FIGS. 9-005 to 9-141 of U.S. Provisional Patent Application No. 61/734,927, filed Dec. 7, 2012, entitled “Systems and Methods for Presenting Analytic Data”; - an actionable analytics interface 222, enabling a user to graphically review calculated analytic data based on users' interactions with an online community or other social media. The actionable analytics interface 222 is described in more detail with reference to FIGS. 9-142 to 9-206 of U.S. Provisional Patent Application No. 61/734,927, filed Dec. 7, 2012, entitled “Systems and Methods for Presenting Analytic Data”;
- a return on investment (ROI) calculation interface 224, enabling a user to compute the return on investment for an online community 100, or compute correlations between business key performance indicators (KPIs) and various metrics. The ROI calculation interface 224 is described in greater detail with reference to FIGS. 9-207 to 9-236 of U.S. Provisional Patent Application No. 61/734,927, filed Dec. 7, 2012, entitled “Systems and Methods for Presenting Analytic Data”; and
- one or more browser cookies 226, which save state or other information for a web page or web application.
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- an operating system 316 (e.g., Linux or Unix) that generally includes procedures for handling various basic system services and for performing hardware dependent tasks;
- a network communications module 318 that is used for connecting the server 114/116/118 to other servers or other computing devices via one or more communication networks, such as the Internet, other wide area networks, local area networks, metropolitan area networks, and the like;
- web server software 320 (e.g. Apache web server or Apache Tomcat) that receives web requests, and delivers appropriate web pages or other resources in response to the requests;
- database server software 322 (e.g., MySQL or other structured query language (SQL) database engine), which stores organized relational data for the online community 100, and provides the data as needed;
- a database 324 that contains one or more community interaction logs. The log database(s) track information about user interactions with the online community. For example, clicking to view a web page generates a “page view” event, which is logged. The log record for this event optionally includes the user name or ID, the time of the page view, which page was viewed, etc.;
- a forum database 326, which includes data for one or more community forums. This includes all data and metadata for posts to each forum, as well as configuration information about each forum;
- a blog database 328, which stores blogs for one or more individuals, including all of the content of the blog, as well as comments, etc.;
- a tribal knowledge base database 330, which is an organized collection of articles that have generally proceeded through a review process, providing useful information on a topic (e.g., how to utilize a feature of a product provided by the business entity);
- an application server 332, which provides the functionality of the online community 100 and functionality to access the interaction data 324 generated by users 102 of the online community 100;
- one or more community interaction applications or interfaces 334, which are used by users 102 who participate in the online community 100;
- a metric explorer interface 5000, which is used by users (e.g., Managers) to review the raw interaction data. This is described in more detail with reference to
FIGS. 5A-5X below and FIGS. 9-005 to 9-141 of U.S. Provisional Patent Application No. 61/734,927, filed Dec. 7, 2012, entitled “Systems and Methods for Presenting Analytic Data”; - an actionable analytics interface 222, which is used by users (e.g., Stakeholders) to review computed analytic data based on the interactions of users 102 with the online community 100. The actionable analytics interface 222 is described in more detail with reference to FIGS. 9-142 to 9-206 of U.S. Provisional Patent Application No. 61/734,927, filed Dec. 7, 2012, entitled “Systems and Methods for Presenting Analytic Data”;
- a KPI/ROI calculation interface 224, which is used by users (e.g., Executives) to evaluate the return on investment for an online community. In some implementations, the interface 224 computes correlations between business key performance indicators and community metrics. This is described in greater detail with reference to FIGS. 9-207 to 9-236 of U.S. Provisional Patent Application No. 61/734,927, filed Dec. 7, 2012, entitled “Systems and Methods for Presenting Analytic Data”;
- a KPI calculation engine 336, which computes correlation coefficients between sets of data;
- a data export application 338, which converts retrieved data into various external file formats, including CSV (comma separated values), PDF (portable document format), PNG (portable network graphics), and XLS (Microsoft Excel).
Although
Each of the methods described herein are, optionally, performed by instructions that are stored in a computer readable storage medium and that are executed by one or more processors of one or more servers or clients. Each of the operations shown in
In some implementations, the device displays (402), in a data display panel, a first representation of a first subset of data from a data set. Respective data items in the data set are (404) associated with corresponding discrete time steps of a plurality of time steps. The first subset of data includes (406) data associated with a first time period that includes more than a threshold number of discrete time steps. In some implementations, the threshold number of time steps is (408) 1. In some implementations the threshold number of time steps is (410) an integer greater than 1 (e.g., 2, 3, 4, 5, 10 or some other reasonable number). In some implementations, the size of the discrete time steps is (412) adjustable by user. The first representation is (414) a first type of data visualization that shows changes in the first subset of data over time (e.g., as shown in
After (e.g., while) displaying the first representation of the first subset of the data, the device receives (418) a first input (e.g., from the input device) corresponding to a request to view data associated with a second time period that includes no more than the threshold number of discrete time steps. In response to receiving the first input, the device displays (420), in the data display panel, a second representation of a second subset of data from the data set. The second subset of data includes (422) data associated with the second time period. The second representation is (424) a second type of data visualization that aggregates the second subset of data over the second time period and shows divisions of the data in a respective set of one or more data-set dimensions (e.g., data-set dimensions other than the dimension of time). The second type of data visualization is (426) different from the first type of data visualization (e.g., as shown in
In some implementations, the second representation shows (428) divisions of data along a plurality of data-set dimensions simultaneously (e.g., via size of box, shading, color, saturation, tone/topic hierarchy, number of posts, topics/node structure, number of posts, sentiment or other dimensions, as described herein with reference to
In some implementations, after displaying the second representation of the second subset of the data from the data set, the device receives (432) a second input corresponding to a request to view data associated with a third time period that has no more that the threshold number of discrete time steps. In response to receiving the second input, the device displaying (434), in the data display panel, a third representation of a third subset of data from the data set. In some implementations, the third subset of data includes (436) data associated with the third time period; and the third representation is (438) the second type of data visualization that aggregates the third subset of data over the third time period and shows divisions of the data in the respective set of one or more data-set dimensions (e.g., as shown in
In some implementations, after displaying the second representation of the second subset of data the device receives (446) a third input corresponding to a request to display additional information corresponding to a respective division that is visually represented in the second representation. In some implementations, the second representation of the second subset of data includes (442) an indication that the respective division includes a plurality of subdivisions that can be viewed in greater detail in the data display panel. For example, the section of the treemap corresponding to the respective division shows subdivisions of the respective division, optionally as subdivisions of the section of the treemap that correspond to the relative amounts of data corresponding to the subdivisions, as shown in elements 5134 and 5136 in
In some implementations, after displaying the third representation of the third subset of data the device receives (446) a third input corresponding to a request to display a fourth subset of data from the data set that is associated with a third time period that includes more than the threshold number of discrete time steps. In some implementations, in response to receiving the third input, displaying (448), in the data display panel, a fourth representation of a fourth subset of data from a data set, where the fourth subset of data includes (450) data associated with the third time period, and the fourth representation is (452) the first type of data visualization that shows changes in the fourth subset of data over time and data emphasizes subdivisions of the respective division. For example, the third representation is a representation of subdivisions of the respective division aggregated over the second time period (e.g., one time step) and the fourth representation is a line graph that illustrates changes in data corresponding to the subdivisions of the respective division over the third time period (e.g., a plurality of time steps).
It should be understood that the particular order in which the operations in
Participation in an online community or other social media generates a lot of data. For example, when a user posts a question, comment, or answer, the post itself is recorded, as well as the date/time of the post, who made the post, etc. Different people related to the community or social media are interested in different aspects of the data. In some implementations, the parties who review the data (e.g., users of the device described above) are categorized into three roles, including Managers, Stakeholders, and Executives.
A manager is someone who participates in the day-to-day management of an online community platform. Manager reviews the direct measurements of participation by community members. For example, a manager would review raw metrics such as the total number of posts, the total number of posts of specific types (e.g., questions, answers), the number of fans, the number of discussion threads and the lengths of those threads, the number of times particular content is viewed by users, the comments or ratings received by each particular user and/or posts, and so on. These quantities are directly measurable by clicks, button presses, and other recorded user interactions, and constitute level 1 data. In general, the level 1 data reviewed by managers comprises raw metrics and simple reports based on the raw metrics.
A business stakeholder is someone who derives business value from the online community. Business stakeholders are less interested in the raw metrics collected about a community, and are more interested in data that shows the success or effectiveness of an online community or other social media. For example, a stakeholder reviews market share or share of the advertising in the market, or other data that demonstrates how well the media content resonates with the participants of the community. The data of interest to the business stakeholders are actionable analytics generated from the raw metrics. Various statistical and analytical techniques can be used to generate the analytics from the raw metrics. Frequently the actionable analytics have complex and non-linear relationships with the raw metrics from which the analytics are derived. The level 2 data reviewed by business stakeholders comprises actionable analytics.
Finally, business executives review data that ties social media directly to business objectives. Generally, the business objectives are financial, such as revenue or profit, but also include less tangible objectives such as customer satisfaction. The level 3 data reviewed by business executives comprise key performance indicators (KPI's), return on investment (ROI), and so on. The level 3 data is derived from the raw metrics and the actionable analytics associated with the community, as well as additional data (e.g., returns, revenues, and customer satisfaction metrics) provided by the entity using the community to promote its business objectives.
In
In
Creating a separate graph for each (node, user selection) combination is both visually hard to understand, and generally does not correspond to what a user wants to see. Instead, preferred implementations enable grouping of the selected data. For example, if a user wants a separate graph for each selected role, then the data for the selected nodes can be grouped together for each selected role. Conversely, if the user wants a graph for each of the nodes, then the data for all of the selected roles can be grouped together for each of the selected nodes. In some implementations, this is implemented using a “Group By” arrow button 5132 (i.e., an example of a dimension selector). In some of some implementations, there is a label “Group By” 5130 adjacent to the arrow button 5132 to provide more information to the user using the user interface shown in
As will be shown in later figures, when the group by arrow 5132 points to the user selector 5026, there is a single graph for each of the selected roles. The data for each graph is limited to the selected nodes rather than using data for the entire community.
Similarly, as will be shown in later figures, when the group by arrow 5132 points to the channel selector 5018, as illustrated in
In some implementations the “Group By” label 5130 and group by arrow 5132 only appear when there are multiple selections for both nodes and users/user groups.
The alignment of the sliders 5048 and 5050 with the time grain is shown in
When a node (such as “Hi-Fi Products” node 5134 in
From the drilled down treemap in
In the sequence of
As shown in
In some implementations, as shown in
In some implementations, as shown in
In some implementations, as shown in
In some implementations, in addition to the standard aggregations, more complex analytics and metrics (also referred to as advanced analytics 5618) are defined, as shown in
In some implementations, the definitions of the advanced analytics 5618 (also referred to as “derivative definitions”) are stored with the metric definitions and attribute definitions in the definition store 5606. In some implementations, the advanced analytics algorithms are implemented using various computing languages (e.g., matlab, Java, etc.), as shown in
In some implementations, as shown in
As described in earlier parts of the specification and shown in
Since the customer intelligence center 5624 allows a user to customize the metrics, aggregations, and data derivatives that can be reviewed in the customer intelligence center 5624. The definitions 5626 of the customized metrics, aggregations, and data derivatives are stored with the standard aggregations 5608. In some implementations, a metric/attribute to script/query translator 5628 is implemented and used to provide an interface between the customer intelligence center 5624 and the customized aggregations 5626 and standard aggregations 5608.
In some implementations, the data calculated according to the customized metrics, aggregations, and analytics are stored as custom view data 5630. The custom view data 5630, standard view data 5610, and data derivatives 5620 (e.g., as stored in database server(s) 118) together serve as the data source for the reports and visualizations shown to users via the metric explorer (e.g., the user interfaces described above with reference to
In some implementations, as shown in
In some implementations, the customer intelligence center 5624 allows a user (e.g., community manager, stakeholder and/or executives) to establish the criteria for having notifications sent to a user-specified recipient. In some implementations, a general purpose notification system 5632 is utilized. A user defines the trigger event for the notification, the type of information to be included in the notification, the format of the notification, and a rate limit for the notification. Examples of trigger events for a notification include a community health indicator (e.g., CHI) value having dropped below a threshold value, an average response time for a particular sub-community having reached a maximum acceptable value, new registration rate having dropped below a minimum threshold value, etc. In some implementations, a trigger event can also be a combination of several conditions. In some implementations, the user is allowed to specify what information the notification would include. For example, the user can require the notification to include actual values of certain metrics and data derivatives, and/or visualizations and reports of certain metrics/time periods/channels/users, etc. In some implementations, the notifications are provided as an email alert, a text message, or some other kinds of messages. In some implementations, the user is allowed to specify a preferred rate limit for the notifications. For example, a rate limit of 2 notifications per day means even if a trigger event has been met more than twice in a particular day, only two notifications are sent to the user. In some implementations, each notification sent to the user can include an aggregated report related to multiple trigger events that have occurred in the past but not yet been notified to the user due to the rate limit. The rate limit allows the user to control the number of notifications received each month/day/hour, so that the user is not overwhelmed by too many notification messages.
As described earlier, the metric explore 5612 is able to present community data on various metrics filtered by various attributes. The metrics explorer 5612 obtains the definitions of the metrics and attributes from the definition store 5606. In addition to the interaction data recorded on the online communities supported by the platform application 5602, in some implementations, the metric explorer also provides data from other third-party channels 5634, as shown in
In some implementations, as shown in
The foregoing description, for purpose of explanation, has been described with reference to specific implementations. However, the illustrative discussions above are not intended to be exhaustive or to limit the invention to the precise forms disclosed. Many modifications and variations are possible in view of the above teachings. The implementations were chosen and described in order to best explain the principles of the invention and its practical applications, to thereby enable others skilled in the art to best utilize the invention and various implementations with various modifications as are suited to the particular use contemplated.
Claims
1. A method, comprising:
- at a computing device with a display: displaying, in a data display panel, a first representation of a first subset of data from a data set, wherein: respective data items in the data set are associated with corresponding discrete time steps of a plurality of time steps; the first subset of data includes data associated with a first time period that includes more than a threshold number of discrete time steps; and the first representation is a first type of data visualization that shows changes in the first subset of data over time; receiving a first input corresponding to a request to view data associated with a second time period that includes no more than the threshold number of discrete time steps; and in response to receiving the first input, displaying, in the data display panel, a second representation of a second subset of data from the data set, wherein: the second subset of data includes data associated with the second time period; the second representation is a second type of data visualization that aggregates the second subset of data over the second time period and shows divisions of the data in a respective set of one or more data-set dimensions; and the second type of data visualization is different from the first type of data visualization.
2. The method of claim 1, wherein the threshold number of time steps is 1.
3. The method of claim 1, comprising:
- after displaying the second representation of the second subset of the data from the data set, receiving a second input corresponding to a request to view data associated with a third time period that has no more that the threshold number of discrete time steps; and
- in response to receiving the second input, displaying, in the data display panel, a third representation of a third subset of data from the data set, wherein: the third subset of data includes data associated with the third time period; and the third representation is the second type of data visualization that aggregates the third subset of data over the third time period and shows divisions of the data in the respective set of one or more data-set dimensions.
4. The method of claim 1, wherein the size of the discrete time steps is adjustable by user.
5. The method of claim 1, wherein the first type of data visualization is a line graph.
6. The method of claim 1, wherein the second type of data visualization is a treemap.
7. The method of claim 1, wherein the second representation shows divisions of data along a plurality of data-set dimensions simultaneously.
8. The method of claim 1, further comprising, after displaying the second representation of the second subset of data:
- receiving a third input corresponding to a request to display additional information corresponding to a respective division that is visually represented in the second representation; and
- in response to receiving the third input, replacing display of at least a portion of the second representation of the second subset of data with a third representation of a third subset of data from the data set that emphasizes subdivisions of the respective division and corresponds to the second time period.
9. The method of claim 8, wherein the second representation of the second subset of data includes an indication that the respective division includes a plurality of subdivisions that can be viewed in greater detail in the data display panel.
10. The method of claim 8, further comprising, after displaying the third representation of the third subset of data:
- receiving a third input corresponding to a request to display a fourth subset of data from the data set that is associated with a third time period that includes more than the threshold number of discrete time steps; and
- in response to receiving the third input, displaying, in the data display panel, a fourth representation of a fourth subset of data from a data set, wherein: the fourth subset of data includes data associated with the third time period; and the fourth representation is the first type of data visualization that shows changes in the fourth subset of data over time and data emphasizes subdivisions of the respective division.
11. A computing device, comprising:
- one or more processors; and
- memory;
- one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, the one or more programs including instructions for: displaying, in a data display panel, a first representation of a first subset of data from a data set, wherein: respective data items in the data set are associated with corresponding discrete time steps of a plurality of time steps; the first subset of data includes data associated with a first time period that includes more than a threshold number of discrete time steps; and the first representation is a first type of data visualization that shows changes in the first subset of data over time; receiving a first input corresponding to a request to view data associated with a second time period that includes no more than the threshold number of discrete time steps; and in response to receiving the first input, displaying, in the data display panel, a second representation of a second subset of data from the data set, wherein: the second subset of data includes data associated with the second time period; the second representation is a second type of data visualization that aggregates the second subset of data over the second time period and shows divisions of the data in a respective set of one or more data-set dimensions; and the second type of data visualization is different from the first type of data visualization.
12. The device of claim 11, wherein the threshold number of time steps is 1.
13. The device of claim 11, wherein the one or more programs include instructions for:
- after displaying the second representation of the second subset of the data from the data set, receiving a second input corresponding to a request to view data associated with a third time period that has no more that the threshold number of discrete time steps; and
- in response to receiving the second input, displaying, in the data display panel, a third representation of a third subset of data from the data set, wherein: the third subset of data includes data associated with the third time period; and the third representation is the second type of data visualization that aggregates the third subset of data over the third time period and shows divisions of the data in the respective set of one or more data-set dimensions.
14. The device of claim 11, wherein the first type of data visualization is a line graph.
15. The device of claim 11, wherein the second type of data visualization is a treemap.
16. A non-transitory computer readable storage medium storing one or more programs, the one or more programs comprising instructions, which when executed by a computing device with one or more processors cause the device to:
- displaying, in a data display panel, a first representation of a first subset of data from a data set, wherein: respective data items in the data set are associated with corresponding discrete time steps of a plurality of time steps; the first subset of data includes data associated with a first time period that includes more than a threshold number of discrete time steps; and the first representation is a first type of data visualization that shows changes in the first subset of data over time;
- receiving a first input corresponding to a request to view data associated with a second time period that includes no more than the threshold number of discrete time steps; and
- in response to receiving the first input, displaying, in the data display panel, a second representation of a second subset of data from the data set, wherein: the second subset of data includes data associated with the second time period; the second representation is a second type of data visualization that aggregates the second subset of data over the second time period and shows divisions of the data in a respective set of one or more data-set dimensions; and the second type of data visualization is different from the first type of data visualization.
17. The non-transitory computer readable storage medium of claim 16, wherein the threshold number of time steps is 1.
18. The non-transitory computer readable storage medium of claim 16, wherein the one or more programs include instructions which, when executed by the computing device, cause the device to:
- after displaying the second representation of the second subset of the data from the data set, receive a second input corresponding to a request to view data associated with a third time period that has no more that the threshold number of discrete time steps; and
- in response to receiving the second input, display, in the data display panel, a third representation of a third subset of data from the data set, wherein: the third subset of data includes data associated with the third time period; and the third representation is the second type of data visualization that aggregates the third subset of data over the third time period and shows divisions of the data in the respective set of one or more data-set dimensions.
19. The non-transitory computer readable storage medium of claim 16, wherein the first type of data visualization is a line graph.
20. The non-transitory computer readable storage medium of claim 16, wherein the second type of data visualization is a treemap.
Type: Application
Filed: Dec 5, 2013
Publication Date: Jun 26, 2014
Applicant: Lithium Technologies, Inc. (Emeryville, CA)
Inventor: Michael Wu (Oakland, CA)
Application Number: 14/098,505
International Classification: G06F 3/0481 (20060101); G06F 3/0484 (20060101);