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This is the starting page for the Data Visualization Community Group. The structure of this page is likely to change as we start collecting information.

What is Data Visualization?

Data visualization or data visualisation is viewed by many disciplines as a modern equivalent of visual communication. It is not owned by any one field, but rather finds interpretation across many (e.g. it is viewed as a modern branch of descriptive statistics by some, but also as a grounded theory development tool by others). It involves the creation and study of the visual representation of data, meaning "information that has been abstracted in some schematic form, including attributes or variables for the units of information" by Michael Friendly (2008), "Milestones in the history of thematic cartography, statistical graphics, and data visualization".

A primary goal of data visualization is to communicate information clearly and efficiently to users via the information graphics selected, such as tables and charts. Effective visualization helps users in analyzing and reasoning about data and evidence. It makes complex data more accessible, understandable and usable. Users may have particular analytical tasks, such as making comparisons or understanding causality, and the design principle of the graphic (i.e., showing comparisons or showing causality) follows the task. Tables are generally used where users will look-up a specific measure of a variable, while charts of various types are used to show patterns or relationships in the data for one or more variables.

Data visualization is both an art and a science. The rate at which data is generated has increased, driven by an increasingly information-based economy. Data created by internet activity and an expanding number of sensors in the environment, such as satellites and traffic cameras, are referred to as "Big Data". Processing, analyzing and communicating this data present a variety of ethical and analytical challenges for data visualization. The field of data science and practitioners called data scientists have emerged to help address this challenge.


The mission of this group is to provide a unified data model for data visualization, data visualization API, core model of data visualization methods and category, and domain specific data visualization methods (e.g. scientific data visualization), and further, data interactive analysis method.

Goal #1

To provide standard ways of data model and visualization APIs. Avoid web applications locked into dedicate data visualization javascript libs, or browser implementation.

Goal #2

Define Data Visualization Method for Domain Specific Data (e.g. Scientific Data, Smart city Data).

Goal #3

Considering the Method of Interactions with Data.

Identified Task Forces

Per conversation during ChinaVis 2016 at Changsha, China, some of the CG members are suggested to start the following task forces:

Use Cases, Requirements and Reference Implementations

To collect use cases of using data visualization in Web, visualization of shared data sets on the web. To identify the standardization requirements from the use cases. To identify the possible reference implementations from industry.


To workout a list of terminologies of data visualization. To workout a reference on translations in different languages (say, Simplified/Traditional Chinese, English, ...)

Datavis Markup Language (?)

To identify if there's consensus on creating a new markup language (based on SPSS grammer?)

Data Model

To define the data model for general/standard data visualization method. To define the data format transferring from server to browser (a JSON based approach?)

DataVis Interaction Method

To identify if there's consensus on defining the standard interaction method, interactive analysis for data visualization.

We expect to soon launch regular teleconferences following a poll to select a date and time. We're also planning to organize a Workshop on Data visualization in Beijing in early Jan of 2015.


Road map of this CG is not identified carefully. Any comments are welcomed. Current discussion mentioned the following tasks.

  • Terminology
  • Use cases and Requirements
  • Markup Languages
  • Data Models
  • APIs and Interactions

Group Events

Meetup event on Sep 20

 The first unofficial meetup event for DataVis CG was organized on Sep 20 2015 in Beijing, China. See more details below.
 Date: Sep 20th 2015 
 Time: 1:00AM UTC;9:00AM (GMT+8 Beijing Time) 
 Location: Peking University, No.5 Yiheyuan Road Haidian District, Beijing, P.R.China
           北京市海淀区颐和园路5号 北京大学 英杰交流中心 星光厅 
 Host: Peking University
 IRC channel: #datavis (see more about IRC at 
 Language: onsite discussion will be in Chinese; IRC scribing and discussion will be in English 
 Remote Participation: facility permitting 
 * Agenda:
 09:00-09:10 Welcome from Prof.Xiaoru Yuan (Peking University) and Round Table Introduction 
 09:10-09:30 Thoughts on Data Visualization Standards - Prof.Xiaoru Yuan (Peking University)
 09:30-09:50 Frond End Development Requirements for Data Visualization - Speaker TBD 
 09:50-10:10 National Standards Work on Big Data - Jinghua Zhao - (CESI)
 10:10-10:30 Introduction of W3C Standards Making Process and the DataVis CG - Chunming Hu (W3C/Beihang) 
 10:30-11:50 Open Discussion ( Discussion Items listed Below) 
 10:50-12:00 Wrap up
 * Open Discussion Items (Not limited to the following items. New items are welcome.)
 1. Use case, scenario and requirements for data visualization standards 数据可视化标准制订的场景、需求、意义
 2. Roadmap for data visualization standards work 数据可视化标准的工作范畴和未来规划 
 3. Possible work scale and work plan 任务分工及近期可开展的标准工作
 4. W3C standards making process and tools 国际化(W3C)工作流程与辅助工具
 5. Possibility to make national standards for data visualization 国内标准立项的可能性探讨
 Event Minutes in English
 Event Report in both English and Chinese

TPAC 2015 Breakout Sessions on October 28

 in Sapporo, Japan. See more details below.
 Date: Sep 20th 2015 
 Time: 2:30PM-3:30PM JST(GMT+9 Tokyo Time) 
 Location: 1F Waiting Room, Sapporo Convention Center
 IRC channel: #datavis (see more about IRC at 
 Language: English 
 * Background Info: 
 Brief Info of the Breakout Session:
 * Open Discussion Items (Not limited to the following items. New items are welcome.)
 1. Use case, scenario and requirements for data visualization standards 数据可视化标准制订的场景、需求、意义
 2. Scope of the data visualization 数据可视化标准的工作范畴和未来规划 
 3. Data Models for visualization 数据可视化中的数据模型
 4. APIs and interactions API 
 5. How DataVis CG works

ChinaVis 2016 Special Session

 in Changsha, China.
 See more detail at W3C China Site (in Chinese). 
 Here's some comments from the meeting.
  • define the vocabulary and terminology (with translation)
  • considering the interaction to datavis elements
  • web components (is bar-chart a good example of web component? )
  • style of data visualization
  • encoding / data model / data format of datavis component
  • considering the structure of data (data format standard)
  • think of data reference (sometimes, the data feed into the datavis component might be a refer to a slice of data)
  • standardization of datavis javascript libs
  • data converting method between implementations
  • datavis in different application area (scientific datavis, commercial datavis, city datavis), there might be common part, and domain-specific part
  • extensibility of datavis specs: small core + domain specific extensions
  • thinking of special requirements of geo-spatial data visualization
  • SVG like datavis component description: a new markup language? (SPSS grammer)

The meeting agrees to setup several task forces to align the ideas, and get some consensus, draft different part of CG report. Includes but not limits to:

  • use case, req & implementation
  • terminology
  • markup language
  • data model and data formats
  • interaction method
  • ...

Group Communication

Data Visualization Community Group mainly uses mailing list for discussion. English is highly recommended as the working language in this community group. The publicly archived list was set up for this purpose.

Group Decision Process

  • Consensus Decisions
 This group will seek consensus decisions. After discussion (via the mailing list or issues list) and due consideration of different opinions, the Chair should record a decision and any objections.
 A common way to determine consensus for important decisions is to conduct a Call for Consensus (CfC) where the Chair puts a proposal to the group on the public mail list and asks for feedback from the Participants within some period of time that is at least 7 days. Silence implies consent. Direct feedback is encouraged, especially to weigh the degree of consensus when there is dissent.
 When the group reaches a decision at a meeting, the decision is tentative. Any group participant may object to a decision reached at a meeting within 7 days of publication of the decision on the mailing list. That decision must then be confirmed on the mailing list.
  • Voting
 Participants may call for an formal vote if they feel the Chair has not accurately determined the consensus of the group, or if the Chair refuses to assess consensus. This should be a rare event, only where the usual, less formal means of making decisions are not accepted. At least 5 Participants, no two from the same organization (or 50% of the organizations and individuals, whichever is smaller), must agree with the call for a formal vote. The call for a vote must specify the duration of the vote which must be at least 7 days and should be no more than 14 days. The Chair must start the vote within 7 days of the request, or group members may start it themselves. The decision is based on the majority of the ballots cast. It is the Chair's responsibility to ensure that the decision process is fair, respects the consensus of the group, and does not unreasonably favor or discriminate against any group participant or their employer.
  • Chair Selection
 Participants in this group choose their Chair(s) and can replace their Chair(s) at any time using whatever means they prefer.
 However, if 5 participants —no two from the same organization— call for an election, the group must use the following process to replace any current Chair(s) with a new Chair, consulting the Community Development Lead on election operations (e.g., voting infrastructure and using RFC 2777).
 Participants announce their candidacies. Participants have 14 days to announce their candidacies, but this period ends as soon as all participants have announced their intentions. If there is only one candidate, that person becomes the Chair. If there are two or more candidates, there is a vote. Otherwise, nothing changes.
 Participants vote. Participants have 21 days to vote for a single candidate, but this period ends as soon as all participants have voted. The individual who receives the most votes —no two from the same organization— is elected chair. In case of a tie, RFC 2777 is used to break the tie. An elected Chair may appoint co-Chairs.
 Participants dissatisfied with the outcome of an election may ask the Community Development Lead to intervene. The Community Development Lead, after evaluating the election, may take any action including no action.

IPR Policy

Standardization should follow implementation experience and a consensus on core use cases. In some cases, proposals could be submitted to existing W3C Working Groups, and in others, new Working Groups could be proposed. Any work that is intended for use in W3C standards specifications will be subject to the Contributor License Agreement (CLA).

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