As part of an ongoing effort to build a knowledge base for the field of opening governance by organizing and disseminating its learnings, the GovLab Selected Readings series provides an annotated and curated collection of recommended works on key opening governance topics. In this edition, we explore the literature on Data Visualization. To suggest additional readings on this or any other topic, please email firstname.lastname@example.org.
Data visualization is a response to the ever-increasing amount of information in the world. With big data, informatics and predictive analytics, we have an unprecedented opportunity to revolutionize policy-making. Yet data by itself can be overwhelming. New tools and techniques for visualizing information can help policymakers clearly articulate insights drawn from data. Moreover, the rise of open data is enabling those outside of government to create informative and visually arresting representations of public information that can be used to support decision-making by those inside or outside governing institutions.
Selected Reading List (in alphabetical order)
- D.J. Duke, K.W. Brodlie, D.A. Duce and I. Herman — Do You See What I Mean? [Data Visualization] — a paper arguing for a systematic ontology for data visualization.
- Michael Friendly — A Brief History of Data Visualization – a brief overview of the history of data visualization that traces the path from early cartography and statistical graphics to modern visualization practices.
- Alvaro Graves and James Hendler — Visualization Tools for Open Government Data — a paper arguing for wider use of visualization tools to open government data achieve its full potential for impact.
- César A. Hidalgo — Graphical Statistical Methods for the Representation of the Human Development Index and Its Components — an argument for visualizing complex data to aid in human development initiatives.
- Genie Stowers — The Use of Data Visualization in Government — a report aimed at helping public sector managers make the most of data visualization tools and practices.
Annotated Selected Reading List (in alphabetical order) Duke, D.J., K.W. Brodlie, D.A. Duce and I. Herman. “Do You See What I Mean? [Data Visualization].” IEEE Computer Graphics and Applications 25, no. 3 (2005): 6–9. http://bit.ly/1aeU6yA.
- In this paper, the authors argue that a more systematic ontology for data visualization to ensure the successful communication of meaning. “Visualization begins when someone has data that they wish to explore and interpret; the data are encoded as input to a visualization system, which may in its turn interact with other systems to produce a representation. This is communicated back to the user(s), who have to assess this against their goals and knowledge, possibly leading to further cycles of activity. Each phase of this process involves communication between two parties. For this to succeed, those parties must share a common language with an agreed meaning.”
- That authors “believe that now is the right time to consider an ontology for visualization,” and “as visualization move from just a private enterprise involving data and tools owned by a research team into a public activity using shared data repositories, computational grids, and distributed collaboration…[m]eaning becomes a shared responsibility and resource. Through the Semantic Web, there is both the means and motivation to develop a shared picture of what we see when we turn and look within our own field.”
Friendly, Michael. “A Brief History of Data Visualization.” In Handbook of Data Visualization, 15–56. Springer Handbooks Comp.Statistics. Springer Berlin Heidelberg, 2008. http://bit.ly/17fM1e9.
- In this paper, Friendly explores the “deep roots” of modern data visualization. “These roots reach into the histories of the earliest map making and visual depiction, and later into thematic cartography, statistics and statistical graphics, medicine and other fields. Along the way, developments in technologies (printing, reproduction), mathematical theory and practice, and empirical observation and recording enabled the wider use of graphics and new advances in form and content.”
- Just as the general the visualization of data is far from a new practice, Friendly shows that the graphical representation of government information has a similarly long history. “The collection, organization and dissemination of official government statistics on population, trade and commerce, social, moral and political issues became widespread in most of the countries of Europe from about 1825 to 1870. Reports containing data graphics were published with some regularity in France, Germany, Hungary and Finland, and with tabular displays in Sweden, Holland, Italy and elsewhere.”
Graves, Alvaro and James Hendler. “Visualization Tools for Open Government Data.” In Proceedings of the 14th Annual International Conference on Digital Government Research, 136–145. Dg.o ’13. New York, NY, USA: ACM, 2013. http://bit.ly/1eNSoXQ.
- In this paper, the authors argue that, “there is a gap between current Open Data initiatives and an important part of the stakeholders of the Open Government Data Ecosystem.” As it stands, “there is an important portion of the population who could benefit from the use of OGD but who cannot do so because they cannot perform the essential operations needed to collect, process, merge, and make sense of the data. The reasons behind these problems are multiple, the most critical one being a fundamental lack of expertise and technical knowledge. We propose the use of visualizations to alleviate this situation. Visualizations provide a simple mechanism to understand and communicate large amounts of data.”
- The authors also describe a prototype of a tool to create visualizations based on OGD with the following capabilities:
- Facilitate visualization creation
- Exploratory mechanisms
- Viralization and sharing
- Repurpose of visualizations
Hidalgo, César A. “Graphical Statistical Methods for the Representation of the Human Development Index and Its Components.” United Nations Development Programme Human Development Reports, September 2010. http://bit.ly/166TKur.
- In this paper for the United Nations Human Development Programme, Hidalgo argues that “graphical statistical methods could be used to help communicate complex data and concepts through universal cognitive channels that are heretofore underused in the development literature.”
- To support his argument, representations are provided that “show how graphical methods can be used to (i) compare changes in the level of development experienced by countries (ii) make it easier to understand how these changes are tied to each one of the components of the Human Development Index (iii) understand the evolution of the distribution of countries according to HDI and its components and (iv) teach and create awareness about human development by using iconographic representations that can be used to graphically narrate the story of countries and regions.”
Stowers, Genie. “The Use of Data Visualization in Government.” IBM Center for The Business of Government, Using Technology Series, 2013. http://bit.ly/1aame9K.
- This report seeks “to help public sector managers understand one of the more important areas of data analysis today — data visualization. Data visualizations are more sophisticated, fuller graphic designs than the traditional spreadsheet charts, usually with more than two variables and, typically, incorporating interactive features.”
- Stowers also offers numerous examples of “visualizations that include geographical and health data, or population and time data, or financial data represented in both absolute and relative terms — and each communicates more than simply the data that underpin it. In addition to these many examples of visualizations, the report discusses the history of this technique, and describes tools that can be used to create visualizations from many different kinds of data sets.”
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