1. Chapter 9Visualization in e-Social Science Liu Yan Yeungnam university

2. Introduction What is visualization? Visualization is any technique for creating images, diagrams, or animations to communicate a message. Visualization through visual imagery has been an effective way to communicate both abstract and concrete ideas since the dawn of man. Visualizations are a core e-science application “e-Science means science increasingly undertaken through distributed global collaborations enabled by the Internet, and involving very large or complex data collections, Terascale computing resources and high performance visualisation” -Taylor 2002

3. Introduction What can Visualizations do? Visualizations can help mediate between humans and complex datasets: not just to highlight and identify patterns within the entire set but also to help us to select relevant parts of the data to analyze in detail and the most appropriates of analysis. What can we learn in this chapter? ① How visualizations may help social scientists’s own research. ② Introduce some of the practical issues involved in the decision to adopt a visualization technique.

4. Classifications of visualizations The highly cited classification focus on the data types to be visualized. (Table 9.1 Classifications of visualizations,165 page) Standard: a general-purpose visualization designed for a wide variety of similar applications or data collections. Standard visualizations are offen available through free software. Bespoke: a visualization created specifically for and tied to, one application or date collection.

5. Recent history of social science visualizations Applications of geography and planning: maps,two-dimensional diagrams and three dimensional models(Ex: Mapping Cyberspace) Applications of politics , economics and sociology: (Ex: a map illustrating visitors’ routes through Duisburg Zoo in Germany.

6. Recent history of social science visualizations SNA( Social Network Analysis): employ network diagrams and have also measured many aspects of network structures. Applications of psychology: might experiment with a range of different state-of-the-art visualizations and the other social sciences might lag significantly behind.

7. E-social science visualizations Case 1: Wikipedia history flow visualization Wikipedia is a popular collaboratively authored free online encyclopedia, it’s easy to edit pages because they contain an edit button and allow unrestricted access to the reader, which make contributions vulnerable.

8. E-social science visualizations IBM's History Flow tool is a visualization tool for a time-sequence of snapshots of a document in various stages of its creation. The tool supports tracking contributions to the article by different users, and can identify which parts of a document have remained unchanged over the course of many full-document revisions. The History Flow tool tracks and graphs the content of each page on a sentence-by-sentence level, using a simple graphical representation to allow many different sentences to be simultaneously presented over time.

9. E-social science visualizations Case 2: Evolino visual simulations Evolino is a research project, with origins in both physics and socipligy, to develop visual simulations of the dynamics of group interactions. Evolino produces a dynamic, evolving display. Each simulation is a computer program that incorporates a mathematical model of social interaction with variable user defined parameters. The main Evolino simulation illustrates the process of natural selection and can be used to experiment with different selection processes. (Ex: figure 9.3 171page)

10. E-social science visualizations Case 3: Usenet conversation analyses with treemap Microsoft’s Netscan project is an initiative to monitor usenet newsgroups and to analyze the pattern of postings and discussion. A core strategy of this project is to continually collect newsgroup posting and use treemap diagrams to simultaneously represent the volume of postings. The netscan research addresses a set of social science goals, and uses significant computing power to process large volumes of internet data . The investigators use a range of visualizations specially designed to highlight different aspects of the data. Online examples of visualizations: Place and Spaces: Mapping Science http://www.scimaps.org/ The Atlas of Cyberspace http://www.kitchin.org/atlas/ Gallery of Data Visualization http://www.math.yorku.ca/SCS/Gallery/

11. Fast, free “born digital” visualizations The focus about visualizations in this section presents a different type of radical innovation: convenience. 1. Blog Pulse monitors millions of individual blogs daily and uses a Google-like interface to visitors search them. It also allows users to submit multiple simultaneous queries and plot the results over time in a graph, allowing the detection of trends.(figure 9.4 173 page) it suggests that the discussion of visualization increased slightly in blog space during the start of 2008. it indicates the blog graphs have embedded context in terms of the original blog postings, which can be viewed by clicking on the relevant part of the graph.

12. Fast, free “born digital” visualizations 2.TouchGraphis another example of a convenient free online visualization. The ToughGraph Google Browser allows the user to enter a term or phrase of interest and then instantly produces a map illustrating the most important sites for that term and the relationship between the sites. (Figure 9.5 174 page) Ex: Facebook, issuecrawler.net, socscibot and lexiurl.

13. Fast, free “born digital” visualizations Mashups and geographic visualization A mashup is a computer program that combines data from more than one source to deliver an integrated product online. Figure 9.6 (176 page) is a googlemashup, illustrating the geographic diversity of one person’s MySpace friends by plotting them on a map of North America. Figure 9.7(176 page) shows the same mashup and data after a few mouse clicks to zoom in on the data, and it is even possible to zoom in to a street-level. A single mouse click will convert the map into a satellite image showing the terrain of the area.

14. conclusion the main advice: look at a range of different types of visualization to get ideas about what is possible, and the engage in dialog with an information visualization expert to arrive at a final decision about the best type to choose and the best strategy to adopt in order to create it. Lots kind of evolutions on e-social science: -More complex visualizations -Quicker production -More distributed -More permanence -More new applications -More data

15. Future research agenda A third broad research agendas for future research: 1. to evaluate the spread of visualizations in e-science. 2. to identify, assess and develop strategies to ameliorate obstacles to the use of visualizations with the social science. 3. to evaluate e-social science visualizations through a cost-benefit analysis.

16. Thank you end