For this part of the lesson each of you will begin by reading articles that report on the development of geovisual analytics software. Next, you will read about different evaluation approaches that have been applied to existing geovisual analytics software. You will then take the information from the combined readings, and find an existing geovisual analytic software and perform a basic evaluation. The evalution could examine the software's interface, functionality, etc. This is not a team assignment.
Readings on Geovisual Analytics Software and Evaluation Methods
The readings listed below are divided into two categories: Example geovisual analytics software and methods for evaluating geovisual analytics software. For this assignment, you are to review at least two (2) readings from the example geovisual analytics software listing and two (2) readings from the geovisual analytics software evaluation methods. You are free to read more than two articles from each category. You are also encouraged to perform your own searches (using Penn State's library research portal or Google Scholar) to find other relevant readings.
Readings on Example Geovisual Analytics Software (pick 2)
Bak, Peter, Matthias Schaefer, Andreas Stoffel, Daniel A. Keim & Itzhak Omer. 2009. “Density Equalizing Distortion of Large Geographic Point Sets.” Cartography and Geographic Information Science. 36(3): 237-250.
Ho, Quan, Patrik Lundblad, Tobias Åström and Mikael Jern, A Web-Enabled Visualization Toolkit for Geovisual Analytics, 2011, Proceedings of SPIE, the International Society for Optical Engineering: SPIE: Electronic Imaging Science and Technology, Visualization and Data Analysis, 78680R-78680R-12.
Hoeber, Orland, and Monjur Ul Hasan. "A geovisual analytics approach for analyzing event-based geospatial anomalies within movement data." Information Visualization 17, no. 2 (2018): 91-107.
Lemmens R, Keßler C (2014) Geo-information visualizations of linked data. In: Proceedings of the 17th AGILE conference on geographic information science, 3–6 June 2014, Castellon, Spain.
MacEachren, Alan M., Anthony C. Robinson, Anuj Jaiswal, Scott Pezanowski, Alexander Savelyev, Justine Blanford, and Prasenjit Mitra. "Geo-twitter analytics: Applications in crisis management." In 25th International Cartographic Conference, pp. 3-8. 2011.
Van Ho, Quan, Patrik Lundblad, Tobias Åström, and Mikael Jern. "A web-enabled visualization toolkit for geovisual analytics." Information Visualization 11, no. 1 (2012): 22-42.
Readings on Geovisual Analytics Software Evaluation Methods (pick 2)
Fabrikant, Sara and Griffin, Amy. 2009. “Introduction: Cognitive Issues in Geographic Information Visualization.” Cartographica, 44(3):139-143.
Heidi Lam, Enrico Bertini, Petra Isenberg, Catherine Plaisant, Sheelagh Carpendale. "Seven Guiding Scenarios for Information Visualization Evaluation.” [Research Report] 2011-992-04, 2011.
MacEachren, Alan M., Anuj Jaiswal, Anthony C. Robinson, Scott Pezanowski, Alexander Savelyev, Prasenjit Mitra, Xiao Zhang, and Justine Blanford. "Senseplace2: Geotwitter analytics support for situational awareness." In Visual Analytics Science and Technology (VAST), 2011 IEEE Conference on, pp. 181-190. IEEE, 2011.
Quinn, Sterling D., and Alan M. MacEachren. "A geovisual analytics exploration of the OpenStreetMap crowd." Cartography and Geographic Information Science 45, no. 2 (2018): 140-155.
Roth, R. E., Finch, B. G., Blanford, J. I., Klippel, A., Robinson, A. C., & MacEachren, A. M. (2011). "Card sorting for cartographic research and practice." Cartography and Geographic Information Science, 38(2), 89-99.
Slocum, Terry A., Connie Blok, Bin Jiang, Alexandra Koussoulakou, Daniel R. Montello, Sven Fuhrmann, and Nicholas R. Hedley. "Cognitive and usability issues in geovisualization." Cartography and Geographic Information Science 28, no. 1 (2001): 61-75.
Interesting Evaluation Ephemera
Crazy Egg: provides visual insight, along with traditional tabular metrics, in the form of heat maps that show click patterns, a “confetti” plot that shows single clicks and associated data, a “scrollmap” that demonstrates where your audience tends to stop scrolling, and an interactive “overlay” that summarizes page sections.
Eggplant: can test any device or technology, and interact with apps just like a user would. Analyzing the actual screen—not the code." It makes intuitive sense to me that, since users increasingly interact with mapping software through a variety of interfaces, evaluating the quality of user experience across all of those interfaces (in terms of "functionality, performance, and usability") is of the utmost desirability.
Google Analytics: Tracking an online mapping service (or anything on the web) with Google Analytics provides the administrator with various metrics regarding not just user counts such as visitors and page views, but additional information such as behavior (how long does a user stay on the site, where were they referred from, what are they most interested in etc.), and user demographics and locations as well.
Hotjar: describes itself as an “all in one” usability testing platform. It is quite pricey, but seems very powerful. It allows you to create several types of heatmaps showing user behavior on your webpages: not only click heatmaps, but also move heatmap (tracking the movement of the users' mouse without clicks!), and scroll heatmaps (how far down do users go on a page).
Oracle User Experience Insight Manager: This tool can track every user click and keystroke, provide insight into user frustration related to an application, and even record entire user sessions for analysis over time. It’s a powerful tool if you can afford it along with the specially trained staff to configure, use, and maintain it.
Slack: a channel based messaging application that can connect to almost any web-enabled tool. It allow entry of a bug or feature request directly into whatever application lifecycle management tool your team uses (e.g. Visual Studio Team services, GIT, etc). It could also provide immediate access to document creation so that software team members can use whatever office tools they need at the time (e.g. Excel, Google Sheets, Word, etc).
Usabilla: a usability testing platform that offers several functionalities, but I believe that its most powerful features focus on getting targeted feedback from users.
Evaluation of a Geovisual Analytic Tool
Below, we present several examples of existing geovisual analytics tools that have been developed. These examples are designed to give you a limited perspective on what has been done to explore refugee data.
Existing Geovisual Analytics Tools
- From the website: ”The Refugee Project is an interactive map of refugee migrations around the world in each year since 1975. UN data is complemented by original histories of the major refugee crises of the last four decades, situated in their individual contexts.”
Not necessarily software per se, but an article on how the refugee flow has been illustrated by maps. From Forbes magazine.
Another example of mapping refugee data. From GDELT Project.
Different state maps showing Syrian refugee crisis.
1. Choose an existing geovisual analytic software. Rather than use one listed above, you should find a geovisual analytic software for this task of your own choosing. This geovisual analytic software could be a website, an app, or downloadable software. For this task, the geovisual analytic software should be free for use. Once you have located the software, explore its interface and functionality. After you feel comfortable with it, write a concise summary that describes its overall utility and functionality. Include a screen capture or two showing the interface and perhaps a symbolization method. Explain some of the available tools the software contains that help visualize data. Make sure to provide a link or some reference to where you found the software.
2. Using one or more of the approaches presented in the readings, discuss the appropriateness of how successful one or more of the methods would be in evaluating the software of your choosing. In your summary, make sure to comment on the strengths and weakness of the evaulation method with regard to your software of choosing.
3. Given what you have learned thus far in the course and any thoughts from your evaluation critique, what kinds of additional tools or functionalities would you recommend be included in the geovisual analytics software of your choosing?