Spatio-Temporal Data Visualization with Interactive Maps in Visual Analytics ApplicationsAlice Rühl, Penn State UniversityScott Pezanowski, Penn State UniversityFrank Hardisty, Penn State UniversityThe increasing importance of Visual Analytics, particularly in response to the advent of 'big data', calls for greater attention to maps in analytic tools and applications. While maps provide a familiar, understandable interface to underlying data, not enough has been done in the field of Visual Analytics to advance the design and usage of maps.
This study explores the development of map components within multi-view applications using multivariate and zoom-level dependent representations of news event data. Integrated in the system with a timeline, a word cloud and other view components, we consider the traditional 'rules' of cartography as well as aspects of human-computer interaction and interactive design research. This allows users to efficiently explore complex spatio-temporal data. Our approach was validated by re-developing the mapping component inside STempo, a project developed at the GeoVISTA Center, Pennsylvania State University.
View presentation »Mapping the Intersection between Social Media and Open SpacesAlan McConchie, Stamen DesignEarlier this year, Stamen launched
parks.stamen.com, a project that collects geotagged social media content within parks and other open spaces in California. We harvest data from four major social media services (Twitter, Foursquare, Flickr, and Instagram), each of which provides a unique view into the different facets of each park, and the diverse communities who enjoy these parks.
We also found that each social network service's public API imposes different constraints on our queries, producing their own intricate geographic patterns. Thus, the quirks of how each API was written results in distinct geometries in digital space that mirror the park users' human geographies in embodied physical space.
In this presentation I will describe the algorithms we use to collect the social media data, and show the cartographic techniques we have been experimenting with to show how parks are used by the public, and how they are represented digitally.
View presentation »SPoTvis: A Geovisual Analytics Tool for Discovering Multi-Scale Spatial Patterns in Tweets Surrounding the 2013 US Government ShutdownJonathan Nelson, Penn State University
Sterling Quinn, Penn State University
Brian Swedberg, Penn State University
Wanghuan Chu, Penn State University
Maggie Houchen, Penn State University
Todd Bodnar, Penn State University
Alan M. MacEachren, Penn State University
In October 2013, the US Congressional debate over allocation of funds to the Patient Protection and Affordable Care Act (commonly known as the ACA or 'Obamacare') culminated in a 16-day government shutdown. Meanwhile the online health insurance marketplace related to the ACA was making a public debut hampered by performance and functionality problems. Messages on Twitter during this time period included sharply divided opinions about these events, with many people angry about the shutdown and others supporting the delay of the ACA implementation. We introduce SPoTvis, a web-based geovisual analytics tool for exploring Twitter messages (or 'tweets') collected about the shutdown. Using an interactive map connected to a term polarity plot, users can compare the dominant subthemes of tweets in any two states or congressional districts. Demographic attributes and political information on the display, coupled with functionality to show (dis)similar features, enrich users' understandings of the units being compared.
View presentation »VisMatch: A Web Tool for Selecting Effective Space-Time Visualization Techniques - Tool Design and User Study ResultsJoanna Merson, Arizona State UniversitySuccessful visualizations can reveal patterns and relationships that would be concealed in traditional maps. However, researchers often choose a visualization technique just because they are familiar with it, regardless of what other visualization techniques might better communicate their data. A researcher that decides search out the best technique from the vast body of visualization literature will be faced with the slow and difficult task of wading through the nuances of very specific implementations. Therefore, I have developed VisMatch, a streamlined, web-based tool designed to help researchers choose which visualization techniques are best suited to the spatial-temporal data they want to communicate. In this presentation, I will present 1) the design behind the tool, which suggests optimal visualization techniques by considering data composition and audience needs; and 2) the results from a user-survey evaluating researcher interaction with VisMatch.
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