Advancements in personal data collection and visualization-commonly referred to as the quantified self (QS) movement-allow individuals to self-track health and other attributes. We extend quantified self (QS) concepts to the quantified other (QO) to explore how the use of technology, collection of data on one's pet dog, and personal visualization affect pet owners' understandings of, and relationships with, their pets. We introduce the term Human-Pet-Computer Interaction (HPCI) as the study of how technology can be designed and used to advance human-pet companionships. As an example, we describe CompanionViz, a personal information visualization prototype designed to inform pet owners on their dogs" caloric inputs/ outputs, as well as exercise and movement habits. We present a user study of CompanionViz featuring a twelve-participant survey and one field study, consisting of three unique use cases, and show that by providing pet owners with quantifiable awareness of their dogs" health and exercise habits using personal visual representations, pet owner-dog bonds can benefit..
Abstract:We introduce spatial patterns of Tweets visualization (SPoTvis), a web-based geovisual analytics tool for exploring messages on Twitter (or "tweets") collected about political discourse, and illustrate the potential of the approach with a case study focused on a set of linked political events in the United States. In October 2013, the U.S. Congressional debate over the 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. SPoTvis supports the analysis of these events using an interactive map connected dynamically to a term polarity plot; through the SPoTvis interface, 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. Relationships among places, politics and discourse on Twitter are quantified using statistical analyses and explored visually using SPoTvis. A two-part user study evaluates SPoTvis' OPEN ACCESS ISPRS Int. J. Geo-Inf. 2015, 4 338 ability to enable insight discovery, as well as the tool's design, functionality and applicability to other contexts.
Individual movement traces recorded by users of activity tracking applications such as Strava provide opportunities that extend beyond delivering personal value or insight to the individual who engages in these “quantified-self” (QS) activities. The large volumes of data generated by these individuals, when aggregated and anonymized, can be used by city planners, Departments of Transportation, advocacy groups, and researchers to help make cities safer and more efficient. This opportunity, however, is constrained by the technical skills and resources available to those tasked with assessing bicycling behavior in urban centers. This paper aims to address the question of how to design cartographic interfaces to serve as mediated platforms for making large amounts of individual bicycling data more accessible, usable, and actionable. Principles of cartographic representation, geovisual analytics techniques, and best practices in user interface/experience design are employed to arrive at an effective visualization tool for a broad urban planning audience. We use scenario-based design methods to encapsulate knowledge of map use practice gleaned from the development process, and conduct a post-implementation two-part user study with seven domain experts to further assess the usability and utility of the interactive mapping tool.
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