11,970 research outputs found
Dynamic Composite Data Physicalization Using Wheeled Micro-Robots
This paper introduces dynamic composite physicalizations, a new class of physical visualizations that use collections of self-propelled objects to represent data. Dynamic composite physicalizations can be used both to give physical form to well-known interactive visualization techniques, and to explore new visualizations and interaction paradigms. We first propose a design space characterizing composite physicalizations based on previous work in the fields of Information Visualization and Human Computer Interaction. We illustrate dynamic composite physicalizations in two scenarios demonstrating potential benefits for collaboration and decision making, as well as new opportunities for physical interaction. We then describe our implementation using wheeled micro-robots capable of locating themselves and sensing user input, before discussing limitations and opportunities for future work
Investigating Rumor Propagation with TwitterTrails
Social media have become part of modern news reporting, used by journalists
to spread information and find sources, or as a news source by individuals. The
quest for prominence and recognition on social media sites like Twitter can
sometimes eclipse accuracy and lead to the spread of false information. As a
way to study and react to this trend, we introduce {\sc TwitterTrails}, an
interactive, web-based tool ({\tt twittertrails.com}) that allows users to
investigate the origin and propagation characteristics of a rumor and its
refutation, if any, on Twitter. Visualizations of burst activity, propagation
timeline, retweet and co-retweeted networks help its users trace the spread of
a story. Within minutes {\sc TwitterTrails} will collect relevant tweets and
automatically answer several important questions regarding a rumor: its
originator, burst characteristics, propagators and main actors according to the
audience. In addition, it will compute and report the rumor's level of
visibility and, as an example of the power of crowdsourcing, the audience's
skepticism towards it which correlates with the rumor's credibility. We
envision {\sc TwitterTrails} as valuable tool for individual use, but we
especially for amateur and professional journalists investigating recent and
breaking stories. Further, its expanding collection of investigated rumors can
be used to answer questions regarding the amount and success of misinformation
on Twitter.Comment: 10 pages, 8 figures, under revie
Tea: A High-level Language and Runtime System for Automating Statistical Analysis
Though statistical analyses are centered on research questions and
hypotheses, current statistical analysis tools are not. Users must first
translate their hypotheses into specific statistical tests and then perform API
calls with functions and parameters. To do so accurately requires that users
have statistical expertise. To lower this barrier to valid, replicable
statistical analysis, we introduce Tea, a high-level declarative language and
runtime system. In Tea, users express their study design, any parametric
assumptions, and their hypotheses. Tea compiles these high-level specifications
into a constraint satisfaction problem that determines the set of valid
statistical tests, and then executes them to test the hypothesis. We evaluate
Tea using a suite of statistical analyses drawn from popular tutorials. We show
that Tea generally matches the choices of experts while automatically switching
to non-parametric tests when parametric assumptions are not met. We simulate
the effect of mistakes made by non-expert users and show that Tea automatically
avoids both false negatives and false positives that could be produced by the
application of incorrect statistical tests.Comment: 11 page
Harnessing Collaborative Technologies: Helping Funders Work Together Better
This report was produced through a joint research project of the Monitor Institute and the Foundation Center. The research included an extensive literature review on collaboration in philanthropy, detailed analysis of trends from a recent Foundation Center survey of the largest U.S. foundations, interviews with 37 leading philanthropy professionals and technology experts, and a review of over 170 online tools.The report is a story about how new tools are changing the way funders collaborate. It includes three primary sections: an introduction to emerging technologies and the changing context for philanthropic collaboration; an overview of collaborative needs and tools; and recommendations for improving the collaborative technology landscapeA "Key Findings" executive summary serves as a companion piece to this full report
Visualization of and Access to CloudSat Vertical Data through Google Earth
Online tools, pioneered by the Google Earth (GE), are facilitating the way in which scientists and general public interact with geospatial data in real three dimensions. However, even in Google Earth, there is no method for depicting vertical geospatial data derived from remote sensing satellites as an orbit curtain seen from above. Here, an effective solution is proposed to automatically render the vertical atmospheric data on Google Earth. The data are first processed through the Giovanni system, then, processed to be 15-second vertical data images. A generalized COLLADA model is devised based on the 15-second vertical data profile. Using the designed COLLADA models and satellite orbit coordinates, a satellite orbit model is designed and implemented in KML format to render the vertical atmospheric data in spatial and temporal ranges vividly. The whole orbit model consists of repeated model slices. The model slices, each representing 15 seconds of vertical data, are placed on the CloudSat orbit based on the size, scale, and angle with the longitude line that are precisely and separately calculated on the fly for each slice according to the CloudSat orbit coordinates. The resulting vertical scientific data can be viewed transparently or opaquely on Google Earth. Not only is the research bridged the science and data with scientists and the general public in the most popular way, but simultaneous visualization and efficient exploration of the relationships among quantitative geospatial data, e.g. comparing the vertical data profiles with MODIS and AIRS precipitation data, becomes possible
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