Destination Area: Data and Decisions (D&D)
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The DA Data and Decisions advances the human condition and society with better decisions through data. D&D integrates all DAs and SGAs with data analytics and decision sciences. Work in this area embraces equity in the human condition by seeking the equitable distribution and availability of physical safety and well-being, psychological well-being, respect for human dignity, and access to crucial material and social resources throughout the world’s diverse communities. D&D also addresses policymaking and policy analysis, collaborating at the intersection of scientific evidence, governance, and analyses to translate scholarship into practice.
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Browsing Destination Area: Data and Decisions (D&D) by Content Type "Conference proceeding"
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- Applying Best Supply Chain Practices to Humanitarian ReliefRussell, Roberta S.; Hiller, Janine S. (Penn State, 2015-05)With the growth in length and breadth of extended supply chains, more companies are employing risk management techniques and resilience planning to deal with burgeoning and costly supply chain disruptions. As companies can learn from humanitarian groups, so can humanitarian groups learn from industry how to respond, recover, and prepare for these disruptive events. This paper looks at industry leaders in supply chain risk management and explores how humanitarian supply chains can learn from industry best practices.
- CrowdLayout: Crowdsourced Design and Evaluation of Biological Network VisualizationsSingh, Divit P.; Lisle, Lee; Murali, T. M.; Luther, Kurt (ACM, 2018-04)Biologists often perform experiments whose results generate large quantities of data, such as interactions between molecules in a cell, that are best represented as networks (graphs). To visualize these networks and communicate them in publications, biologists must manually position the nodes and edges of each network to reflect their real-world physical structure. This process does not scale well, and graph layout algorithms lack the biological underpinnings to offer a viable alternative. In this paper, we present CrowdLayout, a crowdsourcing system that leverages human intelligence and creativity to design layouts of biological network visualizations. CrowdLayout provides design guidelines, abstractions, and editing tools to help novice workers perform like experts. We evaluated CrowdLayout in two experiments with paid crowd workers and real biological network data, finding that crowds could both create and evaluate meaningful, high-quality layouts. We also discuss implications for crowdsourced design and network visualizations in other domains.
- Designing for Schadenfreude (or, how to express well-being and see if youʼre boring people)André, Paul; Schraefel, M.C.; Dix, Alan; White, Ryen W.; Bernstein, Michael; Luther, Kurt (ACM, 2010)This position paper presents two studies of content not normally expressed in status updates—well-being and status feedback—and considers how they may be processed, valued and used for potential quality-of-life benefits in terms of personal and social reflection and awareness. Do I Tweet Good? (poor grammar intentional) is a site investigating more nuanced forms of status feedback than current microblogging sites allow, towards understanding self-identity, reflection, and online perception. Healthii is a tool for sharing physical and emotional well-being via status updates, investigating concepts of self-reflection and social awareness. Together, these projects consider furthering the value of microblogging on two fronts: 1) refining the online personal/social networking experience, and 2) using the status update for enhancing the personal/social experience in the offline world, and considering how to leverage that online/offline split. We offer results from two different methods of study and target groups—one co-workers in an academic setting, the other followers on Twitter—to consider how microblogging can become more than just a communication medium if it facilitates these types of reflective practice.
- Observing a Global Pandemic from Space: Evaluating Participatory Geographic Information Systems (PGIS) during the SARS-CoV-2 PandemicDuChesne, Danielle (Virginia Tech, 2021-04-30)When the novel SARS-CoV-2 virus emerged in December 2019, GIS technologies and web-based GIS dashboards were rapidly employed to share information regarding disease spread and impact on society. As GIS-based tools are capable of providing spatial complexity, interactivity, and interconnectedness, its growth in popularity to help solve multifaceted problems has also grown. These efforts from citizens and scientists alike to engage in Participatory GIS (PGIS) were essential for timely and effective epidemic monitoring and response. However, the original intent of PGIS to involve the public in geographical mapping to uncover context-sensitive place-based information (Brown & Kyttä, 2014) has also created discrepancies such as ignoring the sociopolitical context of data and disregards common geovisualization best practices. The goal of this poster aims to evaluate the challenges of PGIS in analyzing data as it was used during the current global pandemic by exploring COVIDPoops19, a PGIS dashboard tracking wastewater testing as well as describing potential solutions from interdisciplinary frameworks that allow for better decision making, planning, and community action.
- Toward neurobehavioral metrics of social function: Examples from autismChiu, Pearl H. (2012-10-12)Pearl Chiu, researcher at the Virginia Tech Carilion Research Institute, describes the use of behavioral economic games and functional magnetic resonance imaging in the exploration of social symptoms of autism and lists desired collaborations that may become possible with a Center for Autism Research.
- Towards Use And Reuse Driven Big Data ManagementXie, Zhiwu; Chen, Yinlin; Griffin, Julie; Walters, Tyler; Tarazaga, Pablo Alberto; Kasarda, Mary (2015-06-03)We propose a use and reuse driven big data management approach that fuses the data repository and data processing capabilities in a co-located, public cloud. It answers to the urgent data management needs from the growing number of researchers who don’t fit in the big science/small science dichotomy. This approach will allow researchers to more easily use, manage, and collaborate around big data sets, as well as give librarians the opportunity to work alongside the researchers to preserve and curate data while it is still fresh and being actively used. This also provides the technological foundation to foster a sharing culture more aligned with the open source software development paradigm than the lone-wolf, gift-exchanging small science sharing or the top-down, highly structured big science sharing. To materialize this vision, we provide a system architecture consisting of a scalable digital repository system coupled with the co-located cloud storage and cloud computing, as well as a job scheduler and a deployment management system. Motivated by Virginia Tech’s Goodwin Hall instrumentation project, we implemented and evaluated a prototype. The results show not only sufficient capacities for this particular case, but also near perfect linear storage and data processing scalabilities under moderately high workload.
- Twitter Use During an Emergency Event: The Case of UT Austin ShootingLi, Lin Tzy; Yang, Seungwon; Kavanaugh, Andrea L.; Fox, Edward A.; Sheetz, Steven D.; Shoemaker, Donald J. (2011-06-01)This poster presents one of our efforts developed in the context of Crisis, Tragedy, and Recovery Network (CTRnet) project. One of our derived works from this project is the use of social media by government to respond to emergency events in towns and counties. Monitoring social media information for unusual behavior can help identify these events once we can characterize their patterns. As an example, we analyzed the campus shooting occurred in the University of Texas, Austin, on September 28, 2010. In order to study the pattern of communication and the information communicated using social media on that day, we collected publicly available data from Twitter. Collected tweets were analyzed and visualized using Natural Language Toolkit, word clouds, and graphs. They showed how news and posts related to this event swamped the discussions of other issues.
- An Unsupervised Probabilistic Method for Large Scale Flood Mapping: Exploring Archive of Sentinel-1A/B Satellites over IndiaSherpa, Sonam Futi (Virginia Tech, 2021-04-30)Synthetic aperture radar (SAR) imaging provides an all-weather sensing technique that is suitable for near-real-time mapping of disasters such as floods. In this article, I use SAR data acquired by Sentinel-1A/B satellites to investigate a flood event that affected the Indian state of Kerala in August 2018. I apply a Bayesian approach to generate probabilistic flood maps, which contain for each pixel its probability to be flooded rather than binary flood information. I find that the extent of the flooded area begins to increase throughout Kerala after August 8, with the highest values on August 9 and August 21. I observe no apparent correlation between the spatial distributions of the flooded areas and the rainfall amounts at the district level of the study area. Instead, larger flooded areas are in the districts of Alappuzha and Kottayam, located in the downstream floodplain of the Idduki dam, which released a significant volume of water on August 16. The lack of apparent correlation is likely due to two reasons: first, there is often some delay between the rainfall event and the flooding, especially for rather large catchments where flood waves need some time to reach floodplains from higher elevations. Second, rainfall is more abundant at overhead catchments (hills and mountains), whereas flood occurs further downstream in the floodplains. Further comparison of our SAR-based flood maps with optical data and flood maps produced by moderate resolution imaging spectroradiometer highlights the advantages of our data and approach for rapid response purposes and future flood forecasting.
- Virginia Tech Center for Autism Research - Tina Savla perspectiveSavla, Jyoti S. (2012-10-12)This work describes the research perspective of Tina Savla, Center for Gerentology and Department of Human Development. The primary area of research is caregiving and its relationship to stress, including behavioral, psychological, and physiological outcomes of distress.