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Physical Sciences and Mathematics Commons™
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Articles 1 - 4 of 4
Full-Text Articles in Physical Sciences and Mathematics
Spatio-Temporal Visual Analytics: A Vision For 2020s, Natalia Andrienko, Gennady Andrienko
Spatio-Temporal Visual Analytics: A Vision For 2020s, Natalia Andrienko, Gennady Andrienko
Journal of Spatial Information Science
Visual analytics is a research discipline that is based on acknowledging the power and the necessity of the human vision, understanding, and reasoning in data analysis and problem solving. Visual analytics develops methods, analytical workflows, and software tools for analysing data of various types, particularly, spatio-temporal data, which can describe the processes going on in the environment, society, and economy. We briefly overview the achievements of the visual analytics research concerning spatio-temporal data analysis and discuss the major open problems.
Insight Provenance For Spatiotemporal Visual Analytics: Theory, Review, And Guidelines, Andreas Hall, Paula Ahonen-Rainio, Kirsi Virrantaus
Insight Provenance For Spatiotemporal Visual Analytics: Theory, Review, And Guidelines, Andreas Hall, Paula Ahonen-Rainio, Kirsi Virrantaus
Journal of Spatial Information Science
Research on provenance, which focuses on different ways to describe and record the history of changes and advances made throughout an analysis process, is an integral part of visual analytics. This paper focuses on providing the provenance of insight and rationale through visualizations while emphasizing, first, that this entails a profound understanding of human cognition and reasoning and that, second, the special nature of spatiotemporal data needs to be acknowledged in this process. A recently proposed human reasoning framework for spatiotemporal analysis, and four guidelines for the creation of visualizations that provide the provenance of insight and rationale published in …
Geo-Social Visual Analytics, Wei Luo, Alan M. Maceachren
Geo-Social Visual Analytics, Wei Luo, Alan M. Maceachren
Journal of Spatial Information Science
Spatial analysis and social network analysis typically consider social processes in their own specific contexts either geographical or network space. Both approaches demonstrate strong conceptual overlaps. For example actors close to each other tend to have greater similarity than those far apart; this phenomenon has different labels in geography (spatial autocorrelation) and in network science (homophily). In spite of those conceptual and observed overlaps the integration of geography and social network context has not received the attention needed in order to develop a comprehensive understanding of their interaction or their impact on outcomes of interest such as population health behaviors …
Uncertainty-Aware Video Visual Analytics Of Tracked Moving Objects, Markus Höferlin, Benjamin Höferlin, Daniel Weiskopf, Gunther Heidemann
Uncertainty-Aware Video Visual Analytics Of Tracked Moving Objects, Markus Höferlin, Benjamin Höferlin, Daniel Weiskopf, Gunther Heidemann
Journal of Spatial Information Science
Vast amounts of video data render manual video analysis useless while recent automatic video analytics techniques suffer from insufficient performance. To alleviate these issues we present a scalable and reliable approach exploiting the visual analytics methodology. This involves the user in the iterative process of exploration hypotheses generation and their verification. Scalability is achieved by interactive filter definitions on trajectory features extracted by the automatic computer vision stage. We establish the interface between user and machine adopting the VideoPerpetuoGram (VPG) for visualization and enable users to provide filter-based relevance feedback. Additionally users are supported in deriving hypotheses by context-sensitive statistical …