Uncertainty Visualization for Crisis Management in Smart Grid Environments

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SENARATNE, Hansi, Sebastian MITTELSTÄDT, Christine JACOB, Tobias SCHRECK, 2014. Uncertainty Visualization for Crisis Management in Smart Grid Environments. GIScience 2014 : Eighth International Conference on Geographic Information Science. Vienna, 23. Sep 2014 - 26. Sep 2014. In: GIScience 2014 : Eighth International Conference on Geographic Information Science ; Workshop on Visually-Supported Reasoning with Uncertainty. GIScience 2014 : Eighth International Conference on Geographic Information Science. Vienna, 23. Sep 2014 - 26. Sep 2014

@inproceedings{Senaratne2014Uncer-30246, title={Uncertainty Visualization for Crisis Management in Smart Grid Environments}, year={2014}, booktitle={GIScience 2014 : Eighth International Conference on Geographic Information Science ; Workshop on Visually-Supported Reasoning with Uncertainty}, author={Senaratne, Hansi and Mittelstädt, Sebastian and Jacob, Christine and Schreck, Tobias} }

<rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:bibo="http://purl.org/ontology/bibo/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:dcterms="http://purl.org/dc/terms/" xmlns:xsd="http://www.w3.org/2001/XMLSchema#" > <rdf:Description rdf:about="https://kops.uni-konstanz.de/rdf/resource/123456789/30246"> <dcterms:issued>2014</dcterms:issued> <dc:contributor>Schreck, Tobias</dc:contributor> <bibo:uri rdf:resource="http://kops.uni-konstanz.de/handle/123456789/30246"/> <dc:creator>Senaratne, Hansi</dc:creator> <dc:contributor>Senaratne, Hansi</dc:contributor> <dc:contributor>Mittelstädt, Sebastian</dc:contributor> <dc:creator>Mittelstädt, Sebastian</dc:creator> <dc:language>eng</dc:language> <dc:contributor>Jacob, Christine</dc:contributor> <dc:date rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2015-03-12T14:54:10Z</dc:date> <dc:creator>Jacob, Christine</dc:creator> <dcterms:abstract xml:lang="eng">Visual analytics systems are in place within smart grid environments to alleviate crisis situations by allowing decision makers to perceive and understand the severity of a crisis situation. However, errors in measurements that are propagated due to various reasons (such as data transformations, errors in measurement devices etc.) can make the decision makers less confident in deriving information. Therefore, analysis and visualization of uncertainty within such data has become important. In this paper we utilize two uncertainty propagation techniques: sampling and Monte Carlo simulation, to propagate uncertainties inherent in power data within our smart grid environment, and compare their performance to best fit our use-case.We found that the Monte Carlo simulation methodis most suitable for measuring uncertainty in our application domain. Further, we identified most effective visual metaphors to communicate uncertainty to the crisis managers.</dcterms:abstract> <dcterms:title>Uncertainty Visualization for Crisis Management in Smart Grid Environments</dcterms:title> <dcterms:available rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2015-03-12T14:54:10Z</dcterms:available> <dc:creator>Schreck, Tobias</dc:creator> </rdf:Description> </rdf:RDF>

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