Using visual analytics to support decision making to solve the Kronos incident (VAST challenge 2014)
| Type of Publication: | Contribution to a conference |
| URI (citable link): | http://nbn-resolving.de/urn:nbn:de:bsz:352-0-282560 |
| Author: | Fischer, Fabian; Stoffel, Florian; Mittelstädt, Sebastian; Schreck, Tobias; Keim, Daniel A. |
| Year of publication: | 2014 |
| Conference: | IEEE Conference on Visual Analytics Science and Technology (VAST), 2014, Oct 9, 2014 - Oct 14, 2014, Paris |
| Published in: | 2014 IEEE Conference on Visual Analytics Science and Technology (VAST) : Proceedings ; Paris, France, 9-14 October 2014 / Min Chen ... (ed.). - Piscataway, NJ : IEEE, 2014. - pp. 301-302. - ISBN 978-1-4799-6227-3 |
| DOI (citable link): | https://dx.doi.org/10.1109/VAST.2014.7042537 |
| Summary: |
Gaining insights from different heterogeneous data sources is one of the biggest challenges in decision making support. The large volumes of data can only be combined by sophisticated automatic methods. However, unexpected patterns can only be identified with the help of human intuition. In this paper, we present our visual analytics work-flows and tools to process heterogeneous data such as social networks, text streams, and geo-temporal data. We apply these tools on the VAST Challenge data and present our findings and assumptions that we identified in our analysis.
|
| Subject (DDC): | 004 Computer Science |
| Link to License: | In Copyright |
| Bibliography of Konstanz: | Yes |
Cite This
Files in this item
![[PDF]](/themes/Kops/images/mimes/pdf.png "PDF file"){kind=small}
FISCHER, Fabian, Florian STOFFEL, Sebastian MITTELSTÄDT, Tobias SCHRECK, Daniel A. KEIM, 2014. Using visual analytics to support decision making to solve the Kronos incident (VAST challenge 2014). IEEE Conference on Visual Analytics Science and Technology (VAST), 2014. Paris, Oct 9, 2014 - Oct 14, 2014. In: MIN CHEN ..., , ed.. 2014 IEEE Conference on Visual Analytics Science and Technology (VAST) : Proceedings ; Paris, France, 9-14 October 2014. Piscataway, NJ:IEEE, pp. 301-302. ISBN 978-1-4799-6227-3. Available under: doi: 10.1109/VAST.2014.7042537
@inproceedings{Fischer2014Using-30123, title={Using visual analytics to support decision making to solve the Kronos incident (VAST challenge 2014)}, year={2014}, doi={10.1109/VAST.2014.7042537}, isbn={978-1-4799-6227-3}, address={Piscataway, NJ}, publisher={IEEE}, booktitle={2014 IEEE Conference on Visual Analytics Science and Technology (VAST) : Proceedings ; Paris, France, 9-14 October 2014}, pages={301--302}, editor={Min Chen ...}, author={Fischer, Fabian and Stoffel, Florian and Mittelstädt, Sebastian and Schreck, Tobias and Keim, Daniel A.} }
<rdf:RDF xmlns:dcterms="http://purl.org/dc/terms/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:bibo="http://purl.org/ontology/bibo/" xmlns:dspace="http://digital-repositories.org/ontologies/dspace/0.1.0#" xmlns:foaf="http://xmlns.com/foaf/0.1/" xmlns:void="http://rdfs.org/ns/void#" xmlns:xsd="http://www.w3.org/2001/XMLSchema#" > <rdf:Description rdf:about="https://kops.uni-konstanz.de/rdf/resource/123456789/30123"> <dc:creator>Stoffel, Florian</dc:creator> <dc:rights>terms-of-use</dc:rights> <dc:creator>Schreck, Tobias</dc:creator> <dc:contributor>Mittelstädt, Sebastian</dc:contributor> <void:sparqlEndpoint rdf:resource="http://localhost/fuseki/dspace/sparql"/> <dcterms:issued>2014</dcterms:issued> <dspace:hasBitstream rdf:resource="https://kops.uni-konstanz.de/bitstream/123456789/30123/1/Fischer_0-282560.pdf"/> <bibo:uri rdf:resource="http://kops.uni-konstanz.de/handle/123456789/30123"/> <dspace:isPartOfCollection rdf:resource="https://kops.uni-konstanz.de/rdf/resource/123456789/36"/> <dc:creator>Fischer, Fabian</dc:creator> <dc:language>eng</dc:language> <dc:creator>Keim, Daniel A.</dc:creator> <dcterms:abstract xml:lang="eng">Gaining insights from different heterogeneous data sources is one of the biggest challenges in decision making support. The large volumes of data can only be combined by sophisticated automatic methods. However, unexpected patterns can only be identified with the help of human intuition. In this paper, we present our visual analytics work-flows and tools to process heterogeneous data such as social networks, text streams, and geo-temporal data. We apply these tools on the VAST Challenge data and present our findings and assumptions that we identified in our analysis.</dcterms:abstract> <dcterms:rights rdf:resource="https://rightsstatements.org/page/InC/1.0/"/> <dcterms:title>Using visual analytics to support decision making to solve the Kronos incident (VAST challenge 2014)</dcterms:title> <dc:contributor>Keim, Daniel A.</dc:contributor> <dc:contributor>Fischer, Fabian</dc:contributor> <dcterms:hasPart rdf:resource="https://kops.uni-konstanz.de/bitstream/123456789/30123/1/Fischer_0-282560.pdf"/> <dc:creator>Mittelstädt, Sebastian</dc:creator> <dc:contributor>Stoffel, Florian</dc:contributor> <dc:date rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2015-02-27T14:17:09Z</dc:date> <foaf:homepage rdf:resource="http://localhost:8080/jspui"/> <dc:contributor>Schreck, Tobias</dc:contributor> <dcterms:isPartOf rdf:resource="https://kops.uni-konstanz.de/rdf/resource/123456789/36"/> <dcterms:available rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2015-02-27T14:17:09Z</dcterms:available> </rdf:Description> </rdf:RDF>
Downloads since Feb 27, 2015 (Information about access statistics)
| Fischer_0-282560.pdf | 220 |
This item appears in the following Collection(s)
Search KOPS
Browse
My Account
