Publikation:

RescueMark : Visual Analytics of Social Media Data for Guiding Emergency Response in Disaster Situations Award for Skillful Integration of Language Model

Lade...
Vorschaubild

Dateien

Jeitler_2-y97wz7grp4sv4.pdf
Jeitler_2-y97wz7grp4sv4.pdfGröße: 625.92 KBDownloads: 516

Datum

2019

Herausgeber:innen

Kontakt

ISSN der Zeitschrift

Electronic ISSN

ISBN

Bibliografische Daten

Verlag

Schriftenreihe

Auflagebezeichnung

ArXiv-ID

Internationale Patentnummer

Angaben zur Forschungsförderung

Projekt

Open Access-Veröffentlichung
Open Access Green
Core Facility der Universität Konstanz

Gesperrt bis

Titel in einer weiteren Sprache

Publikationstyp
Beitrag zu einem Konferenzband
Publikationsstatus
Published

Erschienen in

CHANG, Remco, ed., Daniel A. KEIM, ed., Ross MACIEJEWSKI, ed.. 2019 IEEE Conference on Visual Analytics Science and Technology (VAST) : Proceedings. Piscataway, NJ: IEEE, 2019, pp. 120-121. ISBN 978-1-72812-284-7. Available under: doi: 10.1109/VAST47406.2019.8986898

Zusammenfassung

This paper presents RescueMark, a web-based visual analytics tool for analyzing disaster situations and guiding emergency response. In disaster situations operators must take quick and effective decisions to solve critical problems. RescueMark provides spatial, topic and temporal event exploration supporting decision making for resource allocation and determine damaged areas of the city. We describe the data analysis and visualization process of the social media data applied to extract the relevant information.

Zusammenfassung in einer weiteren Sprache

Fachgebiet (DDC)
004 Informatik

Schlagwörter

Human-centered computing, Visualization, Visualization application domains, Visual analytics

Konferenz

2019 IEEE Conference on Visual Analytics Science and Technology (VAST), 20. Okt. 2019 - 25. Okt. 2019, Vancouver, BC, Canada
Rezension
undefined / . - undefined, undefined

Forschungsvorhaben

Organisationseinheiten

Zeitschriftenheft

Zugehörige Datensätze in KOPS

Zitieren

ISO 690JEITLER, Astrik Veronika, Alpin TÜRKOGLU, Denis MAKAROV, Timo JOCKERS, Juri F. BUCHMÜLLER, Udo SCHLEGEL, Daniel A. KEIM, 2019. RescueMark : Visual Analytics of Social Media Data for Guiding Emergency Response in Disaster Situations Award for Skillful Integration of Language Model. 2019 IEEE Conference on Visual Analytics Science and Technology (VAST). Vancouver, BC, Canada, 20. Okt. 2019 - 25. Okt. 2019. In: CHANG, Remco, ed., Daniel A. KEIM, ed., Ross MACIEJEWSKI, ed.. 2019 IEEE Conference on Visual Analytics Science and Technology (VAST) : Proceedings. Piscataway, NJ: IEEE, 2019, pp. 120-121. ISBN 978-1-72812-284-7. Available under: doi: 10.1109/VAST47406.2019.8986898
BibTex
@inproceedings{Jeitler2019Rescu-50585,
  year={2019},
  doi={10.1109/VAST47406.2019.8986898},
  title={RescueMark : Visual Analytics of Social Media Data for Guiding Emergency Response in Disaster Situations Award for Skillful Integration of Language Model},
  isbn={978-1-72812-284-7},
  publisher={IEEE},
  address={Piscataway, NJ},
  booktitle={2019 IEEE Conference on Visual Analytics Science and Technology (VAST) : Proceedings},
  pages={120--121},
  editor={Chang, Remco and Keim, Daniel A. and Maciejewski, Ross},
  author={Jeitler, Astrik Veronika and Türkoglu, Alpin and Makarov, Denis and Jockers, Timo and Buchmüller, Juri F. and Schlegel, Udo and Keim, Daniel A.}
}
RDF
<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/server/rdf/resource/123456789/50585">
    <dc:creator>Türkoglu, Alpin</dc:creator>
    <dc:date rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2020-08-27T07:43:10Z</dc:date>
    <dc:creator>Makarov, Denis</dc:creator>
    <dc:language>eng</dc:language>
    <dc:creator>Keim, Daniel A.</dc:creator>
    <dc:contributor>Jeitler, Astrik Veronika</dc:contributor>
    <dc:contributor>Keim, Daniel A.</dc:contributor>
    <void:sparqlEndpoint rdf:resource="http://localhost/fuseki/dspace/sparql"/>
    <dspace:isPartOfCollection rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/36"/>
    <dc:rights>terms-of-use</dc:rights>
    <dcterms:abstract xml:lang="eng">This paper presents RescueMark, a web-based visual analytics tool for analyzing disaster situations and guiding emergency response. In disaster situations operators must take quick and effective decisions to solve critical problems. RescueMark provides spatial, topic and temporal event exploration supporting decision making for resource allocation and determine damaged areas of the city. We describe the data analysis and visualization process of the social media data applied to extract the relevant information.</dcterms:abstract>
    <dcterms:issued>2019</dcterms:issued>
    <dc:contributor>Türkoglu, Alpin</dc:contributor>
    <dspace:hasBitstream rdf:resource="https://kops.uni-konstanz.de/bitstream/123456789/50585/1/Jeitler_2-y97wz7grp4sv4.pdf"/>
    <dcterms:title>RescueMark : Visual Analytics of Social Media Data for Guiding Emergency Response in Disaster Situations Award for Skillful Integration of Language Model</dcterms:title>
    <dc:creator>Buchmüller, Juri F.</dc:creator>
    <dc:contributor>Buchmüller, Juri F.</dc:contributor>
    <dc:creator>Jeitler, Astrik Veronika</dc:creator>
    <dcterms:available rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2020-08-27T07:43:10Z</dcterms:available>
    <dcterms:hasPart rdf:resource="https://kops.uni-konstanz.de/bitstream/123456789/50585/1/Jeitler_2-y97wz7grp4sv4.pdf"/>
    <dcterms:isPartOf rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/36"/>
    <foaf:homepage rdf:resource="http://localhost:8080/"/>
    <bibo:uri rdf:resource="https://kops.uni-konstanz.de/handle/123456789/50585"/>
    <dcterms:rights rdf:resource="https://rightsstatements.org/page/InC/1.0/"/>
    <dc:contributor>Makarov, Denis</dc:contributor>
    <dc:contributor>Schlegel, Udo</dc:contributor>
    <dc:creator>Schlegel, Udo</dc:creator>
    <dc:creator>Jockers, Timo</dc:creator>
    <dc:contributor>Jockers, Timo</dc:contributor>
  </rdf:Description>
</rdf:RDF>

Interner Vermerk

xmlui.Submission.submit.DescribeStep.inputForms.label.kops_note_fromSubmitter

Kontakt
URL der Originalveröffentl.

Prüfdatum der URL

Prüfungsdatum der Dissertation

Finanzierungsart

Kommentar zur Publikation

Allianzlizenz
Corresponding Authors der Uni Konstanz vorhanden
Internationale Co-Autor:innen
Universitätsbibliographie
Ja
Begutachtet
Diese Publikation teilen