A conceptual framework and taxonomy of techniques for analyzing movement

Lade...
Vorschaubild
Dateien
Andrienko_190896.pdf
Andrienko_190896.pdfGröße: 453.35 KBDownloads: 371
Datum
2011
Autor:innen
Andrienko, Gennady
Andrienko, Nathaliya
Wrobel, Stefan
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
Forschungsvorhaben
Organisationseinheiten
Zeitschriftenheft
Publikationstyp
Zeitschriftenartikel
Publikationsstatus
Published
Erschienen in
Journal of Visual Languages & Computing. 2011, 22(3), pp. 213-232. ISSN 1045-926X. Available under: doi: 10.1016/j.jvlc.2011.02.003
Zusammenfassung

Movement data link together space, time, and objects positioned in space and time. They hold valuable and multifaceted information about moving objects, properties of space and time as well as events and processes occurring in space and time. We present a conceptual framework that describes in a systematic and comprehensive way the possible types of information that can be extracted from movement data and on this basis defines the respective types of analytical tasks. Tasks are distinguished according to the type of information they target and according to the level of analysis, which may be elementary (i.e. addressing specific elements of a set) or synoptic (i.e. addressing a set or subsets). We also present a taxonomy of generic analytic techniques, in which the types of tasks are linked to the corresponding classes of techniques that can support fulfilling them. We include techniques from several research fields: visualization and visual analytics, geographic information science, database technology, and data mining.
We expect the taxonomy to be valuable for analysts and researchers. Analysts will receive guidance in choosing suitable analytic techniques for their data and tasks. Researchers will learn what approaches exist in different fields and compare or relate them to the approaches they are going to undertake.

Zusammenfassung in einer weiteren Sprache
Fachgebiet (DDC)
004 Informatik
Schlagwörter
Moving object, Trajectory, Movement data, Visual analytics
Konferenz
Rezension
undefined / . - undefined, undefined
Zitieren
ISO 690ANDRIENKO, Gennady, Nathaliya ANDRIENKO, Peter BAK, Daniel A. KEIM, Slava KISILEVICH, Stefan WROBEL, 2011. A conceptual framework and taxonomy of techniques for analyzing movement. In: Journal of Visual Languages & Computing. 2011, 22(3), pp. 213-232. ISSN 1045-926X. Available under: doi: 10.1016/j.jvlc.2011.02.003
BibTex
@article{Andrienko2011conce-19089,
  year={2011},
  doi={10.1016/j.jvlc.2011.02.003},
  title={A conceptual framework and taxonomy of techniques for analyzing movement},
  number={3},
  volume={22},
  issn={1045-926X},
  journal={Journal of Visual Languages & Computing},
  pages={213--232},
  author={Andrienko, Gennady and Andrienko, Nathaliya and Bak, Peter and Keim, Daniel A. and Kisilevich, Slava and Wrobel, Stefan}
}
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/123456789/19089">
    <dcterms:isPartOf rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/36"/>
    <dcterms:title>A conceptual framework and taxonomy of techniques for analyzing movement</dcterms:title>
    <dc:creator>Kisilevich, Slava</dc:creator>
    <dc:creator>Keim, Daniel A.</dc:creator>
    <dcterms:available rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2012-04-19T13:28:45Z</dcterms:available>
    <dcterms:bibliographicCitation>Publ. in: Journal of Visual Languages &amp; Computing ; 22 (2011), 3. - pp. 213-232</dcterms:bibliographicCitation>
    <dcterms:issued>2011</dcterms:issued>
    <dc:contributor>Andrienko, Gennady</dc:contributor>
    <dspace:hasBitstream rdf:resource="https://kops.uni-konstanz.de/bitstream/123456789/19089/2/Andrienko_190896.pdf"/>
    <dcterms:abstract xml:lang="eng">Movement data link together space, time, and objects positioned in space and time. They hold valuable and multifaceted information about moving objects, properties of space and time as well as events and processes occurring in space and time. We present a conceptual framework that describes in a systematic and comprehensive way the possible types of information that can be extracted from movement data and on this basis defines the respective types of analytical tasks. Tasks are distinguished according to the type of information they target and according to the level of analysis, which may be elementary (i.e. addressing specific elements of a set) or synoptic (i.e. addressing a set or subsets). We also present a taxonomy of generic analytic techniques, in which the types of tasks are linked to the corresponding classes of techniques that can support fulfilling them. We include techniques from several research fields: visualization and visual analytics, geographic information science, database technology, and data mining.&lt;br /&gt;We expect the taxonomy to be valuable for analysts and researchers. Analysts will receive guidance in choosing suitable analytic techniques for their data and tasks. Researchers will learn what approaches exist in different fields and compare or relate them to the approaches they are going to undertake.</dcterms:abstract>
    <dc:creator>Bak, Peter</dc:creator>
    <void:sparqlEndpoint rdf:resource="http://localhost/fuseki/dspace/sparql"/>
    <dcterms:hasPart rdf:resource="https://kops.uni-konstanz.de/bitstream/123456789/19089/2/Andrienko_190896.pdf"/>
    <dc:contributor>Kisilevich, Slava</dc:contributor>
    <foaf:homepage rdf:resource="http://localhost:8080/"/>
    <dspace:isPartOfCollection rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/36"/>
    <dcterms:rights rdf:resource="https://rightsstatements.org/page/InC/1.0/"/>
    <dc:contributor>Wrobel, Stefan</dc:contributor>
    <dc:language>eng</dc:language>
    <dc:contributor>Bak, Peter</dc:contributor>
    <bibo:uri rdf:resource="http://kops.uni-konstanz.de/handle/123456789/19089"/>
    <dc:contributor>Andrienko, Nathaliya</dc:contributor>
    <dc:contributor>Keim, Daniel A.</dc:contributor>
    <dc:creator>Andrienko, Gennady</dc:creator>
    <dc:creator>Andrienko, Nathaliya</dc:creator>
    <dc:rights>terms-of-use</dc:rights>
    <dc:creator>Wrobel, Stefan</dc:creator>
    <dc:date rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2012-04-19T13:28:45Z</dc:date>
  </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