Publikation:

Space-in-Time and Time-in-Space Self-Organizing Maps for Exploring Spatiotemporal Patterns

Lade...
Vorschaubild

Dateien

keim.pdf
keim.pdfGröße: 5.54 MBDownloads: 618

Datum

2010

Autor:innen

Andrienko, Gennady L.
Andrienko, Natalia
Bremm, S.
Landesberger, Tatiana von

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
Zeitschriftenartikel
Publikationsstatus
Published

Erschienen in

Computer Graphics Forum. 2010, 29(3), pp. 913-922. ISSN 0167-7055. Available under: doi: 10.1111/j.1467-8659.2009.01664.x

Zusammenfassung

Spatiotemporal data pose serious challenges to analysts in geographic and other domains. Owing to the complexity of the geospatial and temporal components, this kind of data cannot be analyzed by fully automatic methods but require the involvement of the human analyst's expertise. For a comprehensive analysis, the data need to be considered from two complementary perspectives: (1) as spatial distributions (situations) changing over time and (2) as profiles of local temporal variation distributed over space. In order to support the visual analysis of spatiotemporal data, we suggest a framework based on the “Self-Organizing Map” (SOM) method combined with a set of interactive visual tools supporting both analytic perspectives. SOM can be considered as a combination of clustering and dimensionality reduction. In the first perspective, SOM is applied to the spatial situations at different time moments or intervals. In the other perspective, SOM is applied to the local temporal evolution profiles. The integrated visual analytics environment includes interactive coordinated displays enabling various transformations of spatiotemporal data and post-processing of SOM results. The SOM matrix display offers an overview of the groupings of data objects and their two-dimensional arrangement by similarity. This view is linked to a cartographic map display, a time series graph, and a periodic pattern view. The linkage of these views supports the analysis of SOM results in both the spatial and temporal contexts. The variable SOM grid coloring serves as an instrument for linking the SOM with the corresponding items in the other displays. The framework has been validated on a large dataset with real city traffic data, where expected spatiotemporal patterns have been successfully uncovered. We also describe the use of the framework for discovery of previously unknown patterns in 41-years time series of 7 crime rate attributes in the states of the USA.

Zusammenfassung in einer weiteren Sprache

Fachgebiet (DDC)
004 Informatik

Schlagwörter

Information Visualization, Human information processing, Visual Analytics

Konferenz

Rezension
undefined / . - undefined, undefined

Forschungsvorhaben

Organisationseinheiten

Zeitschriftenheft

Zugehörige Datensätze in KOPS

Zitieren

ISO 690ANDRIENKO, Gennady L., Natalia ANDRIENKO, S. BREMM, Tobias SCHRECK, Tatiana von LANDESBERGER, Peter BAK, Daniel A. KEIM, 2010. Space-in-Time and Time-in-Space Self-Organizing Maps for Exploring Spatiotemporal Patterns. In: Computer Graphics Forum. 2010, 29(3), pp. 913-922. ISSN 0167-7055. Available under: doi: 10.1111/j.1467-8659.2009.01664.x
BibTex
@article{Andrienko2010Space-12645,
  year={2010},
  doi={10.1111/j.1467-8659.2009.01664.x},
  title={Space-in-Time and Time-in-Space Self-Organizing Maps for Exploring Spatiotemporal Patterns},
  number={3},
  volume={29},
  issn={0167-7055},
  journal={Computer Graphics Forum},
  pages={913--922},
  author={Andrienko, Gennady L. and Andrienko, Natalia and Bremm, S. and Schreck, Tobias and Landesberger, Tatiana von and Bak, Peter 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/123456789/12645">
    <dc:creator>Andrienko, Gennady L.</dc:creator>
    <foaf:homepage rdf:resource="http://localhost:8080/"/>
    <dc:creator>Schreck, Tobias</dc:creator>
    <dc:contributor>Bremm, S.</dc:contributor>
    <dcterms:abstract xml:lang="eng">Spatiotemporal data pose serious challenges to analysts in geographic and other domains. Owing to the complexity of the geospatial and temporal components, this kind of data cannot be analyzed by fully automatic methods but require the involvement of the human analyst's expertise. For a comprehensive analysis, the data need to be considered from two complementary perspectives: (1) as spatial distributions (situations) changing over time and (2) as profiles of local temporal variation distributed over space. In order to support the visual analysis of spatiotemporal data, we suggest a framework based on the “Self-Organizing Map” (SOM) method combined with a set of interactive visual tools supporting both analytic perspectives. SOM can be considered as a combination of clustering and dimensionality reduction. In the first perspective, SOM is applied to the spatial situations at different time moments or intervals. In the other perspective, SOM is applied to the local temporal evolution profiles. The integrated visual analytics environment includes interactive coordinated displays enabling various transformations of spatiotemporal data and post-processing of SOM results. The SOM matrix display offers an overview of the groupings of data objects and their two-dimensional arrangement by similarity. This view is linked to a cartographic map display, a time series graph, and a periodic pattern view. The linkage of these views supports the analysis of SOM results in both the spatial and temporal contexts. The variable SOM grid coloring serves as an instrument for linking the SOM with the corresponding items in the other displays. The framework has been validated on a large dataset with real city traffic data, where expected spatiotemporal patterns have been successfully uncovered. We also describe the use of the framework for discovery of previously unknown patterns in 41-years time series of 7 crime rate attributes in the states of the USA.</dcterms:abstract>
    <dc:creator>Andrienko, Natalia</dc:creator>
    <dcterms:bibliographicCitation>First publ. in: Computer Graphics Forum ; 29 (2010), 3. - S. 913-922</dcterms:bibliographicCitation>
    <void:sparqlEndpoint rdf:resource="http://localhost/fuseki/dspace/sparql"/>
    <dcterms:hasPart rdf:resource="https://kops.uni-konstanz.de/bitstream/123456789/12645/1/keim.pdf"/>
    <dspace:hasBitstream rdf:resource="https://kops.uni-konstanz.de/bitstream/123456789/12645/1/keim.pdf"/>
    <dc:rights>terms-of-use</dc:rights>
    <dc:contributor>Landesberger, Tatiana von</dc:contributor>
    <dc:language>eng</dc:language>
    <dc:contributor>Andrienko, Natalia</dc:contributor>
    <dcterms:isPartOf rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/36"/>
    <dc:contributor>Schreck, Tobias</dc:contributor>
    <dcterms:issued>2010</dcterms:issued>
    <dcterms:title>Space-in-Time and Time-in-Space Self-Organizing Maps for Exploring Spatiotemporal Patterns</dcterms:title>
    <dc:creator>Landesberger, Tatiana von</dc:creator>
    <dcterms:available rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2011-07-06T13:16:36Z</dcterms:available>
    <dcterms:rights rdf:resource="https://rightsstatements.org/page/InC/1.0/"/>
    <dc:creator>Bremm, S.</dc:creator>
    <dspace:isPartOfCollection rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/36"/>
    <dc:contributor>Andrienko, Gennady L.</dc:contributor>
    <dc:contributor>Bak, Peter</dc:contributor>
    <dc:date rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2011-07-06T13:16:36Z</dc:date>
    <dc:creator>Bak, Peter</dc:creator>
    <dc:creator>Keim, Daniel A.</dc:creator>
    <bibo:uri rdf:resource="http://kops.uni-konstanz.de/handle/123456789/12645"/>
    <dc:contributor>Keim, Daniel A.</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