Publikation:

Assessing 2D and 3D Heatmaps for Comparative Analysis : An Empirical Study

Lade...
Vorschaubild

Dateien

Kraus_2-1x6gz2rwuh45i0.pdf
Kraus_2-1x6gz2rwuh45i0.pdfGröße: 770.64 KBDownloads: 1474

Datum

2020

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

CHI '20: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems. New York, NY: ACM, 2020, 546. ISBN 978-1-4503-6708-0. Available under: doi: 10.1145/3313831.3376675

Zusammenfassung

Heatmaps are a popular visualization technique that encode 2D density distributions using color or brightness. Experimental studies have shown though that both of these visual variables are inaccurate when reading and comparing numeric data values. A potential remedy might be to use 3D heatmaps by introducing height as a third dimension to encode the data. Encoding abstract data in 3D, however, poses many problems, too. To better understand this tradeoff, we conducted an empirical study (N=48) to evaluate the user performance of 2D and 3D heatmaps for comparative analysis tasks. We test our conditions on a conventional 2D screen, but also in a virtual reality environment to allow for real stereoscopic vision. Our main results show that 3D heatmaps are superior in terms of error rate when reading and comparing single data items. However, for overview tasks, the well-established 2D heatmap performs better.

Zusammenfassung in einer weiteren Sprache

Fachgebiet (DDC)
004 Informatik

Schlagwörter

virtual reality; visual analytics; heatmaps

Konferenz

2020 CHI Conference on Human Factors in Computing Systems : CHI '20, 25. Apr. 2020 - 30. Apr. 2020, Honolulu
Rezension
undefined / . - undefined, undefined

Forschungsvorhaben

Organisationseinheiten

Zeitschriftenheft

Zugehörige Datensätze in KOPS

Zitieren

ISO 690KRAUS, Matthias, Katrin ANGERBAUER, Juri F. BUCHMÜLLER, Daniel SCHWEITZER, Daniel A. KEIM, Michael SEDLMAIR, Johannes FUCHS, 2020. Assessing 2D and 3D Heatmaps for Comparative Analysis : An Empirical Study. 2020 CHI Conference on Human Factors in Computing Systems : CHI '20. Honolulu, 25. Apr. 2020 - 30. Apr. 2020. In: CHI '20: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems. New York, NY: ACM, 2020, 546. ISBN 978-1-4503-6708-0. Available under: doi: 10.1145/3313831.3376675
BibTex
@inproceedings{Kraus2020Asses-49555,
  year={2020},
  doi={10.1145/3313831.3376675},
  title={Assessing 2D and 3D Heatmaps for Comparative Analysis : An Empirical Study},
  isbn={978-1-4503-6708-0},
  publisher={ACM},
  address={New York, NY},
  booktitle={CHI '20: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems},
  author={Kraus, Matthias and Angerbauer, Katrin and Buchmüller, Juri F. and Schweitzer, Daniel and Keim, Daniel A. and Sedlmair, Michael and Fuchs, Johannes},
  note={Article Number: 546}
}
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/123456789/49555">
    <dcterms:isPartOf rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/36"/>
    <dcterms:title>Assessing 2D and 3D Heatmaps for Comparative Analysis : An Empirical Study</dcterms:title>
    <dc:contributor>Schweitzer, Daniel</dc:contributor>
    <dc:creator>Kraus, Matthias</dc:creator>
    <dc:contributor>Sedlmair, Michael</dc:contributor>
    <dc:contributor>Buchmüller, Juri F.</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:contributor>Keim, Daniel A.</dc:contributor>
    <dc:creator>Keim, Daniel A.</dc:creator>
    <dc:creator>Buchmüller, Juri F.</dc:creator>
    <dc:creator>Angerbauer, Katrin</dc:creator>
    <dcterms:abstract xml:lang="eng">Heatmaps are a popular visualization technique that encode 2D density distributions using color or brightness. Experimental studies have shown though that both of these visual variables are inaccurate when reading and comparing numeric data values. A potential remedy might be to use 3D heatmaps by introducing height as a third dimension to encode the data. Encoding abstract data in 3D, however, poses many problems, too. To better understand this tradeoff, we conducted an empirical study (N=48) to evaluate the user performance of 2D and 3D heatmaps for comparative analysis tasks. We test our conditions on a conventional 2D screen, but also in a virtual reality environment to allow for real stereoscopic vision. Our main results show that 3D heatmaps are superior in terms of error rate when reading and comparing single data items. However, for overview tasks, the well-established 2D heatmap performs better.</dcterms:abstract>
    <dcterms:hasPart rdf:resource="https://kops.uni-konstanz.de/bitstream/123456789/49555/1/Kraus_2-1x6gz2rwuh45i0.pdf"/>
    <dc:creator>Schweitzer, Daniel</dc:creator>
    <dcterms:rights rdf:resource="https://rightsstatements.org/page/InC/1.0/"/>
    <dc:rights>terms-of-use</dc:rights>
    <dc:contributor>Angerbauer, Katrin</dc:contributor>
    <dspace:hasBitstream rdf:resource="https://kops.uni-konstanz.de/bitstream/123456789/49555/1/Kraus_2-1x6gz2rwuh45i0.pdf"/>
    <dc:creator>Sedlmair, Michael</dc:creator>
    <dc:contributor>Kraus, Matthias</dc:contributor>
    <foaf:homepage rdf:resource="http://localhost:8080/"/>
    <bibo:uri rdf:resource="https://kops.uni-konstanz.de/handle/123456789/49555"/>
    <dcterms:available rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2020-05-18T15:06:06Z</dcterms:available>
    <dcterms:issued>2020</dcterms:issued>
    <dc:date rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2020-05-18T15:06:06Z</dc:date>
    <dc:language>eng</dc:language>
    <dc:creator>Fuchs, Johannes</dc:creator>
    <dc:contributor>Fuchs, Johannes</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