A Visual Analysis of Multi-Attribute Data Using Pixel Matrix Displays

Lade...
Vorschaubild
Dateien
vda07ming.pdf
vda07ming.pdfGröße: 345.93 KBDownloads: 496
Datum
2007
Autor:innen
Hao, Ming C.
Dayal, Umeshwar
Herausgeber:innen
Kontakt
ISSN der Zeitschrift
Electronic ISSN
ISBN
Bibliografische Daten
Verlag
Schriftenreihe
Auflagebezeichnung
DOI (zitierfähiger Link)
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
Beitrag zu einem Konferenzband
Publikationsstatus
Published
Erschienen in
ERBACHER, Robert F., ed., Jonathan C. ROBERTS, ed., Matti T. GRÖHN, ed., Katy BÖRNER, ed.. Visualization and Data Analysis 2007. SPIE, 2007, 649505. SPIE Proceedings. 6495. Available under: doi: 10.1117/12.706151
Zusammenfassung

Charts and tables are commonly used to visually analyze data. These graphics are simple and easy to understand, but charts show only highly aggregated data and present only a limited number of data values while tables often show too many data values. As a consequence, these graphics may either lose or obscure important information, so different techniques are required to monitor complex datasets. Users need more powerful visualization techniques to digest and compare detailed multi-attribute information to analyze the health of their business. This paper proposes an innovative solution based on the use of pixel-matrix to represent transaction-level information within graphics. With pixel-matrixes, users can visualize areas of importance at a glance, a capability not provided by common charting techniques. Our solutions are based on colored pixel-matrixes, which are used in (1) charts for visualizing data patterns and discovering exceptions, (2) tables for visualizing correlations and finding root-causes, and (3) time series for visualizing the evolution of long-running transactions. The solutions have been applied with success to product sales, Internet network performance analysis, and service contract applications demonstrating the benefits of our method over conventional graphics. The method is especially useful when detailed information is a key part of the analysis.

Zusammenfassung in einer weiteren Sprache
Fachgebiet (DDC)
004 Informatik
Schlagwörter
pixel-matrix visualization, multi-attribute dataset, bar charts, tables, time series
Konferenz
Electronic Imaging 2007, San Jose, CA
Rezension
undefined / . - undefined, undefined
Zitieren
ISO 690HAO, Ming C., Umeshwar DAYAL, Daniel A. KEIM, Tobias SCHRECK, 2007. A Visual Analysis of Multi-Attribute Data Using Pixel Matrix Displays. Electronic Imaging 2007. San Jose, CA. In: ERBACHER, Robert F., ed., Jonathan C. ROBERTS, ed., Matti T. GRÖHN, ed., Katy BÖRNER, ed.. Visualization and Data Analysis 2007. SPIE, 2007, 649505. SPIE Proceedings. 6495. Available under: doi: 10.1117/12.706151
BibTex
@inproceedings{Hao2007-01-28Visua-5468,
  year={2007},
  doi={10.1117/12.706151},
  title={A Visual Analysis of Multi-Attribute Data Using Pixel Matrix Displays},
  number={6495},
  publisher={SPIE},
  series={SPIE Proceedings},
  booktitle={Visualization and Data Analysis 2007},
  editor={Erbacher, Robert F. and Roberts, Jonathan C. and Gröhn, Matti T. and Börner, Katy},
  author={Hao, Ming C. and Dayal, Umeshwar and Keim, Daniel A. and Schreck, Tobias},
  note={Article Number: 649505}
}
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/123456789/5468">
    <dc:format>application/pdf</dc:format>
    <dcterms:rights rdf:resource="https://rightsstatements.org/page/InC/1.0/"/>
    <dcterms:title>A Visual Analysis of Multi-Attribute Data Using Pixel Matrix Displays</dcterms:title>
    <dc:contributor>Dayal, Umeshwar</dc:contributor>
    <dcterms:abstract xml:lang="eng">Charts and tables are commonly used to visually analyze data. These graphics are simple and easy to understand, but charts show only highly aggregated data and present only a limited number of data values while tables often show too many data values. As a consequence, these graphics may either lose or obscure important information, so different techniques are required to monitor complex datasets. Users need more powerful visualization techniques to digest and compare detailed multi-attribute information to analyze the health of their business. This paper proposes an innovative solution based on the use of pixel-matrix to represent transaction-level information within graphics. With pixel-matrixes, users can visualize areas of importance at a glance, a capability not provided by common charting techniques. Our solutions are based on colored pixel-matrixes, which are used in (1) charts for visualizing data patterns and discovering exceptions, (2) tables for visualizing correlations and finding root-causes, and (3) time series for visualizing the evolution of long-running transactions. The solutions have been applied with success to product sales, Internet network performance analysis, and service contract applications demonstrating the benefits of our method over conventional graphics. The method is especially useful when detailed information is a key part of the analysis.</dcterms:abstract>
    <dcterms:available rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2011-03-24T15:55:38Z</dcterms:available>
    <dc:creator>Schreck, Tobias</dc:creator>
    <dcterms:isPartOf rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/36"/>
    <dc:creator>Hao, Ming C.</dc:creator>
    <dcterms:hasPart rdf:resource="https://kops.uni-konstanz.de/bitstream/123456789/5468/1/vda07ming.pdf"/>
    <void:sparqlEndpoint rdf:resource="http://localhost/fuseki/dspace/sparql"/>
    <dspace:hasBitstream rdf:resource="https://kops.uni-konstanz.de/bitstream/123456789/5468/1/vda07ming.pdf"/>
    <dc:contributor>Keim, Daniel A.</dc:contributor>
    <dcterms:bibliographicCitation>Paper for: IS&amp;T/SPIE Conference on Visualization and Data Analysis (VDA 2007), January 28th - February 1st, 2007, San Jose, Ca, USA, 2007</dcterms:bibliographicCitation>
    <dcterms:issued>2007-01-28</dcterms:issued>
    <foaf:homepage rdf:resource="http://localhost:8080/"/>
    <dc:contributor>Hao, Ming C.</dc:contributor>
    <dc:language>eng</dc:language>
    <dc:creator>Keim, Daniel A.</dc:creator>
    <dc:contributor>Schreck, Tobias</dc:contributor>
    <dc:date rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2011-03-24T15:55:38Z</dc:date>
    <dc:creator>Dayal, Umeshwar</dc:creator>
    <dc:rights>terms-of-use</dc:rights>
    <bibo:uri rdf:resource="http://kops.uni-konstanz.de/handle/123456789/5468"/>
    <dspace:isPartOfCollection rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/36"/>
  </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