Datensatz:

"Research Data Curation in Visualization : Position Paper" (Data)

Lade...
Vorschaubild

Datum der Erstveröffentlichung

2022

Autor:innen

Müller, Christoph
Braun, Matthias
Weiskopf, Daniel

Andere Beitragende

Repositorium der Erstveröffentlichung

Universitätsbibliothek Stuttgart

Version des Datensatzes

1.3
Link zur Lizenz

Angaben zur Forschungsförderung

Deutsche Forschungsgemeinschaft (DFG): 251654672
Deutsche Forschungsgemeinschaft (DFG): EXC 2120/1 - 390831618

Projekt

Core Facility der Universität Konstanz
Bewerten Sie die FAIRness der Forschungsdaten

Gesperrt bis

Titel in einer weiteren Sprache

Publikationsstatus
Published

Zusammenfassung

Here, we make available the supplemental material regarding data collection from the publicaiton "Research Data Curation in Visualization : Position Paper". The dataset represents an aggregated collection of the data policies of selected publication venues in the areas of visualization, computer graphics, software, HCI, and Virtual Reality with inclusions from multimedia, collaboration, and network visualization, for the years 2021-2022. Based on a derived index, long-term preservation and data sharing are evaluated for each venue. The index ranges from No policy to Required sharing and preservation. Additionally the verbatim statements (or the lack thereof) used to reach the concluded score are also provided. Abstract: Research data curation is the act of carefully preparing research data and artifacts for sharing and long-term preservation. Research data management is centrally implemented and formally defined in a data management plan to enable data curation. In tandem, data curation and management facilitate research repeatability. In contrast to other research fields, data curation and management in visualization are not yet part of the researcher’s compendium. In this position paper, we discuss the unique challenges visualization faces and propose how data curation can be practically realized. We share eight lessons learned in managing data in two large research consortia, outline the larger curation workflow, and define the typical roles. We complement our lessons with minimum criteria for selecting a suitable data repository and five challenging scenarios that occur in practice. We conclude with a vision of how the visualization research community can pave the way for new curation standards.

Zusammenfassung in einer weiteren Sprache

Fachgebiet (DDC)
004 Informatik

Schlagwörter

Computer and Information Science, Data Curation, Visualization, Research--Data Processing, Data Processing Service Centers--Management, Paper--Preservation, Digital Preservation, Reproducible Research, Replication (Experimental Design), Head-Mounted Displays, Virtual Reality Headsets

Zugehörige Publikationen in KOPS

Publikation
Beitrag zu einem Konferenzband
Research Data Curation in Visualization : Position Paper
(2022) Garkov, Dimitar; Müller, Christoph; Braun, Matthias; Weiskopf, Daniel; Schreiber, Falk
Erschienen in: 2022 IEEE 9th Workshop on Evaluation and Beyond : Methodological Approaches to Visualization, BELIV 2022, Proceedings. Piscataway, NJ: IEEE, 2022, S. 56-65. ISBN 979-8-3503-9629-4. Verfügbar unter: doi: 10.1109/BELIV57783.2022.00011
Link zu zugehöriger Publikation
Link zu zugehörigem Datensatz

Zitieren

ISO 690GARKOV, Dimitar, Christoph MÜLLER, Matthias BRAUN, Daniel WEISKOPF, Falk SCHREIBER, 2022. "Research Data Curation in Visualization : Position Paper" (Data)
BibTex
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/123456789/72892">
    <dcterms:relation>10.18419/darus-3144/2</dcterms:relation>
    <dc:contributor>Müller, Christoph</dc:contributor>
    <dcterms:hasPart>10.18419/darus-3144/1</dcterms:hasPart>
    <foaf:homepage rdf:resource="http://localhost:8080/"/>
    <dc:date rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2025-04-02T09:42:37Z</dc:date>
    <dc:creator>Garkov, Dimitar</dc:creator>
    <dc:creator>Braun, Matthias</dc:creator>
    <dspace:isPartOfCollection rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/71925"/>
    <dcterms:abstract>Here, we make available the supplemental material regarding data collection from the publicaiton "Research Data Curation in Visualization : Position Paper". The dataset represents an aggregated collection of the data policies of selected publication venues in the areas of visualization, computer graphics, software, HCI, and Virtual Reality with inclusions from multimedia, collaboration, and network visualization, for the years 2021-2022. Based on a derived index, long-term preservation and data sharing are evaluated for each venue. The index ranges from No policy to Required sharing and preservation. Additionally the verbatim statements (or the lack thereof) used to reach the concluded score are also provided.
Abstract: Research data curation is the act of carefully preparing research data and artifacts for sharing and long-term preservation. Research data management is centrally implemented and formally defined in a data management plan to enable data curation. In tandem, data curation and management facilitate research repeatability. In contrast to other research fields, data curation and management in visualization are not yet part of the researcher’s compendium. In this position paper, we discuss the unique challenges visualization faces and propose how data curation can be practically realized. We share eight lessons learned in managing data in two large research consortia, outline the larger curation workflow, and define the typical roles. We complement our lessons with minimum criteria for selecting a suitable data repository and five challenging scenarios that occur in practice. We conclude with a vision of how the visualization research community can pave the way for new curation standards.</dcterms:abstract>
    <dc:rights>Creative Commons Attribution 4.0 International</dc:rights>
    <dcterms:created rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2022-09-18T17:55:13.000Z</dcterms:created>
    <dc:creator>Schreiber, Falk</dc:creator>
    <dcterms:issued>2022</dcterms:issued>
    <dc:creator>Müller, Christoph</dc:creator>
    <dcterms:rights rdf:resource="https://creativecommons.org/licenses/by/4.0/legalcode"/>
    <dc:contributor>Weiskopf, Daniel</dc:contributor>
    <dcterms:title>"Research Data Curation in Visualization : Position Paper" (Data)</dcterms:title>
    <dcterms:relation>10.18419/darus-3144/1</dcterms:relation>
    <dc:contributor>Garkov, Dimitar</dc:contributor>
    <dc:contributor>Braun, Matthias</dc:contributor>
    <dcterms:hasPart>10.18419/darus-3144/2</dcterms:hasPart>
    <dcterms:isPartOf rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/71925"/>
    <bibo:uri rdf:resource="https://kops.uni-konstanz.de/handle/123456789/72892"/>
    <dc:contributor>Schreiber, Falk</dc:contributor>
    <void:sparqlEndpoint rdf:resource="http://localhost/fuseki/dspace/sparql"/>
    <dcterms:available rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2025-04-02T09:42:37Z</dcterms:available>
    <dc:language>eng</dc:language>
    <dc:creator>Weiskopf, Daniel</dc:creator>
  </rdf:Description>
</rdf:RDF>
URL (Link zu den Daten)

Prüfdatum der URL

Kommentar zur Publikation

Universitätsbibliographie
Ja
Diese Publikation teilen