Quality Metrics for Information Visualization

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BEHRISCH, Michael, Michael BLUMENSCHEIN, Naam Wook KIM, Mennatallah EL-ASSADY, Johannes FUCHS, Daniel SEEBACHER, Alexandra DIEHL, Ulrik BRANDES, Tobias SCHRECK, Daniel WEISKOPF, Daniel A. KEIM, 2018. Quality Metrics for Information Visualization. In: Computer Graphics Forum. 37(3), pp. 625-662. ISSN 0167-7055. eISSN 1467-8659. Available under: doi: 10.1111/cgf.13446

@article{Behrisch2018Quali-42964, title={Quality Metrics for Information Visualization}, year={2018}, doi={10.1111/cgf.13446}, number={3}, volume={37}, issn={0167-7055}, journal={Computer Graphics Forum}, pages={625--662}, author={Behrisch, Michael and Blumenschein, Michael and Kim, Naam Wook and El-Assady, Mennatallah and Fuchs, Johannes and Seebacher, Daniel and Diehl, Alexandra and Brandes, Ulrik and Schreck, Tobias and Weiskopf, Daniel and Keim, Daniel A.} }

<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/rdf/resource/123456789/42964"> <dc:contributor>Schreck, Tobias</dc:contributor> <dspace:hasBitstream rdf:resource="https://kops.uni-konstanz.de/bitstream/123456789/42964/1/Behrisch_2-1e2yy07dt4l3k9.pdf"/> <dcterms:issued>2018</dcterms:issued> <dc:creator>Kim, Naam Wook</dc:creator> <void:sparqlEndpoint rdf:resource="http://localhost/fuseki/dspace/sparql"/> <dc:creator>Behrisch, Michael</dc:creator> <dc:contributor>Diehl, Alexandra</dc:contributor> <dcterms:rights rdf:resource="https://rightsstatements.org/page/InC/1.0/"/> <dc:creator>Fuchs, Johannes</dc:creator> <foaf:homepage rdf:resource="http://localhost:8080/jspui"/> <dc:contributor>Brandes, Ulrik</dc:contributor> <dc:creator>Weiskopf, Daniel</dc:creator> <dc:creator>Keim, Daniel A.</dc:creator> <dc:contributor>Fuchs, Johannes</dc:contributor> <dcterms:hasPart rdf:resource="https://kops.uni-konstanz.de/bitstream/123456789/42964/1/Behrisch_2-1e2yy07dt4l3k9.pdf"/> <dc:contributor>Behrisch, Michael</dc:contributor> <dc:contributor>Weiskopf, Daniel</dc:contributor> <dc:creator>Seebacher, Daniel</dc:creator> <bibo:uri rdf:resource="https://kops.uni-konstanz.de/handle/123456789/42964"/> <dc:language>eng</dc:language> <dc:contributor>Keim, Daniel A.</dc:contributor> <dc:creator>Blumenschein, Michael</dc:creator> <dc:contributor>Blumenschein, Michael</dc:contributor> <dspace:isPartOfCollection rdf:resource="https://kops.uni-konstanz.de/rdf/resource/123456789/36"/> <dcterms:title>Quality Metrics for Information Visualization</dcterms:title> <dcterms:isPartOf rdf:resource="https://kops.uni-konstanz.de/rdf/resource/123456789/36"/> <dcterms:available rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2018-08-06T09:41:19Z</dcterms:available> <dc:contributor>Seebacher, Daniel</dc:contributor> <dc:creator>Diehl, Alexandra</dc:creator> <dc:contributor>El-Assady, Mennatallah</dc:contributor> <dc:contributor>Kim, Naam Wook</dc:contributor> <dc:creator>Brandes, Ulrik</dc:creator> <dc:rights>terms-of-use</dc:rights> <dcterms:abstract xml:lang="eng">The visualization community has developed to date many intuitions and understandings of how to judge the quality of views in visualizing data. The computation of a visualization’s quality and usefulness ranges from measuring clutter and overlap, up to the existence and perception of specific (visual) patterns. This survey attempts to report, categorize and unify the diverse understandings and aims to establish a common vocabulary that will enable a wide audience to understand their differences and subtleties. For this purpose, we present a commonly applicable quality metric formalization that should detail and relate all constituting parts of a quality metric. We organize our corpus of reviewed research papers along the data types established in the information visualization community: multi- and high-dimensional, relational, sequential, geospatial and text data. For each data type, we select the visualization subdomains in which quality metrics are an active research field and report their findings, reason on the underlying concepts, describe goals and outline the constraints and requirements. One central goal of this survey is to provide guidance on future research opportunities for the field and outline how different visualization communities could benefit from each other by applying or transferring knowledge to their respective subdomain. Additionally, we aim to motivate the visualization community to compare computed measures to the perception of humans.</dcterms:abstract> <dc:creator>El-Assady, Mennatallah</dc:creator> <dc:date rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2018-08-06T09:41:19Z</dc:date> <dc:creator>Schreck, Tobias</dc:creator> </rdf:Description> </rdf:RDF>

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