A Pragmatic Approach to Biases in Visual Data Analysis
A Pragmatic Approach to Biases in Visual Data Analysis
Date
2014
Authors
Verbeiren, Toni
Sakai, Ryo
Aerts, Jan
Editors
Journal ISSN
Electronic ISSN
ISBN
Bibliographical data
Publisher
Series
DECISIVe : Workshop on Dealing with Cognitive Biases in Visualisations
URI (citable link)
International patent number
Link to the license
EU project number
Project
Open Access publication
Collections
Title in another language
Publication type
Contribution to a conference collection
Publication status
Published
Published in
DECISIVe : Workshop on Dealing with Cognitive Biases in Visualisations / Ellis, Geoffrey (ed.)
Abstract
Visual biases and more generally cognitive biases are a part of human life. Often to the frustration of the rational decision makers we aspire to be. Research into these biases has sparked a recent burst in interest, and more and more people are aware of possible pitfalls. In this paper, we argue that the consequences of biases during data analysis have to be considered rather than the occurrences themselves. In applying this, we distinguish between (visual) analysis for exploration and validation. Especially the latter turns out to be hard in some cases, indicated by a qualitative measure we call validation cost. Examples are provided of situations with a high validation cost and the role of visualization is discussed in these cases. For cases with a low validation cost, we argue that biases leading to false positives are far better than trying to avoid biases and ending up with false negatives.
Summary in another language
Subject (DDC)
004 Computer Science
Keywords
Cognitive biases, Pattern Recognition, Problem Solving, Heuristics, Visual biases, Risk assessment
Conference
IEEE VIS 2014, Nov 9, 2014 - Nov 14, 2014, Paris, France
Review
undefined / . - undefined, undefined. - (undefined; undefined)
Cite This
ISO 690
VERBEIREN, Toni, Ryo SAKAI, Jan AERTS, 2014. A Pragmatic Approach to Biases in Visual Data Analysis. IEEE VIS 2014. Paris, France, Nov 9, 2014 - Nov 14, 2014. In: ELLIS, Geoffrey, ed.. DECISIVe : Workshop on Dealing with Cognitive Biases in VisualisationsBibTex
@inproceedings{Verbeiren2014Pragm-33726, year={2014}, title={A Pragmatic Approach to Biases in Visual Data Analysis}, booktitle={DECISIVe : Workshop on Dealing with Cognitive Biases in Visualisations}, editor={Ellis, Geoffrey}, author={Verbeiren, Toni and Sakai, Ryo and Aerts, Jan} }
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/123456789/33726"> <foaf:homepage rdf:resource="http://localhost:8080/"/> <dspace:isPartOfCollection rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/36"/> <void:sparqlEndpoint rdf:resource="http://localhost/fuseki/dspace/sparql"/> <dc:language>eng</dc:language> <dcterms:abstract xml:lang="eng">Visual biases and more generally cognitive biases are a part of human life. Often to the frustration of the rational decision makers we aspire to be. Research into these biases has sparked a recent burst in interest, and more and more people are aware of possible pitfalls. In this paper, we argue that the consequences of biases during data analysis have to be considered rather than the occurrences themselves. In applying this, we distinguish between (visual) analysis for exploration and validation. Especially the latter turns out to be hard in some cases, indicated by a qualitative measure we call validation cost. Examples are provided of situations with a high validation cost and the role of visualization is discussed in these cases. For cases with a low validation cost, we argue that biases leading to false positives are far better than trying to avoid biases and ending up with false negatives.</dcterms:abstract> <bibo:uri rdf:resource="https://kops.uni-konstanz.de/handle/123456789/33726"/> <dcterms:hasPart rdf:resource="https://kops.uni-konstanz.de/bitstream/123456789/33726/3/Verbeiren_0-329490.pdf"/> <dc:creator>Sakai, Ryo</dc:creator> <dcterms:rights rdf:resource="https://rightsstatements.org/page/InC/1.0/"/> <dc:contributor>Aerts, Jan</dc:contributor> <dcterms:title>A Pragmatic Approach to Biases in Visual Data Analysis</dcterms:title> <dc:creator>Verbeiren, Toni</dc:creator> <dc:contributor>Sakai, Ryo</dc:contributor> <dc:contributor>Verbeiren, Toni</dc:contributor> <dcterms:issued>2014</dcterms:issued> <dspace:hasBitstream rdf:resource="https://kops.uni-konstanz.de/bitstream/123456789/33726/3/Verbeiren_0-329490.pdf"/> <dc:rights>terms-of-use</dc:rights> <dcterms:available rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2016-04-28T11:44:12Z</dcterms:available> <dc:creator>Aerts, Jan</dc:creator> <dcterms:isPartOf rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/36"/> <dc:date rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2016-04-28T11:44:12Z</dc:date> </rdf:Description> </rdf:RDF>