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dc.contributor.authorBolte, Fabian
dc.contributor.authorBruckner, Stefan
dc.date.accessioned2021-07-13T11:06:11Z
dc.date.available2021-07-13T11:06:11Z
dc.date.created2021-01-26T14:00:58Z
dc.date.issued2020
dc.identifier.isbn978-3-030-34443-6
dc.identifier.urihttps://hdl.handle.net/11250/2764271
dc.description.abstractMeasurement is an integral part of modern science, providing the fundamental means for evaluation, comparison, and prediction. In the context of visualization, several different types of measures have been proposed, ranging from approaches that evaluate particular aspects of visualization techniques, their perceptual characteristics, and even economic factors. Furthermore, there are approaches that attempt to provide means for measuring general properties of the visualization process as a whole. Measures can be quantitative or qualitative, and one of the primary goals is to provide objective means for reasoning about visualizations and their effectiveness. As such, they play a central role in the development of scientific theories for visualization. In this chapter, we provide an overview of the current state of the art, survey and classify different types of visualization measures, characterize their strengths and drawbacks, and provide an outline of open challenges for future research.en_US
dc.language.isoengen_US
dc.publisherSpringeren_US
dc.relation.ispartofFoundations of Data Visualization
dc.titleMeasures in Visualization Spaceen_US
dc.typeChapteren_US
dc.description.versionacceptedVersionen_US
dc.rights.holderCopyright Springer Nature Switzerland AG 2020en_US
cristin.ispublishedtrue
cristin.fulltextpostprint
cristin.qualitycode1
dc.identifier.doihttps://doi.org/10.1007/978-3-030-34444-3_3
dc.identifier.cristin1879632
dc.source.pagenumber39-59en_US
dc.identifier.citationIn: Chen M., Hauser H., Rheingans P., Scheuermann G. (eds), Foundations of Data Visualization, 39-59.en_US


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