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Open AccessArticle

Exhibiting Uncertainty: Visualizing Data Quality Indicators for Cultural Collections

danubeVISlab, Department for Knowledge and Communication Management, Danube University Krems, Dr.-Karl-Dorrek-Strasse 30, A-3500 Krems, Austria
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Informatics 2019, 6(3), 29; https://doi.org/10.3390/informatics6030029
Received: 30 June 2019 / Revised: 24 July 2019 / Accepted: 24 July 2019 / Published: 31 July 2019
(This article belongs to the Collection Uncertainty in Digital Humanities)
Uncertainty is a standard condition under which large parts of art-historical and curatorial knowledge creation and communication are operating. In contrast to standard levels of data quality in non-historical research domains, historical object and knowledge collections contain substantial amounts of uncertain, ambiguous, contested, or plainly missing data. Visualization approaches and interfaces to cultural collections have started to represent data quality and uncertainty metrics, yet all existing work is limited to representations for isolated metadata dimensions only. With this article, we advocate for a more systematic, synoptic and self-conscious approach to uncertainty visualization for cultural collections. We introduce omnipresent types of data uncertainty and discuss reasons for their frequent omission by interfaces for galleries, libraries, archives and museums. On this basis we argue for a coordinated counter strategy for uncertainty visualization in this field, which will also raise the efforts going into complex interface design and conceptualization. Building on the PolyCube framework for collection visualization, we showcase how multiple uncertainty representation techniques can be assessed and coordinated in a multi-perspective environment. As for an outlook, we reflect on both the strengths and limitations of making the actual wealth of data quality questions transparent with regard to different target and user groups. View Full-Text
Keywords: cultural collections; data quality; uncertainty; visualization; graphs; maps; sets; time-oriented data; cognition support; digital humanities cultural collections; data quality; uncertainty; visualization; graphs; maps; sets; time-oriented data; cognition support; digital humanities
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Windhager, F.; Salisu, S.; Mayr, E. Exhibiting Uncertainty: Visualizing Data Quality Indicators for Cultural Collections. Informatics 2019, 6, 29.

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