Towards A Taxonomy of Uncertainties: Analysing Sources of Spatio-Temporal Uncertainty on the Example of Non-Standard German Corpora
Amelie Dorn Austrian Centre for Digital Humanities, Austrian Academy of Sciences, 1010 Vienna, Austria
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Informatics 2019, 6(3), 34; https://doi.org/10.3390/informatics6030034
Received: 30 June 2019 / Revised: 11 August 2019 / Accepted: 19 August 2019 / Published: 1 September 2019
(This article belongs to the Collection Uncertainty in Digital Humanities)
Different types of uncertainties occur in almost all datasets and are an inherent property of data across different academic disciplines, including digital humanities (DH). In this paper, we address, demonstrate and analyse spatio-temporal uncertainties in a non-standard German legacy dataset in a DH context. Although the data collection is primarily a linguistic resource, it contains a wealth of additional, comprehensive information, such as location and temporal detail. The addressed uncertainties have manifested because of a variety of reasons, and partly also because of decades of data transformation processes. We here propose our own taxonomy for capturing and classifying the various uncertainties, and show with numerous examples how the remedying but also re-introduction of uncertainties affects DH practices.
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Keywords:
digital humanities; uncertainty; indigenous languages; spatial uncertainty; temporal uncertainty; lexical data uncertainty
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MDPI and ACS Style
Rocha Souza, R.; Dorn, A.; Piringer, B.; Wandl-Vogt, E. Towards A Taxonomy of Uncertainties: Analysing Sources of Spatio-Temporal Uncertainty on the Example of Non-Standard German Corpora. Informatics 2019, 6, 34.
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