Semantic Modelling and Publishing of Traditional Data Collection Questionnaires and Answers†
AbstractExtensive collections of data of linguistic, historical and socio-cultural importance are stored in libraries, museums and national archives with enormous potential to support research. However, a sizable portion of the data remains underutilised because of a lack of the required knowledge to model the data semantically and convert it into a format suitable for the semantic web. Although many institutions have produced digital versions of their collection, semantic enrichment, interlinking and exploration are still missing from digitised versions. In this paper, we present a model that provides structure and semantics to a non-standard linguistic and historical data collection on the example of the Bavarian dialects in Austria at the Austrian Academy of Sciences. We followed a semantic modelling approach that utilises the knowledge of domain experts and the corresponding schema produced during the data collection process. The model is used to enrich, interlink and publish the collection semantically. The dataset includes questionnaires and answers as well as supplementary information about the circumstances of the data collection (person, location, time, etc.). The semantic uplift is demonstrated by converting a subset of the collection to a Linked Open Data (LOD) format, where domain experts evaluated the model and the resulting dataset for its support of user queries. View Full-Text
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Abgaz, Y.; Dorn, A.; Piringer, B.; Wandl-Vogt, E.; Way, A. Semantic Modelling and Publishing of Traditional Data Collection Questionnaires and Answers. Information 2018, 9, 297.
Abgaz Y, Dorn A, Piringer B, Wandl-Vogt E, Way A. Semantic Modelling and Publishing of Traditional Data Collection Questionnaires and Answers. Information. 2018; 9(12):297.Chicago/Turabian Style
Abgaz, Yalemisew; Dorn, Amelie; Piringer, Barbara; Wandl-Vogt, Eveline; Way, Andy. 2018. "Semantic Modelling and Publishing of Traditional Data Collection Questionnaires and Answers." Information 9, no. 12: 297.
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