Abgaz, Yalemisew ORCID: 0000-0002-3887-5342, Dorn, Amelie, Piringer, Barbara ORCID: 0000-0001-9983-1362, Wandl-Vogt, Eveline ORCID: 0000-0002-0802-0255 and Way, Andy ORCID: 0000-0001-5736-5930 (2018) Semantic modelling and publishing of traditional data collection questionnaires and answers. Information, 9 (12). pp. 1-24. ISSN 2078-2489
Abstract
Extensive 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.
Metadata
Item Type: | Article (Published) |
---|---|
Refereed: | Yes |
Uncontrolled Keywords: | ontology; E-lexicography; semantic uplift; semantic modelling; questionnaires; linked data; linguistic linked open data |
Subjects: | Computer Science > Machine translating |
DCU Faculties and Centres: | DCU Faculties and Schools > Faculty of Engineering and Computing > School of Computing Research Institutes and Centres > ADAPT |
Publisher: | MDPI |
Official URL: | http://dx.doi.org/10.3390/info9120297 |
Copyright Information: | © 2018 The Authors |
Use License: | This item is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 License. View License |
Funders: | Nationalstiftung of the Austrian Academy of Sciences under the funding scheme: Digitales kulturelles Erbe, No. DH2014/22. as part of the exploreAT!, ADAPT Centre for Digital Content Technology at Dublin City University which is funded under the Science Foundation Ireland Research Centres Programme (Grant 13/RC/2106) and is cofunded under the European Regional Development Fund. |
ID Code: | 23294 |
Deposited On: | 13 May 2019 15:09 by Thomas Murtagh . Last Modified 18 Jan 2021 17:13 |
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