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A semantic model for traditional data collection questionnaires enabling cultural analysis

Abgaz, Yalemisew orcid logoORCID: 0000-0002-3887-5342, Dorn, Amelie, Piringer, Barbara orcid logoORCID: 0000-0001-9983-1362, Wandl-Vogt, Eveline orcid logoORCID: 0000-0002-0802-0255 and Way, Andy orcid logoORCID: 0000-0001-5736-5930 (2018) A semantic model for traditional data collection questionnaires enabling cultural analysis. In: 6th Workshop on Linked Data in Linguistics: Towards Linguistic Data Science, 7 - 12 May 2018, Miyazaki, Japan. ISBN 979-10-95546-19-1

Abstract
Around the world, there is a wide range of traditional data manually collected for different scientific purposes. A small portion of this data has been digitised, but much of it remains less usable due to a lack of rich semantic models to enable humans and machines to understand, interpret and use these data. This paper presents ongoing work to build a semantic model to enrich and publish traditional data collection questionnaires in particular, and the historical data collection of the Bavarian Dialects in Austria in general. The use of cultural and linguistic concepts identified in the questionnaire questions allow for cultural exploration of the non-standard data (answers) of the collection. The approach focuses on capturing the semantics of the questionnaires dataset using domain analysis and schema analysis. This involves analysing the overall data collection process (domain analysis) and analysing the various schema used at different stages (schema analysis). By starting with modelling the data collection method, the focus is placed on the questionnaires as a gateway to understanding, interlinking and publishing the datasets. A model that describes the semantic structure of the main entities such as questionnaires, questions, answers and their relationships is presented.
Metadata
Item Type:Conference or Workshop Item (Paper)
Event Type:Conference
Refereed:Yes
Uncontrolled Keywords:Ontology; E-lexicography; Semantic uplift
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
Published in: 6th Workshop on Linked Data in Linguistics: Towards Linguistic Data Science,Proceedings of. . European Language Resource Association. ISBN 979-10-95546-19-1
Publisher:European Language Resource Association
Official URL:http://lrec-conf.org/workshops/lrec2018/W23/pdf/4_...
Copyright Information:© 2018 ELRA
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: Digitales kulturelles Erbe, No. DH2014/22. as part of the exploreAT! project, ADAPT Centre for Digital Content Technology at Dublin City University funded under the Science Foundation Ireland Research Centres Programme (Grant 13/RC/2106) and is co-funded under the European Regional D
ID Code:23209
Deposited On:25 Apr 2019 15:12 by Thomas Murtagh . Last Modified 18 Jan 2021 17:14
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