A semantic model for traditional data collection questionnaires enabling cultural analysis
Abgaz, YalemisewORCID: 0000-0002-3887-5342, Dorn, Amelie, Piringer, BarbaraORCID: 0000-0001-9983-1362, Wandl-Vogt, EvelineORCID: 0000-0002-0802-0255 and Way, AndyORCID: 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
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.
6th Workshop on Linked Data in Linguistics: Towards Linguistic Data Science,Proceedings of.
.
European Language Resource Association. ISBN 979-10-95546-19-1
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