A Linked Data Model for Data Scopes

Victor de Boer*, Ivette Bonestroo, Marijn Koolen, Rik Hoekstra

*Corresponding author for this work

Research output: Chapter in Book / Report / Conference proceedingConference contributionAcademicpeer-review

Abstract

With the rise of data driven methods in the humanities, it becomes necessary to develop reusable and consistent methodological patterns for dealing with the various data manipulation steps. This increases transparency, replicability of the research. Data scopes present a qualitative framework for such methodological steps. In this work we present a Linked Data model to represent and share Data Scopes. The model consists of a central Data scope element, with linked elements for data Selection, Linking, Modeling, Normalisation and Classification. We validate the model by representing the data scope for 24 articles from two domains: Humanities and Social Science.

Original languageEnglish
Title of host publicationMetadata and Semantic Research
Subtitle of host publication14th International Conference, MTSR 2020, Madrid, Spain, December 2–4, 2020, Revised Selected Papers
EditorsEmmanouel Garoufallou, María-Antonia Ovalle-Perandones
PublisherSpringer Science and Business Media Deutschland GmbH
Pages345-351
Number of pages7
ISBN (Electronic)9783030719036
ISBN (Print)9783030719029
DOIs
Publication statusPublished - 2021
Event14th International Conference on Metadata and Semantics Research, MTSR 2020 - Madrid, Spain
Duration: 2 Dec 20204 Dec 2020

Publication series

NameCommunications in Computer and Information Science
Volume1355 CCIS
ISSN (Print)1865-0929
ISSN (Electronic)1865-0937

Conference

Conference14th International Conference on Metadata and Semantics Research, MTSR 2020
Country/TerritorySpain
CityMadrid
Period2/12/204/12/20

Bibliographical note

Funding Information:
Acknowledgements. The research for this article was made possible by the CLARIAH-PLUS project financed by NWO (http://www.clariah.nl). The authors would like to thank Gard Ruurd for his contributions to the research.

Publisher Copyright:
© 2021, Springer Nature Switzerland AG.

Copyright:
Copyright 2021 Elsevier B.V., All rights reserved.

Keywords

  • Data scope
  • Linked Data
  • Scholarly data

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