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- 3587259.3627559 type ConferencePaper assertion.
- author-list _1 0000-0001-8004-0464 assertion.
- author-list _2 0000-0002-1267-0234 assertion.
- author-list _3 0000-0001-8772-7904 assertion.
- author-list _4 0000-0002-7748-4715 assertion.
- 0000-0002-1267-0234 name "Tobias Kuhn" assertion.
- 0000-0002-7748-4715 name "Jacco van Ossenbruggen" assertion.
- 0000-0001-8004-0464 name "Margherita Martorana" assertion.
- 0000-0001-8772-7904 name "Ronald Siebes" assertion.
- 008xxew50 name "Department of Computer Science, Vrije Universiteit Amsterdam, Amsterdam, Netherlands" assertion.
- kcap-2023 title "Proceedings of the 12th Knowledge Capture Conference (K-CAP 2023)" assertion.
- 3587259.3627559 title "Advancing data sharing and reusability for restricted access data on the Web: introducing the DataSet-Variable Ontology" assertion.
- 3587259.3627559 date "2023-12-05" assertion.
- 3587259.3627559 isPartOf kcap-2023 assertion.
- 3587259.3627559 abstract "In response to the increasing volume of research data being generated, more and more data portals have been designed to facilitate data findability and accessibility. However, a significant portion of this data remains confidential or restricted due to its sensitive nature, such as patient data or census microdata. While maintaining confidentiality prohibits its public release, the emergence of portals supporting rich metadata can help enable researchers to at least discover the existence of restricted access data, empowering them to assess the suitability of the data before requesting access. Existing standards, such as CSV on the Web and RDF Data Cube, have been adopted to facilitate data management, integration, and re-use of data on the Web. However, the current landscape still lacks adequate standards not only to effectively describe restricted access data while preserving confidentiality but also to facilitate its discovery. In this work, we investigate the relationship between the structural, statistical, and semantic elements of restricted access tabular data, and we explore how such relationship can be formally modeled in a way that is Findable, Accessible, Interoperable, and Reusable. We introduce the DataSet-Variable Ontology (DSV), that by combining CSV on the Web and RDF Data Cube standards, leveraging semantic technologies and Linked Data principles, and introducing variable-level metadata, aims to capture high-quality metadata to support the management and re-use of restricted access data on the Web. As evaluation, we conducted a case study where we applied DSV to four different datasets from different statistical governmental agencies. We employed a set of competency questions to assess the ontology's ability to support knowledge discovery and data exploration. By describing high-quality metadata, both at the dataset- and variable levels, while maintaining data privacy, this novel ontology facilitates data interoperability, discovery, and re-use and it empowers researchers to manage, integrate, and analyze complex restricted access data sources." assertion.
- 0000-0002-1267-0234 affiliation 008xxew50 assertion.
- 0000-0002-7748-4715 affiliation 008xxew50 assertion.
- 0000-0001-8004-0464 affiliation 008xxew50 assertion.
- 0000-0001-8772-7904 affiliation 008xxew50 assertion.
- 3587259.3627559 authorList author-list assertion.
- 3587259.3627559 pageEnd "91" assertion.
- 3587259.3627559 pageStart "83" assertion.