https://w3id.org/np/RALL0wAU1OwfnKjaCYz7kcPZv95ES41Ng7vmpe8IBhJSM/Head https://w3id.org/np/RALL0wAU1OwfnKjaCYz7kcPZv95ES41Ng7vmpe8IBhJSM http://www.nanopub.org/nschema#hasAssertion https://w3id.org/np/RALL0wAU1OwfnKjaCYz7kcPZv95ES41Ng7vmpe8IBhJSM/assertion https://w3id.org/np/RALL0wAU1OwfnKjaCYz7kcPZv95ES41Ng7vmpe8IBhJSM http://www.nanopub.org/nschema#hasProvenance https://w3id.org/np/RALL0wAU1OwfnKjaCYz7kcPZv95ES41Ng7vmpe8IBhJSM/provenance https://w3id.org/np/RALL0wAU1OwfnKjaCYz7kcPZv95ES41Ng7vmpe8IBhJSM http://www.nanopub.org/nschema#hasPublicationInfo https://w3id.org/np/RALL0wAU1OwfnKjaCYz7kcPZv95ES41Ng7vmpe8IBhJSM/pubinfo https://w3id.org/np/RALL0wAU1OwfnKjaCYz7kcPZv95ES41Ng7vmpe8IBhJSM http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://www.nanopub.org/nschema#Nanopublication https://w3id.org/np/RALL0wAU1OwfnKjaCYz7kcPZv95ES41Ng7vmpe8IBhJSM/assertion https://doi.org/10.1145/3587259.3627559 http://purl.org/dc/terms/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. https://doi.org/10.1145/3587259.3627559 http://purl.org/dc/terms/date 2023-12-05 https://doi.org/10.1145/3587259.3627559 http://purl.org/dc/terms/isPartOf https://w3id.org/np/RALL0wAU1OwfnKjaCYz7kcPZv95ES41Ng7vmpe8IBhJSM/kcap-2023 https://doi.org/10.1145/3587259.3627559 http://purl.org/dc/terms/title Advancing data sharing and reusability for restricted access data on the Web: introducing the DataSet-Variable Ontology https://doi.org/10.1145/3587259.3627559 http://purl.org/ontology/bibo/authorList https://w3id.org/np/RALL0wAU1OwfnKjaCYz7kcPZv95ES41Ng7vmpe8IBhJSM/author-list https://doi.org/10.1145/3587259.3627559 http://purl.org/ontology/bibo/pageEnd 91 https://doi.org/10.1145/3587259.3627559 http://purl.org/ontology/bibo/pageStart 83 https://doi.org/10.1145/3587259.3627559 http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://purl.org/spar/fabio/ConferencePaper https://orcid.org/0000-0001-8004-0464 http://schema.org/affiliation https://ror.org/008xxew50 https://orcid.org/0000-0001-8004-0464 http://xmlns.com/foaf/0.1/name Margherita Martorana https://orcid.org/0000-0001-8772-7904 http://schema.org/affiliation https://ror.org/008xxew50 https://orcid.org/0000-0001-8772-7904 http://xmlns.com/foaf/0.1/name Ronald Siebes https://orcid.org/0000-0002-1267-0234 http://schema.org/affiliation https://ror.org/008xxew50 https://orcid.org/0000-0002-1267-0234 http://xmlns.com/foaf/0.1/name Tobias Kuhn https://orcid.org/0000-0002-7748-4715 http://schema.org/affiliation https://ror.org/008xxew50 https://orcid.org/0000-0002-7748-4715 http://xmlns.com/foaf/0.1/name Jacco van Ossenbruggen https://ror.org/008xxew50 http://xmlns.com/foaf/0.1/name Department of Computer Science, Vrije Universiteit Amsterdam, Amsterdam, Netherlands https://w3id.org/np/RALL0wAU1OwfnKjaCYz7kcPZv95ES41Ng7vmpe8IBhJSM/author-list http://www.w3.org/1999/02/22-rdf-syntax-ns#_1 https://orcid.org/0000-0001-8004-0464 https://w3id.org/np/RALL0wAU1OwfnKjaCYz7kcPZv95ES41Ng7vmpe8IBhJSM/author-list http://www.w3.org/1999/02/22-rdf-syntax-ns#_2 https://orcid.org/0000-0002-1267-0234 https://w3id.org/np/RALL0wAU1OwfnKjaCYz7kcPZv95ES41Ng7vmpe8IBhJSM/author-list http://www.w3.org/1999/02/22-rdf-syntax-ns#_3 https://orcid.org/0000-0001-8772-7904 https://w3id.org/np/RALL0wAU1OwfnKjaCYz7kcPZv95ES41Ng7vmpe8IBhJSM/author-list http://www.w3.org/1999/02/22-rdf-syntax-ns#_4 https://orcid.org/0000-0002-7748-4715 https://w3id.org/np/RALL0wAU1OwfnKjaCYz7kcPZv95ES41Ng7vmpe8IBhJSM/kcap-2023 http://purl.org/dc/terms/title Proceedings of the 12th Knowledge Capture Conference (K-CAP 2023) https://w3id.org/np/RALL0wAU1OwfnKjaCYz7kcPZv95ES41Ng7vmpe8IBhJSM/provenance 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