Work

The ONTOLISST project on DDI metadata, vocabularies and NLP

Year: 2024

Type: article

Abstract: The talk introduces the new 2-year ONTOLISST project starting in December 2024, funded by the first OSCARS Cascading grant call. The project will develop a simplified multilingual ontology (LiSST) to describe social science research data, create a corpus of social science metadata, and research whether and how NLP tools can help with (semi)automated (meta)data curation. The aim is to better understand how social science archives assign thematic metadata to their datasets in order to describe their contents and how data curation practices shape social scientific understanding. ONTOLISST will build on metadata in DDI format in different languages from various sources and using different CVs. The presentation outlines the project tasks, expected outputs and relationships with existing standards and tools. It also discusses how AI could help to accelerate the tedious, resource-intensive but important work of metadata and data curation and improve (meta)data interoperability across languages and disciplinary barriers.

Source: Zenodo (CERN European Organization for Nuclear Research)

DOI: 10.5281/zenodo.14671272

Authors: Danciu, Alina, Gárdos, Judit, Kleemola, Mari

Institutions: Centre de données socio-politiques de Sciences Po, Centre for Social Sciences, Hungarian Research Network, Tampere University

Language: English

Topic: Research Data Management Practices

Subfield: Information Systems

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

Funder: European Commission

Award: O.S.C.A.R.S. - Open Science Clusters’ Action for Research and Society