A method for examining metadata quality in open research datasets using the OAI-PMH and SQL queries: the case of the Dublin Core 'Subject' element and suggestions for user-centred metadata annotation design. (2018)

• Record Type: Journal Article
• Authors: Balatsoukas, Panos; Rousidis, Dimitris; Garoufallou, Emmanouel
• Is Part Of: International journal of metadata, semantics and ontologies. Volume 13:Number 1(2018)
• Page Start: 1
• Page End: 8
• Publication Date: 2018
• Subjects: Big Data -- Dublin Core -- data quality -- open access repositories -- metadata -- digital curation -- user centred design -- open research datasets -- Dryad -- metadata quality -- OAI-PMH -- SQL queries; Metadata -- Periodicals; Semantic Web -- Periodicals; Ontologies (Information retrieval) -- Periodicals; Data structures (Computer science) -- Periodicals; Information theory -- Periodicals; 005.74
• Languages: English
• ISSNs: 1744-2621

Abstract

Poor quality metadata can have negative impact not only on the way research datasets are retrieved, shared and used by scientists, but also on the way research data repositories are managed and audited. The aim of the research reported in this paper was to perform a descriptive analysis of the Dublin Core's Subject metadata element and identify its quality problems, if any, in the context of the Dryad research data repository following a novel data-preprocessing method using SQL queries. The findings showed quality problems related to the lack of controlled vocabulary and standardisation, like the inconsistent use of singular and plural forms, adjectives and synonyms. This study has both practical and methodological implications for the evaluation of metadata and the improvement of the quality of the research data annotation process in open research data repositories.