Monitoring researchers profiles on Wikidata: a comparative analysis of country-specific metrics
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Authors Biographies: Alessandro Marchetti (b. 1983) works at the University of Pisa's Department of Biology. With a background in oceanography and soft matter, he manages EU-funded projects. Active in Wikimedia Switzerland, his corrent focus is Wikidata and bibliometry. He coordinates Wiki Loves Monuments in Tuscany.
Keywords: open-access bibliometry, Wikicite, data quality, digital identity, SPARQL
TL;DR: This study analyzes the distribution, quality, and completeness of researcher metadata on Wikidata across countries
Abstract: Wikidata, the open and structured data repository of Wikimedia projects, shows an increasingly significant potential as a platform for organizing and sharing metadata in the academic ecosystem. One aspect is the information related to researchers and authors of peer-reviewed content.
This analysis details the use of the QLever SPARQL query service to describe and monitor researchers’ items on Wikidata, and related fundings. By analyzing the distribution and quality of key metrics such as statements and external identifiers, the study provides a comparative analysis across profiles linked to different countries, focusing on researchers’ educational backgrounds, affiliations, and employers.
Key variations in data coverage, completeness, and quality across different academic ecosystems are investigated, specifically:
• Item distribution: how many researcher items can be associated with each country?
• Statement distribution: which properties are most added to researcher items?
• Identifier distribution: which databases are commonly connected to Wikidata?
This comparative approach enables us to reveal patterns and potential biases in how research communities are represented on Wikidata, shedding light on the global academic landscape.
These findings have potential implications for data accuracy, reliability, and equity on Wikidata, as well as for broader discussions on the digital identity of researchers. We propose strategies for further improving data quality, enhancing representation, and fostering collaboration between all stakeholders, primarily Wikidata editors, academic institutions, and research organizations based on existing active projects. By addressing these challenges, we aim to strengthen the framework for supporting the academic community on Wikidata and contribute to building a more comprehensive and accurate global knowledge base.
Format: Paper
Submission Number: 7
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