2026-10-28 –, Naturalis 01
How can you use data to better understand and improve ORCID adoption in your research environment?
In this lightning talk, you will discover how the Czech National ORCID Consortium works with real data to support ORCID adoption and improve researcher data quality. You will see how working with data can help identify challenges in researcher identification and improve data quality, illustrated through an example such as detection and monitoring of potential duplicate researcher records over time based on data from the national research information system (IS VaVaI).
You will also learn how working with different data sources can provide further insights into ORCID adoption and data quality, depending on context and available data.
This session will give you a practical example of how data-driven approaches can support communication with institutions and policymakers and help improve the quality and consistency of researcher data.
Do you want to improve duplicate, incomplete, or inconsistent researcher data? Using the Czech Republic as a case study, you will see how working with data can reveal different types of issues in researcher identification.
In this session, you will discover how you can use real data to better understand and improve ORCID adoption and data quality in your research environment.
You will learn how data analysis can help identify and explore data quality issues, illustrated through a practical example based on data from a national current research information system (IS VaVaI), such as identifying potential duplicate records (e.g. multiple ORCID iDs assigned to the same researcher, inconsistent identifiers, or similar names and affiliations). You will also see how these approaches can be applied over time to track trends and monitor improvements in data quality.
You will also discover how working with additional data sources can provide further insights into ORCID adoption and profile completeness, depending on available data and context. These findings can help you better understand how researchers engage with ORCID and where targeted support or communication may be needed.
You will also see how these insights are translated into practice — for example, by sharing identified issues with institutions and national stakeholders to support data correction and improve overall data consistency.
After this session, you will better understand:
- how to identify and categorise data quality issues (such as duplicate researcher records) using real-world data,
- how to use data analysis to support communication with institutions and policymakers,
- how to apply data-driven approaches to improve ORCID adoption and data quality.
This session offers a practical example of how working with data about researcher identities can strengthen the role of persistent identifiers in a national research ecosystem.
Hana Šilha Machová is the coordinator of the Czech National ORCID Consortium, part of the National Centre for Persistent Identifiers at the National Library of Technology (NTK). She is involved in the EOSC CZ Core Services working group and has extensive experience in research support, persistent identifiers, and scholarly communication.