A study on formalizing the knowledge of data curation activities across different fields
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View abstract on PubMed
Summary
This summary is machine-generated.This study proposes a universal ontology for data curation processes to enable interdisciplinary research data sharing. It addresses the lack of formalized granularity in data curation tasks, promoting data reusability across diverse scientific fields.
Area Of Science
- Data Science
- Information Science
- Scientific Research
Background
- Open science trends necessitate research data sharing.
- Data curation is crucial for data interpretability and reusability.
- Existing data curation practices are field-specific, hindering interdisciplinary sharing.
Purpose Of The Study
- To survey, analyze, and organize knowledge of data curation across research fields.
- To develop a universal ontology for describing data curation processes.
- To facilitate interdisciplinary data sharing and reuse.
Main Methods
- Collected and compared existing data curation vocabularies and procedures.
- Conducted interviews with data curators from various research fields.
- Developed a data curation process ontology using OWL.
Main Results
- Identified a lack of formalized granularity in data curation tasks and procedures.
- Proposed a universally applicable ontology for data curation processes.
- Demonstrated the ontology's validity, consistency, and ability to represent diverse curation activities.
Conclusions
- The proposed ontology provides a knowledge framework for interdisciplinary understanding of data curation.
- This framework supports the identification of functions for data curation support systems.
- Overcoming granularity gaps is essential for promoting interdisciplinary research data reuse.
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