Data management plans as linked open data: exploiting ARGOS FAIR and machine actionable outputs in the OpenAIRE...

Area of Science:

• Research Infrastructure
• Data Science
• Scholarly Communication

Background:

• Open Science Graphs (OSGs) contextualize research entities but lack automated DMP integration.
• Data Management Plans (DMPs) are crucial for research processes but are often underexposed and difficult to find.
• Existing systems lack automated workflows to link DMPs with research data and other contextual information, hindering FAIR data principles.

Purpose of the Study:

• To integrate machine-actionable Data Management Plans (ma-DMPs) into Open Science Graphs (OSGs).
• To enhance the OpenAIRE Research Graph (RG) by incorporating DMP entities and semantics.
• To strengthen the FAIRness of research outputs and improve information exchange within the research ecosystem.

Main Methods:

• Comparative analysis of ARGOS and OpenAIRE RG data models against the DMP Common Standard.
• Extension of the ARGOS tool with export format converters and semantic tagging capabilities.
• Integration of ma-DMPs into the OpenAIRE OSG by adding DMP entities and relationships.

Main Results:

• Successful integration of ARGOS ma-DMPs into the OpenAIRE OSG.
• Enrichment of the OpenAIRE OSG with DMP entities, making them FAIR research outputs.
• Demonstration of interoperability practices for populating the OpenAIRE RG with DMP information.

Conclusions:

• This work introduces the novel concept of exposing ma-DMPs within OSGs, establishing DMPs as key research lifecycle entities.
• It details the interoperability practices of the ARGOS DMP service and its integration with the OpenAIRE Research Graph.
• The findings strengthen research output FAIRness and standardize information exchange by linking DMPs to the broader research graph.