DataDesc: A framework for creating and sharing technical metadata for research software interfaces

Area of Science:

• Computer Science
• Information Science
• Scientific Computing

Background:

• Research software reuse is crucial for efficiency and academic exchange.
• Current challenges include software discoverability and compatibility, leading to redundant development.
• This impedes scientific progress and community advancement.

Purpose of the Study:

• Introduce the DataDesc (Data Description) framework to address research software reuse challenges.
• Enable the description of software interface data models using machine-actionable metadata.
• Enhance the FAIRness (Findability, Accessibility, Interoperability, Reusability) of research software.

Main Methods:

• Developed the DataDesc framework with a specialized metadata schema.
• Created an exchange format for software interface data models.
• Introduced support tools for automated collection and publishing of software documentation.

Main Results:

• The DataDesc framework provides machine-actionable metadata for software interfaces.
• Automated documentation publishing increases software findability and accessibility.
• Improved interoperability and reusability of research software are facilitated.

Conclusions:

• The DataDesc framework significantly enhances the FAIRness of research software.
• This approach promotes wider adoption and impact of research software.
• Streamlined software development and scientific collaboration are key outcomes.