Automatic quality feedback for inter-disciplinary research data management

Names: Vidya Ayer, Christian Pietsch

Audience: researchers, librarians, data scientists, research software engineers

Maximum number of participants: 20-25

Short description:

In this workshop we will share research experiences from the DFG-funded project Conquaire ("continuous quality control for research data to ensure reproducibility"). Our approach is to tap into the research workflow in an unobtrusive manner by sending automated quality assessments via email whenever researchers upload research data or code into our local GitLab instance.
Our workshop learning objective is to understand, familiarize and discuss guidelines for research data management (RDM) services provided by academic libraries and research teams at universities. We will introduce the research data and quality aspects of computational reproducibility in Conquaire and provide context on what information should be stored in metadata to enable data reuse. This will kickstart our workshop objective of deeper discussions on the following topics:

1) Technical (software infrastructure) challenges
- How Universities overcame the technical barries in rainbow-hued interdisciplinary research projects?
- Infrastructure - Automation and software maintenance
    * Version management tools used to maintain changes and dependencies.
    * Discuss impact of dependency hell on projects (reproducibility), find solutions and alternatives.
- Anticipating and preparing for the impact of change - the "technology" and "research freedom" perspective.

2) Tools
- knowledge of open access/open research.
- libre vs. proprietary - reproducibility impact, challenges.

3) Storage
- What library services were integrated while managing research data?
- Discuss the storage challenges.

4) Fundamental RDM challenges in interdisciplinary research projects
- Common file formats.
- Research objects, container objects, ontologies to store metadata.
- Data pipeline maintainence tools.
- Common computational services, skills and technology used.

Workshop outcomes:

- Learn and gain insights on current research data management (RDM) practices.
- Document tools and methodologies currently used within research groups.
- Document guidelines on organizing research workflows in various interdisciplinary scientific research projects.
- Document the impact of Libre tools on research reproducibility and workflow automation.