From Research Data to Research Software Competencies

• Jan Bernoth
• Bettina Buchholz
• Christine Hennig
• Alicia Janz
• Ulrike Lucke
• Evgenia Samoilova
• Sonja Schimmler

While research data availability is increasingly accepted as essential for transparent and reproducible research, research software has not yet achieved equivalent recognition or support. This paper presents findings from the “Research Data and Software Competencies” (RDSC) workshop, which brought together 38 participants from 23 institutions to address this challenge. The workshop was structured around three tracks: the Research Software Track identified essential but overlooked competencies and gaps in existing frameworks; the Competency Development Track explored effective approaches for developing these competencies; and the Collaboration Track focused on sustainable mechanisms for sharing educational resources. The findings synthesize participant perspectives on key priorities and challenges in developing research software competencies.

Code Competencies for Better Science: Recommendations for the German Academic System

• Adina Wagner

Slides: https://files.inm7.de/adina/talk-FSKomp/ Research software is becoming more and more important in the scientific discovery process. However, the necessary skills to develop and use research software are not sufficiently incorporated in the German academic system yet. But what is needed to equip the next generations of students and scientists with software competencies? To address this question, a group of roughly 30 members from various research stakeholders - among others, members of the deRSE association, representatives of academic institutions, research software engineers, open science advocates, and teachers - developed recommendations for action to improve research software skills in the German academic system in a Workshop supported by the Volkswagenstiftung in December 2024. The resulting actionable recommendations address various actors: Science policy, funding bodies, scientific infrastructure, institute directors, managers, teaching staff, interest groups and associations, and developers of research software, and they include short-term as well as long-term actions. In addition, they include a status report from various institutions about their approaches and perspectives on research software competencies, for example from libraries, research data management services, or high performance computing. Their first version has been published in February 2025 ahead of the the deRSE 2025 in Karlsruhe (Christ et al., 2025, https://doi.org/10.5281/zenodo.14273367), This publication shall, however, be a living document, reflecting the evolving needs of the system and the different stakeholders within it. In this contribution, we thus hope present the recommendations to a broader, English-speaking audience and aim to spark multidisciplinary discussions as well as gather feedback to extend and refine the recommendations further.

Comparing Research Software Engineering and Data Science Competencies

• Julian Dehne
• Jan Philipp Thiele
• Katrin Schöning-Stierand
• Florian Goth
• Jan Linxweiler
• Harald von Waldow
• Anna-Lena Lamprecht

Research Software Engineers and Data Scientists have overlapping yet distinct roles within the landscape of digitally skilled professionals. Both roles are highly software-focused and operate across a wide range of research domains, yet their communities and competency frameworks have evolved independently. This paper explores the intersections and distinctions between RSE and DS competencies, particularly as they relate to different phases of the research cycle.

An Overview of Competency Areas in Artifact Evaluation

• Martin Armbruster
• Jan Bernoth

For assessing the quality of (FAIR) research artifacts, artifact evaluations as a form of peer reviews have been established. However, they raise questions about the required competencies. Thus, this short paper provides an overview of six artifact evaluation processes and their goals, which exhibit a multidimensional influence on the required competencies. Based on these factors, initial competency areas can be identified.

A Walk through Metadata for Training Materials

• Leyla Jael Castro

In this talk, we will briefly introduce the subject of metadata with a focus on semantic metadata. We will then move to some semantic metadata available for training materials/learning resources. Rather than going in-depth, the aim is raising awareness of the options out there, some of their differences and similarities.

From Data to Knowledge: OER-Supported Teaching of Data Literacy in Administrative Science

• Jana Plomin
• Paul Walter
• Hannes Schnaitter
• Juliane Schmeling

This article examines the approach to teaching data literacy in the QUADRIGA data literacy centre. It focuses on the structure and evaluation of Open Educational Resources (OER) for postgraduate and postdoctoral administrative scientists created in the project. Using the example of the first case study for one data type, it is shown how data-related technical, methodological and application competences can be promoted through research-led OER and thus key competences can be strengthened. That integrates a specially developed data literacy framework that shows the partition of competencies in the research process.

A Jupyter Book Template for Research-Based Open Educational Resources in Data Literacy

• Hannes Schnaitter
• Evgenia Samoilova
• Lamia Islam

Slides:https://zenodo.org/records/17135938 This paper introduces a Jupyter Book–based template designed to support the creation of modular, interactive Open Educational Resources (OER) for data literacy. The template provides educators with a structured framework to convert authentic research workflows into pedagogically coherent modules, each comprising theoretical background, hands-on practice, reflective activities, and formative assessment. By embedding data skills within discipline-specific case studies, it enables the development of reusable and accessible learning materials. We describe the template’s instructional design and technical architecture, and highlight the core challenge of aligning software requirements with the diverse software competencies of OER creators.

Interactive Visualization with the R Package Shiny: A Tool for Building Research Data and Software Competencies

• Maryam Movahedifar
• Lena Steinmann
• Rolf Drechsler

Interactive tools like the Shiny R package enable researchers to develop user-friendly, reproducible data applications, fostering essential research data and software competencies (RDSCs). This paper explores how Shiny supports training and practice in RDSCs by enhancing workflows, promoting reusability and transparency, and enabling hands-on learning. A simulation-based Shiny app is presented as an example to demonstrate the development and operationalization of competencies related to data visualization, statistical modeling, and software reusability. Practical implications for education and competency-building programs are discussed.

Supporting Research Software Competencies with Infrastructure

• Jan Bernoth

This presentation examines the competencies needed to produce FAIR Research Software based on FAIR Principles for Research Software (FAIR4RS). These competencies will be mapped to existing research software skills, aiming to spark a discussion about the specific skills required to comply with the FAIR4RS. Additionally, it will be addressed how infrastructure from NFDI(xCS) can support these skills while highlighting competency areas that are not yet covered by the available infrastructure.