Institutional Data Science Services at FDZ UB Mannheim: Enhancing Research Data Management
Creators: name: Shigapov, Renat
name: Schumm, Irene
name: Schmidt, Thomas
name: Kamlah, Jan
name: Will, Larissa
Publisher: name: Zenodo
Year: 2025
Subjects: RDM
research data management
data science
research infrastructure
data literacy
Open Science
AI

description: Presentation at the E-Science-Tage conference in Heidelberg, Germany, March 13, 2025 about data science services at Mannheim University Library.
description: Data Science Services have rapidly emerged as essential support mechanisms for research data management (RDM) at universities worldwide. Notable examples include services at Harvard University, the University of Utah, Purdue University, NC State University, and the University of Groningen. In Germany, several initiatives have demonstrated how data science services can drive research data management. These include the Data Science Center at the University of Bremen, the Bielefeld Center for Data Science, and recent discussions on establishing Data Science Centers at higher education institutions.

In alignment with these developments, the research data center (FDZ) at the Mannheim University Library (UB Mannheim) has established institutional data science services at the University of Mannheim. Our goal is to enhance RDM, promote open science, and contribute to research reproducibility. We aim to empower researchers to undertake data science tasks with modern research data management practices. We support researchers throughout the entire data science pipeline — from data collection and processing to analysis, visualization, modeling, and reporting. Our services include not only expert consulting, RDM-focused training, and community engagement, but also implementing the data science pipelines and writing data papers together with researchers.

We begin by advising on the data science components of funding proposals, ensuring the feasibility of data science pipelines. We assist with or perform data acquisition using techniques such as web scraping, API calls, Optical Character Recognition (OCR), audio and video transcription, and data extraction from diverse sources.

Once data is collected, we provide support for or perform data cleaning, exploratory analysis, and modeling using Python and R, with a strong emphasis on open science and reproducibility. We guide researchers in writing open-source code, organizing their repositories on GitHub, archiving their codes, models, data, and documentation in data repositories, ensuring adherence to the FAIR (Findable, Accessible, Interoperable, Reusable) principles, and writing data papers.

We support deploying customized AI systems (chatbots) and using free cloud and institutional infrastructures. Recognizing that many researchers, due to their educational background, may have little to no programming experience, we offer guidance on low-code and no-code tools, empowering them to perform complex analysis without extensive programming skills.

Our services enhance the publication of research data by assisting researchers in presenting their data in accessible formats such as knowledge graphs, interactive web applications, and digital editions.

To foster collaboration and community engagement, we connect researchers with potential partners and actively participate in workshops and conferences hosted by our researchers such as the data science meetups organized by the Mannheim Center for Data Science and the GESS (Graduate School of Economic and Social Sciences) Research Day.

Our training sessions are part of the well-established “Research Skills” series, covering data science topics in RDM events such as “Data Literacy Essentials” and “RDM Seminars”.

This presentation will detail the development of data science services at the research data center of the Mannheim University Library. We will share our experiences in building these services, the challenges we faced, and the positive impact these services have had on RDM at our institution.