-
06/10/2026, 09:00
-
06/10/2026, 09:05
Prof. Dr. Ilona Grunwald
Go to contribution page
University of Bonn
Vice Rectorate for Research and Career Development -
Dr Magdalene Cyra-Wolf (Landesinitiative für Forschungsdatenmanagement - fdm.nrw)06/10/2026, 09:15
The growing importance of research data management (RDM) in academia goes hand in hand with an increasing diversification of tools and methods. At the same time, it remains essential to meet generic needs through robust infrastructures. In North Rhine-Westphalia, a state wide concept on RDM, the “Landeskonzept FDM”, was published 2024 as a strategy in which universities set out chief...
Go to contribution page -
Dr Christian Bittner (University of Bonn), Dr Sergej Zerr (University of Bonn)06/10/2026, 09:45
Effective research data management (RDM) is essential for transparent, reproducible, and reusable research. At the University of Bonn, a growing ecosystem of services supports researchers across the data lifecycle—from data management planning and efficient storage to dataset publication and long-term archiving.
This talk provides an overview of these services and situates them within a...
Go to contribution page -
Prof. Floris van Doorn (Hausdorff Center for Mathematics, University of Bonn), Prof. Hans-Martin von Gaudecker (ECONtribute: Markets & Public Policy, University of Bonn), Prof. Hugo Storm (PhenoRob, University of Bonn), Prof. Jan Hasenauer (Immunosensation, University of Bonn), Prof. Jan-Henrik Haunert (PhenoRob, University of Bonn), Dr Philip Bechtle (Color meets Flavor, University of Bonn), Prof. Sebastian Neubert (Color meets Flavor, University of Bonn)06/10/2026, 10:45
Research data management requirements differ substantially across disciplines, shaped by the type, scale, sensitivity, and lifecycle of the data produced. This session, part of the University of Bonn workshop on research data management and data science, brings together the University’s Clusters of Excellence to provide a practice-oriented overview of how data management is addressed in...
Go to contribution page -
Dr Dirk Barbi (University of Bonn), Dr Jan Martin Brockmann (University of Bonn), Jan Steiner (University of Bonn), Prof. Petra Mutzel (University of Bonn)06/10/2026, 14:00
After successfully bringing the HPC system Marvin into productive operation more than two years ago, nearly 1000 users from 180 working groups have used the centrally provided HPC resources for their research. To shape future development and to better align central services and offers in accordance with researchers’ needs, we propose establishing a sustained HPC User Forum. User surveys and...
Go to contribution page -
Dr Annika Tensi (University of Bonn), Ariane Larrat (University of Bonn)06/10/2026, 14:00
This interactive breakout session introduces the newly founded Open Science Community at the University of Bonn. We invite anyone interested to learn more about our ideas, ongoing activities, and opportunities to get involved.
Locally, the community brings together researchers across fields and career stages from the University of Bonn to exchange experiences on aspects such as Open Access,...
Go to contribution page -
Alexander von Pidoll (University of Bonn), Dr Florentin Schmidt (University of Bonn)06/10/2026, 14:00
How does cutting-edge research become real-world innovation? In this practice-oriented session, the Transfer Center enaCom shows how research data and innovative results can be transformed into commercial value. We will outline enaCom‘s services regarding knowledge and technology transfer available to researchers at the University of Bonn. Learn how enaCom supports funding applications with...
Go to contribution page -
Christian Bittner (University of Bonn), Janina Narloch (University of Bonn), Dr Sergej Zerr (University of Bonn)06/10/2026, 14:00
Research data management (RDM) in large collaborative projects is a complex and demanding task, requiring effective coordination across partners, disciplines, and infrastructures. This interactive session explores strategic approaches to making RDM sustainable and efficient, with particular emphasis on its role in developing strong and competitive funding proposals. We will discuss key...
Go to contribution page -
Prof. Richard McElreath (MPI for Evolutionary Anthropology, Leipzig)06/10/2026, 16:00
Taking inspiration from guerrilla warfare, I discuss a framework for managing scientific research that addresses the complexity of research while advancing goals of transparency and reliability. Real science is complex, there is no single scientific method, and the AI kids are talking about automation. But science is a chaotic network of theories, data, models, graphs, comparisons, summaries,...
Go to contribution page -
Dr Asad Asadzadeh (IGG), Dr Mahsa Moghadas (IGG), Dr Olabisi Obaitor (IGG), Dr Alexandre Pereira Santos (IGG)Poster
Research in urban sustainability, climate adaptation, and resilience increasingly relies on the integrating of heterogenous data sets, including Earth observation (EO) products, fieldwork and surveys, administrative records, crowdsourcing data, and qualitative stakeholder knowledge. Advances in EO, artificial intelligence (AI) and digital urban technologies have significantly expanded the...
Go to contribution page -
Dr Ewa Bres (Servicestelle Forschungsdaten, uni-bonn), Dr Sergej Zerr (Servicestelle Forschungsdaten, uni-bonn)Poster
Die Publikaton von Forschungsdaten nach den FAIR-Prinzipien ist heute ein zentrales Anliegen von Forschung, Politik und Förderinstitutionen. Mit bonndata betreiben wir seit drei Jahren ein Forschungsdatenrepositorium auf Basis von Dataverse, das sich erfolgreich etabliert hat: Rund 380 Datensätze, 23 Sub-bereiche und eine hohe Zahl der Downloads belegen die wachsende Nutzung. Einen besonderen...
Go to contribution page -
Carolin Uebermuth-Feldhaus (University of Bonn), Emil Korintenberg (University of Bonn), Heiko Schoof (INRES Crop Bioinformatics), Jeremy The-Hoffmanns (University of Bonn)Poster
Abstract
Go to contribution page
We analyze plant genome data with the aim of understanding genome evolution and linking genome information to plant traits, thereby also supporting breeding of better performing and more resilient crops.
Bioinformatics integrates sequence information, mainly from DNA sequencing, with high-throughput data for example from genomics and phenotyping. The data life cycle in... -
Lucia Vedder (University of Bonn), Julian Schneider (ZB MED), Gabriel Schneider (ZB MED)Poster
Agricultural research increasingly depends on the integration, standardization, and sustainable reuse of heterogeneous research data. Data are generated across disciplines such as agroecology, breeding, plant production, soil science, and vegetable production, and at spatial scales ranging from genes and plants to fields, landscapes, and the global level. The diversity of data types—including...
Go to contribution page -
Farzane Mohseni (Institute of Geodesy and Geoinformation, University of Bonn, Bonn, Germany)Poster
The DETECT (Regional Climate Change: Disentangling the Role of Land Use and Water Management)-Geonetwork data portal is a cornerstone of the CRC 1502 DETECT. This portal is designed to establish and maintain a centralized research data infrastructure. It provides open data services that strictly adhere to the FAIR data principles: Findability, Accessibility, Interoperability, and Reusability....
Go to contribution page -
Sundar Sripada Venugopalaswamy Sriraman (Geoinformation, IGG, University of Bonn)Poster
Data science in the agricultural domain faces unique data quality challenges. Agricultural datasets are often collected from sensors in the field, processed, published, and made accessible through Research Data Infrastructures (RDIs). The FAIRagro consortium, with more than 30 partners, is building a FAIR (Findable, Accessible, Interoperable, Reusable) research data management system for the...
Go to contribution page -
Jakob Maximilian Horz (Plant Biotechnology and Bioinformatics)Poster
Large comparative studies increasingly depend on the availability of consistent, high-quality public datasets. We encountered this challenge while investigating the evolution of plant genes. To maximize the number of species in our analysis, we surveyed the publicly available genome sequences of flowering plants in the largest database at the NCBI. While genome sequences of many species are...
Go to contribution page -
Jonathan Hecht (Institute of Geodesy and Geoinformation - Machine Learning in Agriculture), Dr Genc Hoxha (Institute of Geodesy and Geoinformation - Machine Learning in Agriculture)Poster
Machine Learning (ML) in agriculture is often approached from a model-centric perspective, where the primary focus lies on developing and optimizing model architectures and learning algorithms, rather than on the data itself. This is reflected, for example, in the common practice of training and evaluating ML models on static benchmark datasets with the goal of achieving high predictive...
Go to contribution page -
Lucia Vedder (University of Bonn)Poster
In computational biology, the availability and careful handling of high-quality digital data are essential for obtaining reliable and biologically meaningful results. In silico analyses depend on accurate sequence information, and many investigations begin with publicly available genome assemblies retrieved from resources such as the National Center for Biotechnology Information (NCBI;...
Go to contribution page -
Prof. Amelie Schiprowski (University of Bonn, Department of Economics), Dominik Wasielewski (University of Bonn, Department of Economics), Prof. Hans-Martin von Gaudecker (University of Bonn, Department of Economics), Dr Holger Gerhardt (University of Bonn, Department of Economics), Prof. Thomas Dohmen (University of Bonn, Department of Economics)Poster
As social scientists, economists investigate the determinants and consequences of decisions made by humans and by the institutions they create, across all areas of life. Given the breadth of their research, economists draw on a vast range of data sources, including their own surveys; laboratory, online and field experiments; publicly available datasets; administrative data; data collected by...
Go to contribution page -
Marko Jovanovic (uni-bonn)Poster
Managing modern medical and biomedical research data requires scalable, integrated, and compliant infrastructures that span the entire data lifecycle. At the Core Facility Research Data Management (University Hospital Bonn/Medical Faculty University of Bonn), we provide a comprehensive suite of digital services designed to support researchers, administrators, and students alike.
This...
Go to contribution page -
Amirhossein Nikfal (Forschungszentrum Jülich)Poster
Environmental and climate research increasingly depends on large, heterogeneous, and distributed datasets. Managing these data requires not only sufficient storage and computing capacity, but also reliable services for publication, discovery, access, provenance, and long-term reuse. The DETECT project addresses these requirements through a distributed infrastructure operated across...
Go to contribution page -
Prof. Floris van Doorn (Hausdorff Center for Mathematics, University of Bonn), Prof. Hugo Storm (PhenoRob, University of Bonn), Prof. Jan Hasenauer (Immunosensation, University of Bonn), Prof. Jan-Henrik Haunert (PhenoRob, University of Bonn), Dr Philip Bechtle (Color meets Flavor, University of Bonn), Prof. Sebastian Neubert (Color meets Flavor, University of Bonn)
Research data management requirements differ substantially across disciplines, shaped by the type, scale, sensitivity, and lifecycle of the data produced. This session, part of the University of Bonn workshop on research data management and data science, brings together the University’s Clusters of Excellence to provide a practice-oriented overview of how data management is addressed in...
Go to contribution page -
Hannah Miserre, Dr Tugbek KayaPoster
Modern biomedical research increasingly relies on large and heterogeneous datasets generated across different experimental platforms, research groups, and core facilities. Within our Research Training Group, these range from sequencing and spatial transcriptomics to proteomics, imaging, electrophysiology, and data derived from mouse models and human tissue. Managing such diverse and...
Go to contribution page -
Prof. Jochen Garcke (uni-bonn)Poster
The DKZ.2R (Rhine-Ruhr Center for Scientific Data Literacy) is one of eleven data literacy centers in Germany funded by the Federal Ministry of Research, Technology and Space (BMFTR). It is expected to be funded till the End of 2028.
The DKZ.2R offers researchers at different career stages a range of different services to improve their skills in dealing with research data. These include...
Go to contribution page -
Tim Adams (Fraunhofer SCAI)Poster
Data-sharing of clinical patient-level data has the potential to accelerate research but is strongly restricted by data protection regulations such as the GDPR. Synthetic data generation (SDG) is a promising alternative to direct data-sharing, but release of synthetic data requires evaluation of fidelity, privacy, and downstream utility. These assessments are non-trivial and often require...
Go to contribution page -
Ole Bialas (University of Bonn)Poster
Open educational materials for data analysis and programming often depend on datasets that need to remain accessible, well-documented, and reusable over time. At the iBehave open technology support (iBOTS), we develop such materials for neuroscience researchers. This raises several research data management challenges: How can datasets be made available through stable public references while...
Go to contribution page -
Fabrizio Musacchio (German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany)Poster
Computational research increasingly relies on custom software to process, analyse, and manage research data, yet most scientific software originates as project-specific analysis scripts developed to answer a particular research question. While such scripts are often sufficient for individual studies, the requirements for reproducibility, transparency, reuse, long-term maintenance, and...
Go to contribution page -
Shakunthala Natarajan (Institute for Cellular and Molecular Botany (IZMB), University of Bonn)Poster
Gene expression analyses are necessary to understand gene function and unravel the genetic basis of biological processes. Omics technologies like transcriptomics enable such expression analyses via techniques like RNA-Seq. Transcriptomic technologies have been subjected to a number of transition stages and have witnessed rapid advancements. Falling prices and enhanced throughput of short read...
Go to contribution page
Choose timezone
Your profile timezone: