Dagstuhl-Seminar 25381
Open Scholarly Information Systems: Status Quo, Challenges, Opportunities
( 14. Sep – 19. Sep, 2025 )
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Organisatoren
- Hannah Bast (Universität Freiburg, DE)
- Guillaume Cabanac (University of Toulouse, FR)
- Paolo Manghi (CNR - Pisa, IT)
- Jian Wu (Old Dominion University - Norfolk, US)
Koordinator
- Marcel R. Ackermann (Schloss Dagstuhl - Trier, DE)
Kontakt
- Michael Gerke (für wissenschaftliche Fragen)
- Susanne Bach-Bernhard (für administrative Fragen)
Over the past 30 years, a rich ecosystem of scholarly information systems that openly provide their services to the scientific community has developed. Examples of such systems are aggregators of metadata, such as DBLP, OpenCitations, OpenAIRE Graph, OpenAlex, ORKG, aggregators of full texts such as Semantic Scholar, CiteSeerX, CORE, data repositories, such as arXiv.org, Figshare, Zenodo, Dataverse, and ID authorities, such as ORCID, ROR, Crossref, DataCite.
In this interdisciplinary Dagstuhl Seminar, we want to bring together practitioners from this ecosystem as well as researchers who investigate related research questions or who rely on these systems in their research. This Dagstuhl Seminar is the first of its kind. It will provide a unique opportunity for dialogue, sharing insights, building new networks, and fostering collaboration. In particular, we aim to achieve the following outcomes:
Education about the status quo: Few participants will be familiar with the full ecosystem, which has developed fast in recent years. Just knowing which systems and services exist in the meantime and having heard about them from the creators or key people will be very valuable for all participants.
Bridging the gap between researchers and system providers: We are confident that both researchers on key topics and key people from the various systems will be present at the seminar. We expect that the system’s people will learn about new research relevant to their systems. Vice versa, researchers will learn which problems are relevant in practice, and get inspiration for new practical problems to work on.
Identifying common tasks: We expect that several of the tasks will lead to the identification of common tasks and potentials for synergies between projects. As a minimum, new network connections will form. We also expect that new collaborations or joint initiatives will form, for tackling challenges of common interest.
Klassifikation
- Digital Libraries
- Information Retrieval
- Machine Learning
Schlagworte
- scholarly information systems
- scholarly big data
- knowledge graphs
- semantic search
- artificial intelligence