Data Science Symposium 2026

Session

Session 2.1 - AI-ready data as Infrastructure (Talks)

9 Oct 2026, 09:00

5-1.214 - ATLANTIK / ATLANTIC - Linke Seite – Großer, unterteilbarer Konferenzraum (GEOMAR - Standort Ostufer / GEOMAR - East Shore)

43. ODIS2ODV: Bridging Ocean Data Discovery and Scientific Analysis through FAIR and AI-Ready Metadata

Sebastian Mieruch

09/10/2026, 09:00

Talk

The Ocean Data Information System is an international and diverse federation of data systems coordinated through the International Oceanographic Data and Information Exchange of UNESCO’s Intergovernmental Oceanographic Commission, sharing data and information about their holdings and capabilities over the Web using linked open data norms. “Nodes” in the ODIS Federation share metadata using...

33. Elbe River Basin Water Body Knowledge Graph: Integrating Modern and Historical Data

Laura Schild (Alfred-Wegener-Institut, Potsdam)

09/10/2026, 09:15

Talk

Climate and land-use change are reshaping the relationships between hydrological processes, water quality, and biodiversity in river ecosystems. Effective adaptation requires an integrated understanding of these interactions, yet water management often relies on fragmented, localized, and sector-specific datasets, potentially leading to suboptimal decisions. In particular, hydrological and...

4. HMG NetCDF 2.0 – Building a Community-Driven Metadata Guideline for FAIR and AI-Ready NetCDF Data

Björn L. Saß (Helmholtz-Zentrum Hereon), Dr Romy Fösig (Karlsruhe Institute of Technology)

09/10/2026, 09:30

Talk

NetCDF is one of the most widely used scientific data formats in E&E sciences, yet metadata quality, completeness, and interoperability remain highly heterogeneous across institutions, disciplines, and data infrastructures. While standards such as CF Conventions, ACDD, and DataCite provide important foundations, their implementation often varies significantly, limiting data reuse,...

42. Marine Data - Research Vessels: AI-readiness underway

Marcus Krüger (Deutsche Allianz Meeresforschung)

09/10/2026, 09:45

Talk

What makes research data AI-ready? AI-readiness is often considered a property of individual datasets. For heterogeneous observational data, however, it emerges from the infrastructure and processes connecting data acquisition, metadata, quality control, processing, publication and reuse.
The Marine Data – Research Vessels project (formerly “Underway” Research Data), coordinated by the German...

39. FAIR enough – a Data Journey from Observations to Analysis and Archives

Nico Harms (AWI), Noemi Ruegg (AWI)

09/10/2026, 10:00

Talk

The Earth System sciences are disciplines that generate tremendous and ever-growing amount of data in many heterogeneous forms. Thus, tools and frameworks to manage these data are becoming increasingly important in order to promote, foster, and safeguard the “FAIR Guiding Principles for scientific data management and stewardship” [1]. The O2A data flow framework [2] presents a holistic...

45. Beyond FAIR: A Framework for AI-Ready Data in Earth and Environmental Science

Tobias Weigel (Helmholtz-Zentrum Hereon)

09/10/2026, 10:15

Talk

The increasing adoption of artificial intelligence (AI) and machine learning (ML) in Earth and environmental sciences places new demands on scientific data infrastructures that extend beyond traditional FAIR (Findable, Accessible, Interoperable, Reusable) principles. While FAIR provides a strong foundation for data sharing and reuse, it does not fully address requirements such as provenance...