Work

Data management in the DAM research mission mareXtreme and beyond

Year: 2025

Type: article

Abstract: The poster gives an overview of the data management approach in DAM research mission mareXtreme, which consists of four consortia: ElbeXtreme, METAscales, MULTI-MAREX and PrimePrevention. There is a great diversity of research data produced from the natural, social and engineering sciences, including data from environmental observations, laboratory experiments, modelling and interview data. These will serve to jointly develop new forecasting technologies and recommendations for action to improve risk management of marine extreme events and natural hazards. Annotation with metadata directly at collection of research data, e.g. using the O2A Registry of the AWI and/or the Ocean Science Information System (OSIS) of the GEOMAR will ensure reproducibility of results and streamline the archiving process at later stages. According to the DAM Research Data Guideline (Wiemer et al. 2021), high quality data will be archived and published in open access whenever possible in domain-specific trusted long-term repositories according to the FAIR principles (Wilkinson et al. 2016). These include e.g. PANGAEA - Data Publisher for Earth and Environmental Science (Felden et al. 2023), WDC-CLIMATE and the European Nucleotide Archive. Their visibility and findability will be enhanced by dissemination through the Marine Data Portal.

Source: Zenodo (CERN European Organization for Nuclear Research)

DOI: 10.5281/zenodo.15195335

Authors: Wittmann, Astrid C, Höring, Flavia, Wiemer, Gauvain, Felden, Janine, Glöckner, Frank Oliver, Metfies, Katja

Institutions: Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung, University of Bremen, Deutsche Allianz Meeresforschung, Constructor University

Language: English

Topic: Research Data Management Practices

Subfield: Information Systems

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

Funder: Bundesministerium für Bildung und Forschung

Awards: DAM Extrem: PrimePrevention - Vorhersage mariner biologischer Gefahren zur Verhinderung sozioökonomischer Auswirkungen, Leitantrag, Vorhaben: Entwicklung eines intelligenten Ozeanbeobachtungssystems zur Erkennung mariner biologischer Gefahren, Unterwegsdaten-2, Vorhaben: Aufbereitung und Kuration von Bathymetrie-, Unterwegs- und Forschungsmissionsdaten, Mitarbeit DAM-Portal