Recommendations for Future Data Management Plans in Earth System Sciences

Publikation: Beitrag in FachzeitschriftKonferenzartikelBeigetragenBegutachtung

Beitragende

Abstract

Most research activities in Earth System Sciences (ESS) are data-driven. There is a growing need to establish innovative, cross-cutting data management and data analysis methods in ESS to support the collaboration of interdisciplinary research building on heterogeneous sources. Data management plans (DMPs) are structured documents that outline data handling and include for instance agreements on roles, specifications of data products, and definition of workflows. However, the structure of existing DMP templates is mostly designed for funder’s requirements and consequently address only the broad and interdisciplinary research community. Thus, these templates do lack (1) guidance on how to structure domain-specific information in a DMP – by providing domain-specific profiles, e.g. to harmonize the structure and improve the comprehensibility of DMP instances and (2) (linking into) tools enabling efficient management and reuse of information / sections of DMP instances. Therefore, we provide a concept of future DMP templates and address geo-domain-specific requirements, and the integration of DMPs into research data infrastructures. We recommend integrating structured provenance and quality information, using established concepts, and define a pathway to link tools into research data infrastructures, such that they foster automation of data management workflows and data reuse.

Details

OriginalspracheEnglisch
Aufsatznummer31
Seitenumfang7
FachzeitschriftAGILE: GIScience Series
Jahrgang2
PublikationsstatusVeröffentlicht - 2021
Peer-Review-StatusJa

Konferenz

Titel24th AGILE Conference on Geographic Information Science
UntertitelGeospatial Technologies: on the verge of change
KurztitelAGILE 2021
Veranstaltungsnummer24
Dauer8 - 11 Juni 2021
Ortonline

Externe IDs

ORCID /0000-0002-5181-4368/work/144671058
ORCID /0000-0002-3085-7457/work/154192821

Schlagworte

Schlagwörter

  • data management plans, research data management, provenance, research data infrastructures, quality information, data management plans, research data management, provenance