Workflows for marine metadata and data management

Data managers regularly face the need to manually replicate the same sequence of steps to ensure (meta)data edition, update and publication in different infrastructures. For example fisheries datasets are often time series of spatial catches with biological observations and, as such, can be disseminated in spatial data infrastructures but are also valuable species occurrences for biodiversity research which can ultimately be assigned a DOI in various data repositories (eg GBIF, Zenodo, Pangaea…). Obviously, with the increasing volume of data management tasks, there is no reason to waste time by manually editing the same metadata elements (eg Title, abstract, spatial or temporal extent..) in different infrastructures complying with different standards. Multiple tasks can indeed be automated through APIs and orchestrated as steps of workflows which can be fed by various sources.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2024-11-21
DOI
https://doi.org/10.5281/zenodo.14198689
Primary Topic
Research Data Management Practices
Type
article
Field-Weighted Citation Impact
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article

Workflows for marine metadata and data management

Zenodo (CERN European Organization for Nuclear Research)
Research Data Management Practices
article

Workflows for marine metadata and data management

article en

Abstract

Data managers regularly face the need to manually replicate the same sequence of steps to ensure (meta)data edition, update and publication in different infrastructures. For example fisheries datasets are often time series of spatial catches with biological observations and, as such, can be disseminated in spatial data infrastructures but are also valuable species occurrences for biodiversity research which can ultimately be assigned a DOI in various data repositories (eg GBIF, Zenodo, Pangaea…). Obviously, with the increasing volume of data management tasks, there is no reason to waste time by manually editing the same metadata elements (eg Title, abstract, spatial or temporal extent..) in different infrastructures complying with different standards. Multiple tasks can indeed be automated through APIs and orchestrated as steps of workflows which can be fed by various sources.

Zenodo (CERN European Organization for Nuclear Research)
Marine Biodiversity Exploitation and Conservation (FR)
Openalex Percentile: Top 35%
Research Data Management Practices
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