ArticleEcology and evolution2021
Metadata Made Easy: Develop and Use Domain-Specific Metadata Schemes by following the dmdScheme approach.
Article in Ecology and evolution, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
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Who cites it
2 citing papers in PubMed.
- The FAIRSCAPE AI-readiness Framework for Biomedical Research.bioRxiv : the preprint server for biology · 2026Article
- Metadata Made Easy: Develop and Use Domain-Specific Metadata Schemes by following the dmdScheme approach.Ecology and evolution · 2021Article
Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Metadata plays an essential role in the long-term preservation, reuse, and interoperability of data. Nevertheless, creating useful metadata can be sufficiently difficult and weakly enough incentivized that many datasets may be accompanied by little or no metadata. One key challenge is, therefore, how to make metadata creation easier and more valuable. We present a solution that involves creating domain-specific metadata schemes that are as complex as necessary and as simple as possible. These goals are achieved by co-development between a metadata expert and the researchers (i.e., the data creators). The final product is a bespoke metadata scheme into which researchers can enter information (and validate it) via the simplest of interfaces: a web browser application and a spreadsheet.We provide the R package dmdScheme (dmdScheme: An R package for working with domain specific MetaData schemes (Version v0.9.22), 2019) for creating a template domain-specific scheme. We describe how to create a domain-specific scheme from this template, including the iterative co-development process, and the simple methods for using the scheme, and simple methods for quality assessment, improvement, and validation.The process of developing a metadata scheme following the outlined approach was successful, resulting in a metadata scheme which is used for the data generated in our research group. The validation quickly identifies forgotten metadata, as well as inconsistent metadata, therefore improving the quality of the metadata. Multiple output formats are available, including XML.Making the provision of metadata easier while also ensuring high quality must be a priority for data curation initiatives. We show how both objectives are achieved by close collaboration between metadata experts and researchers to create domain-specific schemes. A near-future priority is to provide methods to interface domain-specific schemes with general metadata schemes, such as the Ecological Metadata Language, to increase interoperability.
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Registered trials
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