FAIR data representation in times of eScience: a comparison of instance-based and class-based semantic representations of empirical data using phenotype descriptions as example

BACKGROUND: The size, velocity, and heterogeneity of Big Data outclasses conventional data management tools and requires data and metadata to be fully machine-actionable (i.e., eScience-compliant) and thus findable, accessible, interoperable, and reusable (FAIR). This can be achieved by using ontolo...

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Detalles Bibliográficos
Autor principal: Vogt, Lars
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8613519/
https://www.ncbi.nlm.nih.gov/pubmed/34823588
http://dx.doi.org/10.1186/s13326-021-00254-0

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8613519/
https://www.ncbi.nlm.nih.gov/pubmed/34823588
http://dx.doi.org/10.1186/s13326-021-00254-0

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