A user-centric metadata model to foster sharing and reuse of multidisciplinary datasets in environmental and life sciences

Metadata integrity in bioinformatics: Bridging the gap between data and knowledge

“…Ontology and terminology corrections: Another important aspect is highlighted by Beretta et al (2021): They bring to attention that interdisciplinary data sharing and the discovery and reuse of data face additional challenges due to discipline specific formats and different metadata standards as well as semantic heterogeneity [91] . Therefore, they introduce a user-centric and flexible metadata model, which is based on a common paradigm based the observation concept [91] . In accordance with the FAIR principles, they aim to reuse existing ontological and terminological resources and specify the semantics of the elements of the model with ontologies and vocabularies [91] .…”

“…Therefore, they introduce a user-centric and flexible metadata model, which is based on a common paradigm based the observation concept [91] . In accordance with the FAIR principles, they aim to reuse existing ontological and terminological resources and specify the semantics of the elements of the model with ontologies and vocabularies [91] . By adding semantics to metadata, the model enhances discoverability and semantic interoperability, which enables interdisciplinary research projects [91] .…”

“…In accordance with the FAIR principles, they aim to reuse existing ontological and terminological resources and specify the semantics of the elements of the model with ontologies and vocabularies [91] . By adding semantics to metadata, the model enhances discoverability and semantic interoperability, which enables interdisciplinary research projects [91] . Additionally, the model can utilize reasoning capabilities and for instance enhance a search query for a certain fish in the ocean by finding all datasets of the various species of the fish as well as datasets related to the habitat of the fish [91] .…”

“…By adding semantics to metadata, the model enhances discoverability and semantic interoperability, which enables interdisciplinary research projects [91] . Additionally, the model can utilize reasoning capabilities and for instance enhance a search query for a certain fish in the ocean by finding all datasets of the various species of the fish as well as datasets related to the habitat of the fish [91] . There are of course more solutions, for instance the tool Protégé ( https://protege.stanford.edu ) is an ontology editor equipped with the capability to be integrated with a reasoner for ontology consistency testing (e.g.…”