SciData: a data model and ontology for semantic representation of scientific data

With the move toward global, Internet enabled science there is an inherent need to capture, store, aggregate and search scientific data across a large corpus of heterogeneous data silos. As a result, standards development is needed to create an infrastructure capable of representing the diverse natu...

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Vydáno v:Journal of cheminformatics Ročník 8; číslo 1; s. 54
Hlavní autor: Chalk, Stuart J.
Médium: Journal Article
Jazyk:angličtina
Vydáno: Cham Springer International Publishing 14.10.2016
BioMed Central Ltd
Springer Nature B.V
Témata:
Chemical research
Chemistry
Chemistry and Materials Science
Computational Biology/Bioinformatics
Computer Applications in Chemistry
Documentation and Information in Chemistry
Forecasts and trends
Information management
Jean-Claude Bradley Memorial Series
Research Article
Theoretical and Computational Chemistry
Science data
JSON-LD
Scientific data model
Semantic annotation
Ontology
RDF
ISSN:1758-2946, 1758-2946
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Shrnutí:With the move toward global, Internet enabled science there is an inherent need to capture, store, aggregate and search scientific data across a large corpus of heterogeneous data silos. As a result, standards development is needed to create an infrastructure capable of representing the diverse nature of scientific data. This paper describes a fundamental data model for scientific data that can be applied to data currently stored in any format, and an associated ontology that affords semantic representation of the structure of scientific data (and its metadata), upon which discipline specific semantics can be applied. Application of this data model to experimental and computational chemistry data are presented, implemented using JavaScript Object Notation for Linked Data. Full examples are available at the project website (Chalk in SciData: a scientific data model. http://stuchalk.github.io/scidata/ , 2016 ).
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ISSN:1758-2946
1758-2946
DOI:10.1186/s13321-016-0168-9