What does this mean?
Humans should be able to exchange and interpret each other’s data (so preferably do not use dead languages). But this also applies to computers, meaning that data that should be readable for machines without the need for specialised or ad hoc algorithms, translators, or mappings. The main goal of this principle is to provide a “common understanding” of digital objects by means of a language for knowledge representation to be used to represent these objects.
The principle I1 defines some properties that these languages should have. The chosen language should have a formal specification, i.e., the language’s syntax and grammar are defined in a precise way. Another requirement is that the knowledge representation language specifications should be shared and accessible so others can read the specifications and learn the language. Finally, in other to support interoperability, the language should be designed to be used in more than one scenario.
- The RDF extensible knowledge representation model is a way to describe and structure datasets. You can refer to the Dublin Core Schema as an example.
- JSON LD
- See example data models for Predicted gene-disease associations from text mining and Tissue gene expression.
- See data models from EBI in the ‘documentation’ links on this page http://www.ebi.ac.uk/rdf/
Links to Resources