Example semantics literature

Markup

This part is mainly meant to be auxiliary to the writing process and likely to be largely dropped as the draft advances, using pointers instead to existing documents covering this ground. It is expected to be largely skipped by experts but to be vital for non-experts who attempt to understand the present document.

Controlled vocabularies

"16. Common vocabularies are the foundation for both human and machine communication (e.g. in data sharing, in automated workflows, data integration and analysis). By agreeing on a set of concepts and their definitions within a domain, a community of practice can share data and information unambiguously. Data integration and analysis critically requires semantic consistency as well as syntactic standardisation, the former being more challenging to achieve than the latter. Initially communities will accept a small controlled vocabulary - terms supported by human-readable text definitions. As terms are rarely independent of one another, the vocabulary list evolves into a thesaurus and, as formal relationships between terms are agreed, an ontology [66]. There are lessons to be learnt by looking elsewhere, for example, Google’s "Knowledge Graph" [67], the Unified Medical Language System (UMLS), medical informatics) [68], AGROVOC (agriculture) [69] and OBO (plant and animal phenotypes) stable of ontologies [70]. AGROVOC covers many of the terms relevant to biodiversity and is modular enough to be extended. There are other ontologies useful for capturing biodiversity data, such as the environment ontology, EnvO [71], and the more general DAML [72]. There is a pressing need for ontologies that span multiple communities, implying domains, and at present, such over-arching technologies do not seem to exist. Individual community ontologies...