Ontologies: Relational Vocabularies

Data managers, scientists, and others in the marine science community are used to working with controlled vocabulariesA managed list of terms. In the context of vocabularies, management typically includes careful selection of terms, maintenance of terms over time (i.e. addition, deprecation, modification), and presentation of the vocabulary in an accessible format. Related Guide, even if they know them by another name. After all, anyone working with a set of data described using an agreed-upon set of terms has been exposed to controlled vocabulary usage. For many purposes, basic controlled vocabularies are a good tool: they are often simple to develop, can be passed between a small community of users, and are easy to store, visualize, and access.

However, as projects and users require more data interoperabilityThe ability of two or more information systems to exchange metadata with minimal loss of information. Related Guide, more advanced data comparison, and better discoveryUse of metadata values or vocabularies to find metadata or data sets. Related Guide, the limitations of simple vocabularies become more apparent. OntologiesA type of relational controlled vocabulary, which provides for categories, relationships, rules and axioms among metadata elements. Typically a hierarchy of classes and terms, an ontology is a machine-readable way of relating metadata terminology. Related Guide provide additional functionality to meet these new challenges. Ontologies improve on simple vocabularies by allowing relationshipsConnections between metadata terms within a vocabulary. These relationships can connect terms by scope, provenance, or other well-defined criteria. between terms to be defined (e.g. "Sea Surface Temperature" is a kind of "Temperature"), and by providing a way for rulesIn the context of crosswalking, rules are a process which define how to deal consistently with complex element mappings. Rules are created and applied during the mapping of elements from the source schema to the target schema, when one-to-one relationships between schema elements do not exist. Related Guide or properties to be defined for terms (e.g. an "estuary" must have a salinity of <33 psu). Semantic technologySemantic technology provides the meaning behind data alongside the data itself. Software written to enable semantic technology explicitly separates the underlying code, data input and output, and data meaning from one another., including the use of ontologies, paves the way for data interoperability, advanced search and discovery, and "machine reasoning"in a way that simpler technologies cannot support.

In this guide, we will explore the nature of ontologies and their applicability in marine science. First, we will explain exactly what an ontology is, including how it differs from a standard controlled vocabulary. Then we discuss the importance of ontologies, including the various strengths of using ontologies. We also provide a brief overview of the various technologies which form the foundation of ontology work, including the RDFResource Description Framework and OWLWeb Ontology Language formats. Finally, we discuss various methods of developing and providing ontologies, as well as working with existing ontologies.