Risk Data Ontology
A Risk Data Ontology is a framework that represents and categorizes knowledge about risk data using semantic information technologies (Semantic Web). In principle any semantic technology can be the starting point for defining a risk data ontology.
A Risk Data Ontology is a component of the overall Risk Data Standards of an organization or ecosystem. It is a more advanced and flexible information structure than a Risk Data Taxonomy which focuses on the classification of risk data (a taxonomy can be embedded in an ontology but the later may have richer information about relations between concepts, constraints etc.)
The availability of an ontology means that knowledge expressed through this specification can be exploited by computer programs, e.g., to verify the consistency of that knowledge or to make implicit knowledge explicit.
The Open Risk Manual adopts the W3C frameworks and tools
- The W3C Web Ontology Language (OWL) is a Semantic Web language designed to represent rich and complex knowledge about things, groups of things, and relations between things. OWL is part of the W3C’s Semantic Web technology stack, which includes RDF, RDFS, SPARQL, etc
- OWL documents, known as ontologies, can be published in the World Wide Web and may refer to or be referred from other OWL ontologies.
This article documents a specific Risk Data Ontology (RDO) as embedded and used in the Open Risk Manual and associated Open Source / Open Risk Data Projects. The RDO Ontology aims to be an interface between the domain of Risk Management, in particular Quantitative Risk Management and more generic / detailed data ontologies applicable to e.g. Credit Risk data or Operational Risk data.
The key elements of the ontology are:
- Classes (owl:Class) are the main concepts handled by the RDO ontology. The choice of classes defines the scope of this knowledge domain.
- Object properties (owl:ObjectProperty) relates individual instances of two OWL classes.
- Datatype properties (owl:DatatypeProperty) relates individuals (instances) of OWL classes to literal values.
Risk Data Ontology
In the context of the RDO Risk Model Ontology this entry constitutes an annotation of the Ontology itself
- Risk Data, is the core class that is the subject of the ontology, with its four core components:
RDO Object Properties
Related Data Ontologies
Risk data, being a specific type of data are already covered by a range of well developed ontologies that cover data governance, data modelling etc
- The DCAT vocabulary, an RDF vocabulary designed to facilitate interoperability between data catalogs published on the Web
- The Data Cube vocabulary enabling the publishing of multi-dimensional data, such as statistics, on the web
- SDMX, the global initiative to improve Statistical Data and Metadata eXchange
- The PROV Ontology (PROV-O) expresses the PROV Data Model using the OWL2 Web Ontology Language (OWL2) [OWL2-OVERVIEW]. It provides a set of classes, properties, and restrictions that can be used to represent and interchange provenance information generated in different systems and under different contexts