Linked Data

Risk Function Ontology

The Risk Function Ontology (RFO) is a new ontology describing risk management roles (posts) and functions.

Reading Time: 3 min.
The Risk Function Ontology The Risk Function Ontology is a framework that aims to represent and categorize knowledge about risk management functions using semantic web information technologies. Codenamed RFO codifies the relationship between the various components of a risk management organization. Individuals, teams or even whole departments tasked with risk management exist in some shape or form in most organizations. The ontology allows the definition of risk management roles in more precise terms, which in turn can be used in a variety of contexts: towards better structured actual job descriptions, more accurate description of internal processes and easier inspection of alignement and consistency with risk taxonomies (See also live version and white paper (OpenRiskWP04_061415)
Risk Model Ontology

Risk Model Ontology

Reading Time: 2 min.
Semantic Web Technologies: The Risk Model Ontology is a framework that aims to represent and categorize knowledge about risk models using semantic web information technologies. In principle any semantic technology can be the starting point for a risk model ontology. The Open Risk Manual adopts the W3C’s Web Ontology Language (OWL). OWL is a Semantic Web language designed to represent rich and complex knowledge about things, groups of things, and relations between things.
From Big Data, to Linked Data and Linked Models

From Big Data, to Linked Data and Linked Models

Reading Time: 5 min.
From Big Data, to Linked Data and Linked Models: The big data problem: As certainly as the sun will set today, the big data explosion will lead to a big clean-up mess How do we know? We only have to study the still smouldering last chapter of banking industry history. Currently banks are portrayed as something akin to the village idiot as far as technology adoption is concerned, and there is certainly a nugget of truth to this.