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Data Ontology: Why is it Important?

by Stan Jin & Tom Spouse 

FinTech & RegTech are about Data, Data, and more Data. It all starts with Data and it all ends with Data. As serious advocates for technologies like Blockchain and Artificial Intelligence (AI)/Machine Learning (ML), Prospect 33 is foremost concerned with the quality of data that will feed the system. No matter the potential for any new technology to deliver successful projects, without foundationally clean data, effectivity will be lost.

Data is a corporate asset and it must be identified, protected, used, and managed consistently throughout its life-cycle. It must meet the required levels of information quality and maintain alignment with specific governance principles, such as:

  • Enterprise data must be maintained close to source
  • Enterprise data must be traceable and reconcilable>
  • Enterprise data must be accessible
  • The enterprise data management framework must be maintained and supported
  • Essential data-related documentation must be recorded, maintained, available, and utilised
  • Accountability and responsibility must be clearly established for enterprise data

But what is Ontology?

Ontology provides the definition of vocabulary and specifies the meaning (semantics) of terms within systems. As we are all aware, the data we have on-hand is massive, complex, and (if we are to be perfectly honest) a total mess. Ontology is about defining “what is what” and understanding “where what goes” in a practical and usable way.

At the core of ontology is taxonomy, which, if we remember grade school science, is the arrangement of a system in a hierarchical order on the basis of shared attributes (kingdom > phylum > class > order > family > genus > species – points to anyone who remembered that!).

Data, when standardised and arranged in a similar manner, not only becomes understandable, but usable.

In an enterprise setting, Data Ontology ensures that business rules and data are unambiguous, unified, linked, and most importantly, readable both by humans and machines. Once applied, it opens up the door for innovative and transformative technologies to truly maximise its potential for effectivity.

As a very high-level introduction to what Data Ontology entails, it begins with 3 main languages:

  • Resource Description Framework (RDF): specifies the relationship between data, and is a flexible data model for linking data across global systems
  • Resource Description Framework Schema (RDFS): specifies the relationship between patterns to reach simple inference
  • Web Ontology Language (OWL): specifies more complex relationships between patterns based on description logics, and is more a expressive representation of knowledge, however, it is hard to scale

We believe that Data Ontology is essential to future-proof every financial institution for the onslaught of the demand for new technologies to be integrated into legacy systems, be it to optimise operations or cost-effectively deliver regulatory compliance requirements.

In the financial services industry, the Enterprise Data Management Council’s Financial Industry Business Ontology (FIBO) is the industry standard resource for the definitions of financial business applications and the ways they relate to each other. In a nutshell, FIBO is a collection of business conceptual ontologies. FIBO continues to gain acceptance and traction by global financial institutions and regulatory agencies.

Not wishing to dive into too much of a rabbit hole, you may be interested in understanding a little more about Ontology Engineering, which is often referenced as Knowledge Graphs. It is the design & creation of Ontologies, as well as the tools and methods for utilising Knowledge Graph. Other by-products of Ontology Engineering are innovations such as Semantic Technology and Cognitive Computing (AI).

A portion of Prospect 33’s Future Leaders Programme is focused on the mentorship of our cohorts in Data Ontology, facilitated by Stan Jin. Regardless of role, we believe that possessing even an elementary knowledge of Data Ontology is vital for any individual looking to accelerate their career within the financial services industry.

To learn more about our Data Ontology and our Future Leaders Programme, click here.

P33 Global Data Lab