One Accountant's Perspective on Knowledge Graphs

Here is one accountant's perspective on knowledge graphs.  My overall philosophy and technique is summarized in the document Logical Digital Twins of Financial Reports which is an accumulation of about 20 years of trying to figure out knowledge graphs.  The methodology that I use summarized by the Seattle Method.  The tools that I use can be understood by using Auditchain Luca, and here is information relating to using that software. And finally, these use cases and test cases helps you understand what I can do with knowledge graphs.

Happy to take any feedback what improves that I am trying to do with knowledge graphs. Ping me on LinkedIn.

I have been told by others that I have a unique approach to knowledge graphs.  This blog post summarizes that approach which has a focus on high quality, leverages a high level model to manage complexity to make creating software approachable to business professionals, uses Lean Six Sigma principles and philosophies, and I come at this holistically.

Admittedly, I am what has been described as an "accidental taxonomist" (another term used is "dinker").   That could be a good thing in some ways and perhaps a bad thing in other ways.  My approach to figuring out knowledge graphs started by being very naïve but I think that I ended up at a better place because of that naiveite.  Allow me to explain.

My professional background is as a certified public accountant (CPA, also known as a CA).  I have a degree in business with a concentration in accounting, I started my career as an auditor with Price Waterhouse, and ended up becoming an accounting information systems consultant.  My career took a significant turn in 1998 when I introduced the idea of what became XBRL to my professional trade association, the American Institute of Certified Public Accountants (AICPA).  XBRL is now a global standard used around the world. The FASB publishes the taxonomy for US GAAP and the IFRS Foundation publishes an XBRL taxonomy for International Financial Reporting Standards (IFRS). The U.S. Securities and Exchange Commission (SEC) has been collecting financial reports from public companies using XBRL for over ten years and the European Single Market Authority (ESMA) has been doing the same for listed companies for I believe three years.

I learned to program a bit using VBA in Excel and then also used Microsoft Access and VBA to build all sorts of tools that would help me in my daily work.  Then my involvement in creating the Extensible Business Reporting Language (XBRL) technical specification and more importantly the XBRL taxonomies for US GAAP and IFRS I was thrust into a completely new world.

Literally, I could not tell you the difference between "syntax" and "semantics" in 2002.  But I was building XBRL taxonomies, things did not seem to work the way it seemed they should work, I did not understand why, and so I started trying to figure out why things did not work.  That lead me down a path which is documented in what amounts to my "lab notebook".

Listening to people like John Sowa, Barry Smith, Frank Puppe, Bob Kowalski, Harold Boley, William Kent, and others; I recognized that many others were trying to figure out the same sorts of things that I was trying to figure out.

The conclusions that I ended up reaching are instantiated in the documentation and examples that I have come up with.  If anyone thinks there is a better way; I am all ears.  I just want to figure all this out and apply it to financial accounting, reporting, auditing, and analysis.  At the same time I might suggest that what I have learned might be useful to others in other areas of knowledge.

Additional Information:

• Universal Technology of Accountability
• General Purpose Financial Reporting Support for XBRL
• Financial Data Transparency Act of 2022
• Mastering XBRL-based Digital Financial Reporting
• Two AASB 1060 Reports to Fiddle With
• Knowledge Hypergraphs: Enriching Triples with Structure