Digital Financial Reporting

This webcast is an excellent introduction to SKOS, Simple Knowledge Organization System. This is part of resource made available by the W3C for SKOS, which you can get to here.

This is a SKOS System Organization Primer.

The most important thing which I got out of this webcast was a better understanding exactly what SKOS brings to the table and the difference between a controlled vocabulary, a thesaurus, a taxonomy, an ontology:

• Controlled vocabulary. Basically a set of standard terms.  For example, "Yes" and "No" is a controlled vocabulary.  May seem odd; but one could also use "yes" and "no"; "true" and "false"; "yeah" and "nay"; you get the point.  A listing of postal codes for each of the states in the United States is a controlled vocabulary.
• Taxonomy. A taxonomy adds the notion of a hierarchy between the members of a controlled vocabulary.  For example, the terms "horse" and "cat" and "dog" are all types of "mammals".
• Thesaurus.  A thesaurus provides a specific type of relationship, a similar term, a broader term, or a narrower term.
• Ontology. An ontology allows you to define your own types of relationships; specific, explicit types of relationships rather than general "parent-child" type relationships.

So SKOS is the global standard way for defining controlled vocabularies, taxonomies, thesauri.  SKOS is also a standard way to build other ontologies, it seems.  SKOS leverages the standards RDF and OWL.  So basically, SKOS is a standard way of using the RDF and OWL standard to extend the SKOS framework.  So, SKOS is extensible in a controlled manner.

Why is this important for XBRL?  Two reasons.  First, this clearly shows the weakness of things like the "parent-child" relationship in the XBRL presentation relations.  "Parent-child" has no real meaning.  But, people building taxonomies (a) imply meaning, (b) imply meaning differently thus creating inconsistencies, (c) don't communicate that meaning to others using the XBRL taxonomy.  This is true of both the IFRS and US GAAP financial reporting taxonomies.

Second, the XBRL definition relations DO provide a mechanism for communicating meaning of relations.  For example, the XBRL Dimensions specification does exactly this, defining "all", "not-all", "hypercube-dimension", "dimension-domain", "domain-member" relations.  Now, these are more technically oriented-type relations; but they are explicit.  Other explicit type relations can be defined.  However, is XBRL the best mechanism for articulating more relationships?  Is SKOS better? Or OWL?

Project10X's Semantic Wave Report: Industry Roadmap to Web 3.0 & Multibillion Dollar Market Opportunities (this is a 34 page executive summary) lays out a vision for what "the web" will become/is becoming.

Things like XBRL, the US GAAP and IFRS taxonomies, and the move by the U.S. Securities and Exchange Commission and others to XBRL-based digital financial reports contributes to moving toward the Project10X vision. However, we are only getting started.

The Project10X executive summary, which I strongly encourage you to read, talks about things like "semantic user experience" and "semantic applications" and "semantic infrastructure". That summary and this Prezi presentation Semantics Overview provides graphic "From Searching to Knowing - Spectrum of Knowledge Representation and Reasoning Capabilities".  The graphic is shown below (click on it to see a larger version).  On the graphic I have made some annotations specific to XBRL, the US GAAP and IFRS taxonomies, and how those taxonomies will change, moving from "weak semantics" towards "strong semantics":

If you look at the graphic and notice terms such as semantics, model, ER model, topic map, RDF, UML, OWL, conceptual model, syntactic interoperability, semantic interoperability, and such that I have been mentioning on this blog for a number of years.

I could not have told you the difference between syntax and semantics seven years ago.  But I learned. Most people have a vision of the US GAAP and IFRS taxonomy as little more than a glossary or list of terms.  That will change over time.

Back to terms like "semantic applications". The Prezi uses the term "Smart Applications" and "Smart Data".  They describe this as:

• Knowledge is baked into the application
• New knowledge can be inferred
• Agility to adapt to ever-changing conditions
• Semi-automated data integration
• Machine intelligence

Maybe these are just buzz words, people trying to communicate ideas which are hard to explain.  But, the disclosure management systems being built will work this way.

There will be no magic involved here. The key to this semantic technology is the representation of knowledge in forms which both people and computers can understand.  Knowledge about how to do things, knowledge about something, etc.  Again, no magic.

In that chart above, my knowledge and imagination can only get me about half way up that graphic, about to the area of "First Order Logic".  But, I am learning more and more by going down the right path, realizing that we are building models rather than "tagging financial information".  Others are also realizing that "tagging" is not what should be going on.

Web 3.0 is not only inevitable, it is imminent. Are you doing the right things to prepare?