Knowledge Assembly

I ran across a new term, knowledge assembly, which is used to explain some important ideas related to the idea of a knowledge graph or knowledge graph system.  Similar terms are knowledge fabric or data fabric or data mesh or information mesh.  Allow me to explain.

Hetionet provides an example of what they refer to as a knowledge assembly.  Hetionet is a demonstration of connecting multiple databases of information (an “assembly") that contain data and meta data related to biomedicine.

A similar sort of knowledge assembly for a financial reporting scheme which is a subset of finance.  There is knowledge that is common to all financial reporting schemes such as the double entry bookkeeping model and the accounting equation. The logical model of a financial report is part of that assembly.  The conceptual framework of the financial reporting scheme is a part of the knowledge assembly.  The different reporting styles permitted by that financial reporting scheme is part of the knowledge assembly.  How to compute financial ratios used to analyze information reported per that scheme are part of the knowledge assembly. A specific economic entity's report model is another part of the assembly.  The entire SEC EDGAR system database of reports could be part of the knowledge assembly, or similarly the ESMA database of reported financial information.is another part of the assembly.

Not provided to the regulators unless called for by a lawsuit or something,  the accounting working papers and audit schedules that support the financial report model and financial report.  That part of the knowledge assembly supports the economic entity's financial report.

Validation and verification is used to assure quality of information within a knowledge assembly.  Everything must be consistent, complete, and precise; there are no contradictions in the system.

I provides examples of what amount to a knowledge assembly in my examples of different general purpose financial report creation schemes.  All of my examples use the same framework which I refer to as the Seattle Method.  That framework is heavily tested and is proven to work effectively.

My framework uses the global standard XBRL to represent the knowledge graphs within a standards-based knowledge graph system using a standards-based framework (Seattle Method, Standard Business Report Model) that make up the knowledge assembly.  Other machine readable representation approaches of such a knowledge assembly exist such as the Semantic Web Stack (RDF+OWL+SHACL and then use SPARQL to query information) or a graph database (using GSQL) or PROLOG (modern ISO standard PROLOG) or other such similar robust standards-based mechanisms.

A knowledge assembly is a set of knowledge graphs that, when processing, is seen as one unitary graph. A knowledge graph is a machine-readable structured representation of knowledge (semantics) related to a particular area of interest.  So a knowledge assembly is a machine-readable network of things and relations between things.  The things and relations are classified or grouped in helpful/useful ways.  Semantics is the science of giving meaning to data.  Knowledge assemblies are about semantics which is data in context, a.k.a. information. Knowledge = ontology (things and relations between things) + rules (assertions, restrictions, constraints).  A knowledge assembly can be explained using a logical theory or logical schema that verifies/validates the knowledge assembly.  Knowledge assembly terminology is grounded in the more approachable and innately understandable terminology of logic and philosophy, not the technical jargon/terminology of computer science.

What always seems to be necessary to work with some machine readable knowledge assembly is:

  1. Some sort of database to store the knowledge within.
  2. A logical model that is used to understand and process the information within that knowledge assembly.
  3. Some sort of reasoning engine or semantic reasoner or rules engine that understands the logical model (#2) and processes the information in the database (#1) to give you the answers that you need from the knowledge stored in the knowledge assembly.
This capability, when implemented effectively, is an incredibly useful tool.  This can be a general tool, think semantic spreadsheet or a specific tool for financial reporting.  But you need to make it work like a well oiled machine for the capability to be useful.


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