Information Theory Patterns

Per Wikipedia, informatics is used synonymously to mean information systems, information science, information theory, information engineering, information technology, information processing, computer science, information and computer science, computer science and engineering, and "modern computer science".

Huh.

Ok, let me look at information theory.  Information theory relates to the transmission, processing, extraction, understanding, and utilization of information.  Information theory relates to the reduction of uncertainty in that endeavor; maximizing "signal" and reducing or removing "noise" which might cause the signal to be misinterpreted.

The following seem to be the logical patterns within information theory:

  • Logical statements: Logical statements are the building blocks of information.  Information is comprised of some set of true logical statements. For example, "The sky is blue." is a logical statement. (Note that a statement is a type of sentence. Not all sentences are statements; for example, "What time is it?", which is a question, is not a statement.)
  • Logical connectors: Logical connectors enable compound or complex logical statements to be created. For example, "AND" and "OR" and "NOT" and "IF...THEN" are connectors that let you build infinitely compound/complex logical statements.
  • Logical associations: Logical statements can be associated to other logical statements forming a relationship.  There are three broad categories of associations. (Note that a logical association is a type of logical statement.)
    • "Is-a" associations (a.k.a. generalization-specialization, type-subtype, class-subclass).  For example, "Cash and cash equivalents" is a type of Asset.
    • "Has-a" associations (a.k.a. whole-part, mereology). For example, "A balance sheet has part "Assets".
    • "Property-of" (a.k.a. trait, quality, attribute).  For example, "Assets has a property of balance type which is always "debit".
  • Logical assertions: A logical assertion (a.k.a. constraint, restriction, rule) is another category of logical statement.  For example, "Assets = Liabilities + Equity" is an assertion.
  • Logical structures: A logical structure is some set of logical statements (including logical associations) that go together for one reason or another.
  • Logical proof: A set of logical statements and logical associations (which is actually a type of logical statement) forms a theory.  A logical proof is used to make certain that there are no contradictions or inconsistencies within the set of logical statements that forms the logical theory. A logical proof demonstrates or establishes that all the logic within the system (set of logical statements which constitutes a logical theory) is working as would be expected.
  • Logical reasoning: Logical reasoning used to process the logical statements and arriving at a conclusion, a logical proof, in a rigorous way.  There two broad categories of logical reasoning: deductive and non-deductive.  Deductive reason is always certain. Non-deductive reasoning, which can never be certain because it is based on probability, but it can be helpful.
  • Machine-readable representation (physical format, technical format): Humans could read all of the logical statements and manually establish a logical proof of the information.  But to have a machine process the logical statements, you need to represent the logical statements in some form that the machine can understand.
All of the above can be done by humans. Automation is the process of getting a smart machine, such as a computer, to perform that processing.  Informatics is a set of philosophies, principles, and techniques to performing that processing.  In summary, information theory combines logic, mathematics, and computation to understand how information flows and can be effectively communicated!

Additional Information:

Comments

Post a Comment

Popular posts from this blog

Getting Started with Auditchain Luca (now called Luca Suite)

Image
(Note that a newer, production version as opposed to only the development version , of Luca Suite is available) The Innovator's Dilemma points out that disruptive innovations often look like toys that are doing everything wrong. Auditchain Luca , which is part of the Auditchain Suite , is a unique approach to creating a knowledge graph .  To experience using Auditchain Luca, have a look at the Getting Started with Auditchain Luca instructions. Be sure to grab the Excel and JSON import files used for this getting started exercise.   This getting started exercise uses one of several different approaches to getting information into a tool for constructing and viewing professional quality knowledge graphs .  Additional getting started guides will be made available over time. Auditchain Luca might not make sense to you if you don't understand the paradigm shift that is occurring and if you have not shifted your mental map. For the next step in your journey, consider t...
Read more

Relational Knowledge Graph System (RKGS)

Image
Relational Knowledge Graph System (RKGS) is an interesting idea that combines the relational paradigm and the knowledge graph paradigm.  This documentation, Why RKGS , explains the idea. This gets even more interesting with the notion of "relational AI".  RelationalAI is described as follows by the company of the same name, Relational.ai : “RelationalAI is a cloud-based relational knowledge graph management system, with state of the art probabilistic processing and declarative reasoning at scale to make developing Data Applications a superpower for your business.” This notion of knowledge graphs represented in relational databases fits into my belief that knowledge graphs have two aspects: the expression SYNTAX and the logic of what is expressed or SEMANTICS. While the LOGIC of a knowledge graph is always the same regardless of technical syntax used to express that logic; there are many, many different technical syntaxes that can be used to represent a knowledge graph. There...
Read more

Professional System for Creating Financial Reports Leveraging Knowledge Graphs

Image
The document Professional System for Creating Financial Reports Leveraging Knowledge Graphs explains a new approach, a new paradigm, for creating financial reports.  The document provides a practical, nontechnical description of a professional system for creating provably high-quality financial reports where the report creator is using financial reporting schemes (such as US GAAP and IFRS) where report creator is permitted to modify the report model which leverages global standard knowledge graphs represented using XBRL. This new approach is useful, it is highly novel, and the details were highly complicated to pull together.  This is certainly not an incremental innovation.  It is definitely a disruptive innovation and it could very well be a foundational innovation. You can decide which for yourself. Foundational technologies have two dimensions that need to be considered: novelty and complexity. The more novel the technology is, the more effort needed to ensure users ...
Read more