Digital Financial Reporting

I have put together what I am calling a Gentle and Cheap Introduction to XBRL-based Digital Financial Reporting. It is targeted at anyone who wants to understand what XBRL-based financial reporting is, how to do it with hands-on experience, starting from the very basics but providing a rock solid foundation upon which you can build.

Stay tuned for more information.

After you do the gentle introduction, build out your basic understanding.

I have been nurturing along what I call my "Proof" representation for a number of years.  I have improved the proof representation, see Proof Plus.  Of particular note is the Microsoft Access Database Application that you can use to generate the XBRL taxonomy schema, XBRL linkbases, XBRL formula, and XBRL instance.

What is useful about the Proof and Proof Plus representations is that they contain all of the information patterns you will run across in XBRL-based financial reports.  Why is that important?  Well, it shows you how to represent things like an adjustment, a variance, as well as common information patterns, and make all the report pieces fit together effectively.

Check it out!  Want to learn more? Try this blog post.

Logical English is explained by Robert Kowalski Akber Datoo in the following goal:

Goal: The ultimate goal of Logical English is to serve as a general-purpose computer language, which can be understood by a reader without any training in computing, logic or mathematics. It is inspired in part by the language of law, which can be viewed as a programming language that is executed by humans rather than by computers.

You can get more details that explain Logical English here in this presentation by Robert Kowalski.

Accounting is also a language, the language of business. While the language of accounting might not have inspired Logical English, it can definitely leverage it.  Others are creating languages for processing XBRL-based financial reports.  XULE, created by XBRL US, is one example. To understand XULE, see this guide and these examples provided by XBRL US.  Pacioli has its language. XBRL Formula has its language also. Sphinx is another proprietary language provided by CoreFiling.  There are many more general and specific approaches to processing machine-readable information.

The question is not whether IF this sort of processing will be the way things are done in the future in accounting, reporting, auditing, and analysis. Computational professional services is inevitable.  The question is: how to you get all this to work effectively.  Here is how I get all this to work today including proof THAT it actually works effectively. How will all this work in the future? Maybe Logical English or something like Logical English.

For more on this, consider having a look at the special purpose model that I have created for financial reporting: 

• Essence of Accounting
• Computational Thinking
• Computational Professional Services
• Logical Theory Describing Financial Report

Perhaps someone will distill all this down into a special purpose language for accounting, reporting, auditing, and analysis. Or, maybe a subset of Logical English will work.  The more specific the language the easier it is to create and use.  The more general, the harder it will be to use but the more powerful the language will be.  Striking the right balance between general and specific is important to get the right balance between "ease of use" and "power" and "reliability" and "maintainability".

Knowledge Graphs and Logical English, Video

Logical English, Github