BLOG: Digital Financial Reporting
This is a blog for information relating to digital financial reporting. This blog is basically my "lab notebook" for experimenting and learning about XBRL-based digital financial reporting. This is my brain storming platform. This is where I think out loud (i.e. publicly) about digital financial reporting. This information is for innovators and early adopters who are ushering in a new era of accounting, reporting, auditing, and analysis in a digital environment.
Much of the information contained in this blog is synthasized, summarized, condensed, better organized and articulated in my book XBRL for Dummies and in the chapters of Intelligent XBRL-based Digital Financial Reporting. If you have any questions, feel free to contact me.
Entries from June 14, 2020 - June 20, 2020
Enterprise Knowledge Graph Principles
The Enterprise Knowledge Graph Foundation has published a set of principles for an Enterprise Knowledge Graph (EKG).
A knowledge graph is one approach to storing information within a knowledge base. The article, What is a Knowledge Graph? is an explanation of what a knowledge graph is (and isn't) and the difference between a knowledge base and a database. You can download the knowledge base GraphDB here. This is a quick start guide for GraphDB. Or, you can fiddle around in the Neo4j Sandbox here.
This is an excellent article that explains why graph databases are the future of databases. This is excellent information aboug GSQL which is a graph query language.
Ontology + Data = Knowledge Graph
A Brief History of Knowledge Graph's Main Ideas: A Tutorial
Introduction to Knowledge the Graph
Creating a small knowlege graph video series:




Explore!
This blog post makes you aware of the Explore example application that I am making available that helps those interested understand how to extract and analyze information from XBRL-based financial reports. Go to the Explore web page to read the documentation, download the database application and Excel information extraction tools, etc.
Read the documentation to get a good overview of what the database application is and does. Or, watch this video walk through.
Essentially, there are 109,778 financial reports from 3,600 public companies that use 17 different US GAAP reporting styles to submit information to the SEC.
This is an excellent starting point (i.e. training data) that can be used to create machine learning applications related to US GAAP financial reporting. I might create a similar set for IFRS. There is lots of VBA code that helps you understand the proper steps of extracting information from XBRL-based reports. Don't make the mistake of focusing on the actual code (i.e. I am not really a very good programmer); focus on the necessary steps to be effective.
Note that if you want to update the database with additional reports, you can use the SEC's RSS feed of reports to do so.
If you cannot open a Microsoft Access database but you want the data, email me and I can get you a copy of the data in Excel.



