XBRL-based Digital Financial Reporting

One of the unique aspects of XBRL-based information is that the information is readable both by machines and by humans.  This article explains how that capability is achieved. Simple "Hello World" Example Here is a very simple " Hello World " example of XBRL-based information. (Here is the same report in the XBRL International test case format .) This is the same information rendered for editing a report as opposed to reading the report: Here is the same information in the form of a sharable viewer which you can use to have a closer look at this small Hello World! example. Here is the same information in the form of a set of HTML pages that also provide a means of viewing the information from within the machine readable XBRL files. How This Works So the rendering of the information that you see by multiple different software vendors in multiple different but all very human readable formats is not a one off.  This  capability is by design. Here is a comparison of

" The Threat of Inaccuracy ".   I wish that I could say I came up with that phrase, but I did not.  That phrase is from a whitepaper published by Fluree, Decentralized  Knowledge Graphs Enable Most Accurate Generative AI Results . Effectively, what that whitepaper says is, "Garbage in, garbage out." How is artificial intelligence going to deal with inaccurate information? Think about something.  Why would you expect information provided by artificial intelligence, generative or otherwise, to be useful if there underlying input information has inaccuracies? Things like workflow automation are a result of or consequence of the capability to remove inaccuracies from input information.  And notice that I am using the term "information" and not "data". People don't seem to be grasping that what is happening is a paradigm shift. "Data", "information", and "knowledge" are not the same thing.  Information is application

A couple of weeks back I had a "significant learning moment".  Someone drew the following diagram on a whiteboard and asked, "What does this mean?" Ask ten people and you will very likely get multiple different answers. Who is to say which answer is right and which is wrong?  Basically, if one does not specify what the above means with clarity, then those looking at that diagram are free to make assumptions as to the intent of the creator of the diagram. Let's take this example further.  What does the diagram below mean and how does the diagram below differ from the diagram above? And yet another diagram; how does what you see below differ from what you see above? So, let's keep going.  How does the diagram above differ from the diagram below?  Note that I have added an arrow from Thing 1 to Thing 2. And what about the difference between the diagrams above and below. Note that I added a label that describes the relation between Thing 1 and Thing 2. And now l

The semantics of first-order logic are agreed to and very well understood.  However, not everyone uses the same terminology to describe their understanding of first-order logic so there tend to be many different descriptions of first-order logic using different terminology.  There is no one agreed upon standard description of first order logic.  Current descriptions of first-order logic tend to be technical in nature.  None of those versions are both complete and explained in terms that a business professional can understand.  For example, current descriptions seem to enable the description of the necessary "privative" artifacts and imply the notion of higher level artifacts, but don't explicitly provide common higher level artifacts.  (An example of defining higher level artifacts is provided by Atomic Design Methodology .) And, therefore, I have to come up with my own set of terminology and description to describe what I am trying to describe in terms that are approacha

Auditchain Luca is worth checking out if you have never checked it out before or if you have seen it months ago but have not been following it's progress.  To understand the fundamentals of Auditchain Luca, check out the getting started information . What I am going to do is provide examples, somewhat of a "showcase", of XBRL-based digital reports below using a new capability of Auditchain Luca which is the ability to share a report and/or report model.  This capability is just getting going, lots of really good ideas are in the works. For each bullet below, click on the link for the item in the bulleted list to go to the viewer and have a look at the XBRL-based digital report and report model human readable rendering.  This is not the XBRL; it is the information that has been conveyed by the XBRL. Yes, most of the examples are financial reporting related.  I am an accountant and that is the type of information I tend to work with; thus the financial reporting related exa

Still brainstorming ways to a explain model-based financial report.  This approach is inspired by a way someone is describing something else that I was introduced to: ( larger view ) On the one hand, something like a UML model is clearer and more precise, but on the other hand the typical business professional does not know UML.  This model of the pieces of a financial report is another approach. Additional Information : Practical, Simple Explanation of a Logical System (Draft 1) GIST - A Minimalist Upper Ontology Representing a Logic System (a.k.a. Knowledge Graph) Using Global Standard XBRL Modern Accountancy Foundation (Understanding of XBRL) XBRL is an Extra Fancy Knowledge Graph

A named graph is a concept in the Semantic Web architecture where a set of Resource Description Framework ( RDF ) statements (a graph) are identified using an internationalized resource identifier ( IRI ). This allows for descriptions to be made about that set of statements, such as context, provenance information, or other metadata. In an RDF database, a named graph is essentially a subset of data that has been given a unique label (referred to as a name). A graph database can contain multiple named graphs alongside its default graph, and each fact can be present in or absent from any graph. Named graphs form a patrician of information that can be used. Named graphs are useful for managing sets of RDF data within an RDF store, enabling fine-grained access control, and managing chains of provenance for pieces of data. Additional Information : Named Graphs (ScienceDirect) Graph Search Algorithms: Developer's Guide Named Graphs, Chapter 5. Data Management Patterns Wolfram, Nonahed

Stantec is a Canadian company that is regulated by the SEC and submits a 40-F. SEC Filing Page Interactive Data (SEC Rendering of raw XBRL) Inline XBRL  BLOCKS of Information in report (197 blocks)  (Example of SAME INFORMATION represented as  Level 3 Disclosure Text block  |  Level 4 Detail ) Facts (1741 in total) Raw XBRL (XBRL instance, autogenerated from the Inline XBRL by the SEC) Report Model only (XBRL taxonomy schema and linkbases, not the XBRL instance) Report Model rendered as HTML (Simple view of report model) Report Model, XBRL converted to XML Infoset (readable as a tree) Auditchain Pacioli validation report from validating raw XBRL on IPFS All SEC filings Financial reports on company website