Seattle Method

Retrofitting semantics onto an existing symbolic systems is problematic, but it's probably unavoidable. Almost all organizational knowledge already exists in symbolic form. Electronic spreadsheets are symbolic systems.  Relational databases are symbolic systems.  Data warehouses are symbolic systems. To understand the different types of systems, please have a look at this blog post, Five Types of Systems . Tableau has added a semantic layer. Microsoft Excel can now get a semantic model via Power BI  ( and this ). Microsoft Fabric IQ  allows for the creation of a semantic layer. Databricks gets a semantic model from Unity Catalog . You can add a semantic layer to Google Sheets . Everybody and their brother is providing a semantic layer these days. The real challenge is not adding the semantics with a semantic layer. The challenge is recovering semantics that were never explicitly captured in the first place.  All that data in those spreadsheets and databases nev...

"In the hands of someone with no knowledge, they can produce clumsy, ugly, barely functional output, but in the hands of a skilled craftsman, they can product works of utility, beauty, and durability." Quoted from Semantic Web for the Working Ontologist . Industrial engineering and informatics are closely related disciplines, but they begin from different perspectives. Industrial engineering starts with work, processes, systems, and optimization. Informatics starts with information, knowledge, people, and digital systems. A useful way to think about their relationship is: Industrial engineering optimizes how work flows. Informatics optimizes how information flows. Industrial engineering designs how people work; work systems . Informatics designs how people interact with information; structuring systems into discrete stable units . Pragmatic Knowledge Management Systems design how people create, share, preserve, and evolve knowledge; think knowledge framework. Industrial engi...

This is a walk through of my PROOF financial reporting framework, a report prepared using that reporting framework, and a validation report which verifies that the report model and reported facts have been created correctly.  This walk through uses off the shelf software that is currently available except where I explicitly state otherwise. Overview : Reporting framework HTML page view (Created using Coyote reporting and a style sheet I created)  Reporting framework viewer (commercially available software application) Report model and report (commercially available software application) Report model and report verification (commercially available software application) Links to all files Theory of Financial Reporting Framework This is an overview of the reporting framework . There are two sections.  The first has information that relates to all reporting styles.  The second section relates to one specific reporting style of the reporting framework. A reporting sty...

A Pragmatic Knowledge Management System (PKMS) is basically a Semantic Knowledge Management System (SKMS) that has been supplemented to add restrictions and capabilities that turn the system from one that is semantic to a system that is pragmatic in nature. A Pragmatic Knowledge Management System embraces the notion of the Pragmatic Web . A Pragmatic Knowledge Management System operationalizes a Semantic Knowledge Management System and grounds it in reality and truth. A Pragmatic Knowledge Management System embraces immutable digital distributed ledgers where appropriate to enhance accountability . A Pragmatic Knowledge Management System is a platform upon with trusted ecosystems can be built. Reliable industrial processes can be created, maintained, and managed. Systems that have zero tolerance for error. A Pragmatic Knowledge Management System is a deterministic system, as are accounting information systems . A Pragmatic Knowledge Management System is a system of discrete stable ...

This blog post is from a very good email sent by Richard Gasca , the creator of Accounting & Audit by Design (A&AD) Framework, to a private email list of accountants interested in A&AD.  I thought it would be a good thing to share more broadly. Auditchain's demonstration of Pacioli Ledger Alpha and the Integrity Audit Log, reinforced by yesterday's announcement of Auditchain's partnership with PwC , represents a formidable and welcome technical milestone. Anchoring event sequences via the Haber-Stornetta cryptographic lineage (1991, 1993, 1997), utilizing Ethereum EIP-712 structured signatures, and batch-stamping Merkle roots onto public blockchains definitively solves post-hoc ledger tampering. Auditchain is entirely right on a fundamental premise: the substrate must come first, and establishing physical, append-only non-repudiation is the foundational prerequisite for any modern financial platform.  To bridge the chasm between raw cryptographic bits and a leg...

The future of information processing spans a possible spectrum from symbolic spreadsheets, to AI‑augmented spreadsheets, to fully grounded pragmatic systems powered by neuro‑semantic and neuro‑pragmatic AI. As I see it, there is a spectrum of three broad possible alternatives for processing information going forward.  Those broad alternatives appear to be: Spreadsheet Centric (Status quo) : Continue using electronic spreadsheets as the primary mechanism for organizing, calculating, and reporting information. This approach remains symbolic and manual, with limited structure and no semantic or pragmatic grounding. Spreadsheet + AI (Augmented Symbolic) : Retain electronic spreadsheets as the core environment but use AI to assist/augment with formulas, modeling, cleaning, and analysis. This enhances productivity but still operates within a symbolic, ungrounded paradigm. Pragmatic Systems + AI (Grounded, Model Driven) : Transition to pragmatic systems that encode meaning, evidence,...