Data

Accounting vs. Data Acquisition

As established earlier, accounting is not mere data acquisition (see Chapter 1). While data acquisition deals with objective measurements—like temperature, weight, or speed—accounting involves dimensions that are subject to human interpretation.

Two Categories of Data Aspects

We propose that the aspects (or properties) of accounting data fall into two distinct categories:

1. Realia: Objective, measurable attributes (e.g., what, where, when, temperature, weight). These belong to the world of data acquisition.

2. Humania: Subjective dimensions tied to human interactions, such as the traditional accounting cycles:

   • Order-to-Cash (OTC)
   • Procure-to-Pay (PTP)
   • Record-to-Report (RTR) These exist exclusively in the human world of agreements, processes, and social constructs.

Structuring Data: A Shift in Approach

A persistent habit in accounting—borrowed from data acquisition—is the “WYSIWYG” (What You See Is What You Get) mindset: recording data with the final output already in mind. This limits flexibility and ignores the potential of separating content from presentation.

Our Position: More intelligence should be invested in structuring data before it is recorded. We record a representation of the world, not the world itself. This contrasts with current trends in our profession, which often focus on post-recording analysis.

A Starting Point for Analysis

We propose the following:

1. Data is a representation of realities, composed of both Realia and Humania.
2. Hypothesis (to be validated in practice):
   • Realia belong to nodes (e.g., entities, objects, or fixed attributes).
   • Humania belong to edges (e.g., transactions, relationships, or flows of value).

This gives us a foundation to analyze the data we want to record—and later, present—without premature constraints.