Via my "context lenses" (i.e., my subjective view of the world) a unit of Data (or Datum) is like a cube of sugar, each side representing a value factor along the following dimensions:

  1. Identity -- via Resolvable URIs based Names for everything
  2. Data Representation Format Dexterity -- e.g., HTTP based Content Negotiation which loosens the coupling between Data Model Semantics and actual Data Representation (Syntax/Markup)
  3. Platform Agnostic Data Access -- e.g. via ubiquitous HTTP
  4. Change Sensitivity -- data warehouses are like real-world warehouses, goods rot and perish overtime
  5. Provenance -- data about the data (metadata) that helps establish "Who", "What", "When", "Where", and at least approximate or guesstimate "Why"
  6. Data Mesh Navigability -- delivered via inference rules.

The quality of service factors above nullify many of the typical concerns associated data driven business models, such as:

  • Wholesale Imports (crawls) - where your data is crawled and/or imported wholesale into a new data space with zero attribution to the source
  • Lossy Attribution -- attribution is delivered in literal form which doesn't deliver branding fidelity across many value chain layers or entire life cycle of a given data item
  • Service Provisioning -- effectively build any business model if you can align services with unambiguously identifiable consumers with actual data items or across entire data spaces.