The Navigator helps you clarify the problem, see which parts of Trusted Data matter, and identify a useful place to start.
It follows visible relationships and matching rules. Use the result as a structured starting point for discussion, not automated professional advice.
Clarify the problem
Start from a client question, not from a list of concepts.
See what matters
Connect the question to the relevant data, definitions, ownership, quality and controls.
Choose a next step
Point toward a focused assessment, prototype or deeper reference when it is useful.
Structured starting point
Which accelerator should we start with?
Three bounded prompts use a visible static rules table. The initial result is an example; change any answer to update it. No chatbot or hidden model is making the recommendation.
Recommended accelerator1 week
Trusted Data Discovery Accelerator
Answers: what does this data actually represent? Uses Reality Mapping to identify entities, duplicate representations, identity candidates, relationships, coverage, assumptions, and confidence.
Named deliverable
Reality Mapping assessment and evidence-backed discovery brief
Scope note
Demonstrated in an independent personal project; not presented as client-delivery validation.
Why this result
It directly matches the selected client problem. It directly supports the selected next decision. It fits the available data signals.
Next action
Select one bounded dataset landscape and run the Reality, Identity, Coverage and Linkage assessment.
These suggestions use an approved set of public methods and explicit matching rules. They are prompts for discussion, not automated advice.
methodCurated Data
AI-Ready Data Foundation Assessment
A reusable consulting pattern for assessing whether an enterprise data foundation can support GenAI, RAG, GraphRAG, semantic governance, and AI-assisted decisions.
Pathway layer
Curated Data
Delivery stages
Assess → Discover → Design
Possible use
One-week Spatial Data Governance & AI-readiness Case Analysis
methodSemantic Layer
Digital Twin 2.0 Semantic Governance Assessment
A one-day PoC pattern for assessing whether a digital twin data foundation is ready for semantic layer, knowledge graph, GraphRAG, AI agents, and decision support.
Pathway layer
Semantic Layer
Delivery stages
Assess → Discover → Design
Possible use
Freedo-style one-day PoC
methodKnowledge
Knowledge Graph Readiness Assessment
A reusable consulting pattern for assessing whether an organisation is ready to build and operate a knowledge graph for enterprise AI, GraphRAG, digital twin, or semantic governance use cases.
Pathway layer
Knowledge
Delivery stages
Assess → Discover → Design
Possible use
Digital Twin Semantic Readiness Workbench
methodKnowledge
Source-to-Scene Pipeline
An emerging method for transforming heterogeneous source data into a coherent, governed, semantically connected operational scene for AI, simulation, and decision support.
Pathway layer
Knowledge
Delivery stages
Discover → Design → Prototype → Govern
Possible use
One-week Spatial Data Governance & AI-readiness Case Analysis