TRUST Audit
Know what your spatial data can prove.
A structured assessment of how spatial data is sourced, handled, changed, validated, governed, and prepared for analytics or AI.
ORIGIN
Where did the data come from?
CUSTODY
Who handled it and when?
CHANGE
What changed and why?
VALIDATION
How was it checked?
TRUST
Is it ready for use?
Assessment framework
A practical framework for spatial data trust.
The audit follows the pathway from origin to decision readiness, testing whether the organization has enough evidence to support confidence.
Origin
Can the source, method, date, provider, and acquisition context be verified?
Custody
Is responsibility clear as data moves between people, vendors, systems, and teams?
Change
Can meaningful edits, transformations, approvals, and version decisions be traced?
Validation
Are quality checks repeatable, documented, and connected to the dataset?
Audit process
Evidence first. Recommendations second.
The process moves from discovery and evidence collection to an actionable improvement roadmap.
01
Scope
Identify priority datasets, workflows, decisions, and stakeholders.
02
Collect
Review files, metadata, systems, procedures, and available evidence.
03
Verify
Test whether evidence supports the stated source, handling, and status.
04
Score
Evaluate maturity across the five TRUST dimensions.
05
Improve
Prioritize governance, workflow, evidence, and tooling improvements.
Deliverables
Clear findings your team can act on.
The audit is designed to turn fragmented evidence into a practical view of current maturity, risk, and next steps.
Trust maturity score
A structured view of current strength across origin, custody, change, validation, and readiness.
Included
Evidence register
A working record of sources, verification levels, documents, systems, and supporting proof.
Included
Workflow and governance findings
Clear gaps affecting accountability, repeatability, authority, and decision confidence.
Included
Prioritized improvement plan
Recommended actions for process, governance, validation, and Attashe readiness.
Included
Frequently asked questions
What organizations usually ask first.
The audit can be focused on one priority dataset or expanded across a larger workflow or portfolio.
Does the audit require Attashe?
No. The audit stands on its own and can be used to understand current maturity before any platform decision.
What information is needed?
Priority datasets, available metadata, workflow documentation, system context, validation records, and access to the people who understand the process.
What happens after the audit?
Your team receives a prioritized roadmap. The next step may be process improvement, governance work, validation design, or an Attashe implementation discussion.