Ontology Playground Share Link
https://microsoft.github.io/Ontology-Playground/#/share/eJzVWU2P5EgR_Sshc9mVXK3u-dju6Vtvz0iMxLCrmd7d...
What this ontology represents
This ontology models the people, systems, and artifacts involved when a production incident is raised against an enterprise application. It captures the real-world flow of how a defect goes from being detected to being triaged, diagnosed, fixed, validated, and deployed — through the coordinated effort of developers, SMEs, scrum masters, business analysts, testers, and business owners.
The real-world scenario
Drawn from enterprise incident management in healthcare technology operations. When a Production application goes down or behaves unexpectedly, multiple roles converge to triage the issue. The ontology captures who does what, in what sequence, and how the work flows from problem detection through to controlled deployment of the fix via change management.
Why these entities and relationships matter
Incident response is fundamentally a sense-making activity. Anyone or any AI agent reasoning about an incident needs to know what was affected (Application, Environment), who is doing what (Developer, SMEArchitect, ScrumMaster, BusinessAnalyst, Tester, BusinessOwner), why it happened (RootCause), and how it was closed out (Resolution, ChangeRequest).
Modeling this shared vocabulary lets the organization answer questions like:
a) "Which Production incidents on Application X were caused by configuration root causes in the last quarter?"
b) "Which resolutions were deployed without a corresponding change request?" (a compliance gap)
c) "Who is the Business Owner that needs to be notified for any incident affecting Application X?"
These questions are obvious in plain English but only answerable when the meaning of each term is consistent across teams.
Model summary
12 entities, 11 relationships, color-coded into three semantic groups: red (the incident), blue/cyan (systems context), purple (the human team), green/teal (outcomes and artifacts). The model deliberately stays simple — sense-making over scale.
