Complete firstBounded subject
The scope and purpose of Competency Questions are stated as a concrete question.
Without scope, competency question test suite becomes arbitrary.
Method guideKnowledge Modeling
Competency Questions
A practical method guide: clarify prerequisites and materials, understand the complete process, and look up outputs, pitfalls, and stop criteria.
ComplexityMedium
Time2-4 h
Participants2-8
FormatWorkshop + async
MaturityEstablished
01
Prerequisite
What needs to be finished first
Complete firstAccess to relevant perspectives
Use cases and decision questions, domain vocabulary, representative instance data and domain decision makers are available.
Without these perspectives, central claims in competency question test suite remain unsupported.
02
Preparation
What needs to be ready before start
Materials
Use cases and decision questions, domain vocabulary, representative instance data, shared workspace, source links, and decision log.
People / roles
Domain expert · ontology engineer · data consumer
Pre-read
Collect Use cases and decision questions, domain vocabulary, representative instance data in advance and mark open assumptions.
Time needed
60–90 minutes initially; ongoing test maintenance
Setup
Prepare translate a natural-language domain question into terms, formal query, test data, and expected answer visibly and calibrate assessment terms before starting.
03
Core question
The one question this method answers
Which domain questions must the ontology answer with defined data and inferences?
04
Flow
Phases with goal, actions, output and pitfall
Competency questions state in natural language which inferences an ontology should enable. Terms, quantification, example answer, and test query are explicit.
competency question test suite
Fictional worked example
translate a natural-language domain question into terms, formal query, test data, and expected answer as a precise working structure with a fictional example.
Competency question
User · question · decision
Which open actions are overdue?
Semantics
Terms · quantifier · horizon
status=open; dueDate<today.
Test case
Data · expected answer · negative case
A-17; completed A-18 excluded.
Formalisation
Query · axioms · version
SPARQL + hasOwner/memberOf.
The example demonstrates the domain logic of Competency Questions; worksheets remain blank.
Grüninger and Fox: Methodology for the Design and Evaluation of Ontologies
- 1
Elicit question
Elicit question
Goal
Produce CQ backlog so the core question “Which domain questions must the ontology answer with defined data and inferences?” can be answered with stronger support.
Inputs for this step
- Use cases and decision questions
- domain vocabulary
- representative instance data
Actions
- Collect real decision questions with domain actors.
- Record source, rationale, and open uncertainty directly in CQ backlog.
Output
CQ backlog
CQ backlog · source · uncertainty · next decision
Quality check
Is the question relevant to a concrete user?
Pitfall
The domain question remains vague or has no unambiguous expected test answer. Clarify decision context, quantifier, horizon, and expected example answer before formalising.
Timing: 10–20 minutes
- 2
Specify
Specify
Goal
Produce precise CQ so the core question “Which domain questions must the ontology answer with defined data and inferences?” can be answered with stronger support.
Inputs for this step
- CQ backlog
- domain vocabulary
- representative instance data
Actions
- Clarify quantifier, horizon, terms, and desired answer.
- Record source, rationale, and open uncertainty directly in precise CQ.
Output
precise CQ
precise CQ · source · uncertainty · next decision
Quality check
Can a unique example answer be given?
Pitfall
The domain question remains vague or has no unambiguous expected test answer. Clarify decision context, quantifier, horizon, and expected example answer before formalising.
Timing: 10–20 minutes
- 3
Formalise
Formalise
Goal
Produce query test so the core question “Which domain questions must the ontology answer with defined data and inferences?” can be answered with stronger support.
Inputs for this step
- precise CQ
- domain vocabulary
- representative instance data
Actions
- Translate CQ into a query and required axioms.
- Record source, rationale, and open uncertainty directly in query test.
Output
query test
query test · source · uncertainty · next decision
Quality check
Does the formal query preserve the domain question?
Pitfall
The domain question remains vague or has no unambiguous expected test answer. Clarify decision context, quantifier, horizon, and expected example answer before formalising.
Timing: 10–20 minutes
- 4
CQ tests
CQ tests
Goal
Produce CQ test suite so the core question “Which domain questions must the ontology answer with defined data and inferences?” can be answered with stronger support.
Inputs for this step
- query test
- domain vocabulary
- representative instance data
Actions
- Run positive, negative, and boundary test data.
- Record source, rationale, and open uncertainty directly in CQ test suite.
Output
CQ test suite
CQ test suite · source · uncertainty · next decision
Quality check
Does the test fail when a core axiom is missing?
Pitfall
The domain question remains vague or has no unambiguous expected test answer. Clarify decision context, quantifier, horizon, and expected example answer before formalising.
Timing: 10–20 minutes
05
Artifact
What comes out at the end
Sketch: what the artifact looks like
Form
Versioned competency question test suite with date, sources, owners, and next review.
Versioning / ownership
Retain date, source, assumption state, and decision for every version of competency question test suite.
Tool alternatives
- competency question test suite as board or document
- Source and evidence register
- Decision and action log
competency-questions-working-template.md
Plan Competency Questions around its domain steps and the concrete decision question.
Competency Questions: Worksheet
Question
To be confirmed
Desired outcome
To be confirmed
Scope
Full workshop Time: 60–90 minutes initially; ongoing test maintenance
Complete this worksheet on paper or in your own document during the work.
Preparation for this scope
Method setup
- Materials: Use cases and decision questions, domain vocabulary, representative instance data, shared workspace, source links, and decision log.
- Roles: Domain expert · ontology engineer · data consumer
- Advance information: Collect Use cases and decision questions, domain vocabulary, representative instance data in advance and mark open assumptions.
- Overall time needed: 60–90 minutes initially; ongoing test maintenance
- Setup: Prepare translate a natural-language domain question into terms, formal query, test data, and expected answer visibly and calibrate assessment terms before starting.
Prepare for the work steps
Elicit question: Elicit question
- Use cases and decision questions
- domain vocabulary
- representative instance data
Specify: Specify
- CQ backlog
- domain vocabulary
- representative instance data
Formalise: Formalise
- precise CQ
- domain vocabulary
- representative instance data
CQ tests: CQ tests
- query test
- domain vocabulary
- representative instance data
competency question test suite
Competency question
User · question · decision
...
Semantics
Terms · quantifier · horizon
...
Test case
Data · expected answer · negative case
...
Formalisation
Query · axioms · version
...
Enter only real input, sources, and decisions.
Grüninger and Fox: Methodology for the Design and Evaluation of Ontologies
Elicit question: Elicit question
Expected artifact: CQ backlog
CQ backlog · source · uncertainty · next decision
Entry:
...
- Is the question relevant to a concrete user?
Specify: Specify
Expected artifact: precise CQ
precise CQ · source · uncertainty · next decision
Entry:
...
- Can a unique example answer be given?
Formalise: Formalise
Expected artifact: query test
query test · source · uncertainty · next decision
Entry:
...
- Does the formal query preserve the domain question?
CQ tests: CQ tests
Expected artifact: CQ test suite
CQ test suite · source · uncertainty · next decision
Entry:
...
- Does the test fail when a core axiom is missing?
Open questions and next steps
...
Method guide: https://methodatlas.meierhoff-systems.de/en/methods/competency-questions/run-sheet
06
Example output
Concrete filled scenario, fictional example
Fictional example for orientation. Counts and timings describe this case and are not universal requirements.
competency-questions-beispiel.md
Concrete filled scenario, fictional example
CQ: which open actions are overdue today, and which organisation contains their owner? Terms: Action, dueDate, status, hasOwner, memberOf. Test data contain two open and one completed action. Expected: A-17 only. The SPARQL test runs for every ontology version.
07
Pitfalls
Recognize symptoms and steer against them
Quick overview, the full text is in the matching phase in the flow
- Elicit questionThe domain question remains vague or has no unambiguous expected test answer.View in phase
- SpecifyThe domain question remains vague or has no unambiguous expected test answer.View in phase
- FormaliseThe domain question remains vague or has no unambiguous expected test answer.View in phase
- CQ testsThe domain question remains vague or has no unambiguous expected test answer.View in phase
Trap
Elicit question
Symptom
The domain question remains vague or has no unambiguous expected test answer.
What to do
Clarify decision context, quantifier, horizon, and expected example answer before formalising.
Trap
Specify
Symptom
The domain question remains vague or has no unambiguous expected test answer.
What to do
Clarify decision context, quantifier, horizon, and expected example answer before formalising.
Trap
Formalise
Symptom
The domain question remains vague or has no unambiguous expected test answer.
What to do
Clarify decision context, quantifier, horizon, and expected example answer before formalising.
Trap
CQ tests
Symptom
The domain question remains vague or has no unambiguous expected test answer.
What to do
Clarify decision context, quantifier, horizon, and expected example answer before formalising.
08
Stop criteria
When to pause, resolve prerequisites, or choose another approach
competency question test suite answers the core question with traceable evidence or explicitly marked uncertainty.
Owners, next actions, and review dates are named for open points.
Finished the method guide?
Go to the profile for purpose, similar methods, and sources or continue to the next method in the catalog.