FHIR Ontology Requirements

This page is OBSOLETE. RDF Work has moved Here

DRAFT

Desiderata

How FHIR profiles are approached, designed, constrained, or extended should be based on a formal logical model. That model should be explicit and be developed prior to the profiles that result from it. Without such a model to operate from, FHIR will lack the semantic and structural consistency required to make FHIR computable.

Requirements

Priorities are indicated using MoSCoW terms (MUST, SHOULD, COULD, WON'T).

1. FHIR Instance Mappings

(MUST) We must define lossless bi-drectional transformations from FHIR XML/JSON resource instances to FHIR RDF resource instances and vice versa. FHIR RDF resource instance data that is transformed into FHIR XML resource instance data must validate against schemas and declared profiles. This round-tripping must not be dependent on any information other than the definition of FHIR resources and data types. (I.e. round-tripping must not be dependent on FHIR profiles, vocabulary definitions or other external information.)

2. FHIR Ontology Mappings

(MUST) We must define lossless bi-directional transformations from FHIR Profile instances (XML/JSON/RDF) to OWL/RDFS ontology representations and vice versa

3. Complete FHIR Coverage

(MUST) The RDF representation of FHIR resource instance data must be capable of expressing all legal FHIR instances that make use of any valid FHIR profiles, including extensions. An RDF instance data representation that is limited to only a subset of possible FHIR instances is not acceptable.

4. Monotonic with Modifier Exensions

(MUST) FHIR RDF data with modifier extensions must be "safe" for RDF reasoning, i.e., the semantics of the RDF must be monotonic even in the presence of modifier extensions.

5. Vocabulary Bindings

(MUST) The FHIR ontology must support vocabulary bindings to code, Coding and CodeableConcept - including dealing with extensible value sets and multi-code system value sets.

(SHOULD) The FHIR vocabulary representation should be able to leverage existing semantic web terminology representations (e.g. SNOMED-CT)

6. Enforce Constraints

(SHOULD) The FHIR ontology should enforce constraints that are representable in OWL/RDF whenever possible, e.g. schema constraints, regular expressions, etc.

7. Annotation Information

(SHOULD) In the RDFS/OWL Ontology representation, should expose at least minimal annotation information for display in an ontology editor for use by humans

8. User Friendly

RDF/OWL expressions should be (business, clinical) user friendly and understandable.
(This was felt to be unachievable.)

9. Datatype IRIs

(SHOULD) To support inference, datatypes (date, dateTime, value, etc.) should be represented as IRIs (xsd) rather than as string literals.

10. Articulate Value

Clearly articulate the value of the new RDF/RDFS/OWL representation over the current XML/JSON representation
(This will be a separate goal of the group, rather than a FHIR ontology requirement.)

11. Enable Inference

(MUST) The FHIR ontology must support inference on FHIR instance data, both in use cases based on the open world assumption and in use cases based on the closed world assumption.

12. Common Model

Create a common OWL/RDFS representation for information model elements and medical terminology concepts.
(This may be pursued as a separate project of the group.)

13. Valid Against Schemas and Profiles

(Merged into #1.)

14. RDF Quality

(MUST) Transformations into RDF must meet software quality checks including ontological closure. The RDF instance which is transformed from FHIR XML or FHIR JSON must be capable of being opened without further modification by widely available tools including Protégé and the RDF must meet quality checks including successful closure of graphs - all the links are understood by the tool.

15. Auto Generated

(MUST) The FHIR ontology and FHIR RDF instance data mappings should be auto-generatable from the FHIR specification.

16. Profiles from OWL

(MAY) We may find a way to transform OWL/RDF ontologies into FHIR profiles.
(Subsumed by #2)

USE CASES

Real world use cases that require and demonstrate the value of an RDF/OWL representation - TBD

• Identify (through extension profile properties) inheritance relationships to abstract concepts and properties that hold across resources. E.g. "All orders", "All interventions", "All medications"
• Allow easy testing of subsumption relationships between profiles - "Profile A is a proper constraint on Profile B"
• Allow validation of mappings between FHIR elements and RIM, v2 and other models to:
  • Ensure that mapped to elements and paths actually exist
  • Allow identification of overlapping or unclear semantics in FHIR (as well as poorly expressed/imprecise mappings)
• Allow FHIR-based data to be linked to other RDF data and queried via technologies such as SPARQL
• Provide a recommended syntax for persisting FHIR data as triple-stores, allowing reasoning capabilities to be exercised (e.g. subsumption testing of codes when querying)