CTS2-LE Interoperability: Unterschied zwischen den Versionen
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== RDF == | == RDF == | ||
| − | Modern semantic (web) technologies have its root in mature knowledge representation (KR) methods and techniques. They can be seen as a “Webification” of KR languages such as the Frame Language and Description Logics (DL). In fact, the Resource Description Language (RDF) standard can be considered as a simple frame language as well as a language for semantic nets and OWL has its direct foundation in a certain DL dialect. The semantics of these languages are the theoretical backbone of controlled vocabularies and are widely used to define concrete vocabularies. For instance, SNOMED-CT has the expressivity of the OWL EL++ dialect and even LOINC can be proper represented and processed by means of DL. | + | Modern semantic (web) technologies have its root in mature knowledge representation (KR) methods and techniques. They can be seen as a “Webification” of KR languages such as the Frame Language and Description Logics (DL). In fact, the Resource Description Language (RDF) standard can be considered as a simple frame language as well as a language for semantic nets and OWL has its direct foundation in a certain DL dialect. The semantics of these languages are the theoretical backbone of controlled vocabularies and are widely used to define concrete vocabularies. For instance, SNOMED-CT has the expressivity of the OWL EL++ dialect |
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| + | and even LOINC can be proper represented and processed by means of DL. | ||
Another important aspect is the utilization of RDF for storing and querying linked (big) data. So far many RDF stores (Jena TDB, Virtuoso, etc.) are available and able to hold data in the range of several hundred million triples. Compared to object stores and assuming an average number of 10 object attributes, one can easily store and retrieve several million objects. These capabilities gives CTS2-LE the opportunity to “weave” instance nets for arbitrary medical data objects together with referenced vocabularies. | Another important aspect is the utilization of RDF for storing and querying linked (big) data. So far many RDF stores (Jena TDB, Virtuoso, etc.) are available and able to hold data in the range of several hundred million triples. Compared to object stores and assuming an average number of 10 object attributes, one can easily store and retrieve several million objects. These capabilities gives CTS2-LE the opportunity to “weave” instance nets for arbitrary medical data objects together with referenced vocabularies. | ||
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By default the CTS2-LE distribution uses [https://jena.apache.org/documentation/tdb/ Jena TDB] for storing terminology data. This component can easily be exchanged by any other triple store solution (e.g. [http://virtuoso.openlinksw.com/ Virtuoso]). | By default the CTS2-LE distribution uses [https://jena.apache.org/documentation/tdb/ Jena TDB] for storing terminology data. This component can easily be exchanged by any other triple store solution (e.g. [http://virtuoso.openlinksw.com/ Virtuoso]). | ||
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== SPARQL == | == SPARQL == | ||
Version vom 4. September 2020, 14:24 Uhr
This section describes the set of standards that provide solution developers with standard interfaces for extending the functionality of CTS2-LE and for utilizing CTS2-LE terminology services within their own solutions:
- Common Terminology Services (CTS2): CTS2-LE functional model
- Resource Description Framework (RDF): CTS2-LE internal terminology data format
- SPARQL Protocol And RDF Query Language (SPARQL): CTS2-LE terminology query language
- Fast Healthcare Interoperability Resources (FHIR): CTS2-LE external terminology exchange format
CTS2
The Common Terminology Services Version 2 is a joint standardization effort from HL7 and OMG. The objective was to provide a model and specification for discovering, accessing, distributing and updating terminological resources. CTS2 served as a blueprint for CTS2-LE in order to support a wide range of applications.
For further information on CTS2 see:
- OMG CTS2 Homepage (contains links to all published versions of the CTS2 standard)
RDF
Modern semantic (web) technologies have its root in mature knowledge representation (KR) methods and techniques. They can be seen as a “Webification” of KR languages such as the Frame Language and Description Logics (DL). In fact, the Resource Description Language (RDF) standard can be considered as a simple frame language as well as a language for semantic nets and OWL has its direct foundation in a certain DL dialect. The semantics of these languages are the theoretical backbone of controlled vocabularies and are widely used to define concrete vocabularies. For instance, SNOMED-CT has the expressivity of the OWL EL++ dialect
SPARQL
The SPARQL Protocol And RDF Query Language (SPARQL) is a W3C semantic web standard for manipulating and querying RDF graphs. For further information about SPARQL, see:
- W3C SPARQL Working Group homepage with references to all parts of the SPARQL standard
- SPQRQL by Example tutorial containing many example queries to open RDF stores (e.g. medication databases)
Use of SPARQL in CTS2-LE
Due to the full RDF-encoding of all terminology artifacts, CTS2-LE allows for arbitrary queries within and across terminologies, value sets, concepts, and concept relationships. For this means are provided to transmit a standard SPARQL query to CTS2-LE. The query result is provided in standard SPARQL Query Results XML Format.
Interoperability with 3rd-Party Solutions
Third-Party-Solutions have full access to the complete CTS2-LE terminology base through the CTS2-LE SPARQL REST API. Queries must comply to the CTS2-LE CTS2 RDF-Binding.
HL7 FHIR
HL7 Fast Healthcare Interoperability Resources is an HL7 draft standard for exchanging healthcare information in a structured, interoperable and easily implementable manner. In contrast to the constraint-based approach of HL7v3 (e.g. an implementation guide for a referral letter constraints the CDA RMIM, which constraints the HL7 RIM ist), HL7 FHIR is based on modular resources which can be composed to use-case-specific data interchange definitions. FHIR already comes with a catalogue of standard resource definitions which can be composed and tailored to match the need of a specific healthcare data exchange problem. For further information about HL7 FHIR see:
- HL7 FHIR homepage with links to the full FHIR documentation and the FHIR catalogue of standard resource definitions
- Introduction to FHIR (German)
- German FHIR Blog von Simone Heckmann
Use of HL7 FHIR in CTS2-LE
CTS2-LE uses the FHIR value set resource definiton as its standard format for externalizing terminologies and value sets. In particular terminology artifacts can be uploaded and retrieved using this standard.
Interoperability with 3rd-Party Solutions
The CTS2-LE REST API provides various interfaces for sharing FHIR value sets that can be used for connecting terminology providing and consuming services to CTS2-LE:
- Resolve Value Set: Resolve and/or fetch an FHIR origined value set (or terminology) which is identified by it's URI.
- Request Concept Details: Fetch the details of a concept which is identified through a codesystem and code.
- Update Value Set: Create or update a FHIR coded value set (or terminology) within CTS2-LE.
An example for using these APIs in conjunction with web forms can be found here.
