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A Framework for Evaluating and Utilizing 
Medical Terminology Mappings 
EHR4CR – Open PHACTS, SALUS and W3C collaboration ...
Objective 
• Show the challenging nature of mapping 
utilization among different terminologies. 
• A framework built upon ...
Semantic landscape 1(3) 
3 
For more information about these see the reference 
slides in the end of this slide deck. 
201...
Semantic landscape 2(3) 
4 
Providers of terminology mappings, 
some examples 
2014 Medical Informatics Europe 
http://sli...
Semantic landscape 3(3) 
5 
Providers of terminology mappings, 
some examples 
Providers of terminologies, 
some examples ...
Rationale 
• Challenging nature of mapping utilization, or 
“How hard can it be?” 
– Appear to the uninitiated as a simple...
Example Scenario 
• Challenging nature of mapping utilization, or 
“How hard can it be?” 
– Appear to the uninitiated as a...
Example Scenario 1(3) 
8 
Defined 
Mappings
Example Scenario 2(3) 
9 
matches 
matches 
matches 
Defined 
Mappings 
Inferred 
Mappings
Example Scenario 3(3) 
10 
matches 
matches 
matches 
Defined 
Mappings 
Inferred 
Mappings 
matches 
Problematic 
Mapping...
“It’s complicated”. So, we often become, somewhat 
reluctant, creators of our own mappings 
• Availability of up-to-date i...
Objective: A more collaborative 
semantic landscape 
12 
Informed consumers of 
terminology mappings 
Value adding provide...
Framework 
13 
2014 Medical Informatics Europe 
http://slideshare.net/kerfors/MIE2014
Mapping Strategies 
• Lexical Mappings (LOOM) generated by performing lexical comparison between 
preferred labels and alt...
Terminology Mappings Validation Schemes
Collaborative semantic landscape 
16 
Informed consumers of 
terminology mappings 
Value adding providers of 
terminology ...
17 
Application of RDF for 
representing mappings 
Enabled by applications of 
the RDF standard
18 
Application of RDF for 
representing provenance 
Enabled by applications of 
the RDF standard
Applications of RDF for packaging assertions 
19 
(e.g. mappings) with provenance 
Enabled by applications of 
the RDF sta...
20 
Applications of RDF for describing 
datasets and linksets with justifications 
Enabled by applications of 
the RDF sta...
Example Scenario 
21 
matches 
matches 
matches 
Defined 
Mappings 
Inferred 
Mappings 
matches 
Problematic 
Mappings
22 
Example Scenario 
matches 
Defined 
Mappings 
Inferred 
Mappings
matches 
Defined 
Mappings 
Inferred 
Mappings 
23 
SKOS/RDF for representing mappings 
ICD9CM:999.4 skos:exactMatch SNOME...
Nanopublication for packaging mappings 
and mapping provenance representations 
ICD9CM:999.4 skos:exactMatch MedDRA:100671...
Justification Vocabulary terms for 
Relating Terminology Concepts/Terms 
25 
??
26 
Applications of RDF for describing 
datasets and linksets with justifications 
2014 Medical Informatics Europe 
http:/...
Linksets: Justification Vocabulary Terms 1(3) 
27 
2014 Medical Informatics Europe 
http://slideshare.net/kerfors/MIE2014
Linksets: Justification Vocabulary Terms 2(3) 
28 
2014 Medical Informatics Europe 
http://slideshare.net/kerfors/MIE2014
Linksets: Justification Vocabulary Terms 3(3) 
29 
2014 Medical Informatics Europe 
http://slideshare.net/kerfors/MIE2014
CIM Workshop at ISWC2014 to discuss: 
Justification Vocabulary terms for 
Relating Terminology Concepts/Terms 
30
Acknowledgments 
• Session chair 
• MIE2014 organizers 
• SALUS team: Hong Sun, Ali Anil Sinaci, Gokce Banu Laleci Erturkm...
Reference material 
• Projects/organisations of the authors of this paper 
• Example 
– Mapping Representation using SKOS ...
EHR4CR 
Electronic Healthcare Record For Clinical Research 
http://www.ehr4cr.eu/ 
• IMI (Innovative Medicine Initiative) ...
Open PHACTS 
Open Pharmacology Space 
http://www.openphacts.org/ 
• IMI (Innovative Medicine Initiative) 
• 31 partners: 1...
SALUS 
Sustainable Proactive Post Market Safety Studies 
http://www.salusproject.eu/ 
• European Commission (STREP) 
• ICT...
W3C 
Semantic Web Health Care and Life Sciences Interest 
Group (HCLS IG) 
http://www.w3.org/2001/sw/ 
• .. 
36 
2014 Medi...
Mapping Representation using SKOS 
37 
<http://purl.bioontology.org/ontology/ICD9CM/999.4> 
<http://www.w3.org/2004/02/sko...
Mapping Provenance Representation 
38 
:NanoPub_1_Supporting_2 = { 
[ a r:Proof, r:Conjunction; 
r:component <#lemma1>; 
r...
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MIE2014: A Framework for Evaluating and Utilizing Medical Terminology Mappings

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MIE2014: A Framework for Evaluating and Utilizing Medical Terminology Mappings

  1. 1. A Framework for Evaluating and Utilizing Medical Terminology Mappings EHR4CR – Open PHACTS, SALUS and W3C collaboration Sajjad Hussain1, Hong Sun2, Ali Anil Sinaci3, Gokce Banu Laleci Erturkmen3, Charlie Mead4, Alasdair Gray5, Deborah McGuinness6, Eric Prud’Hommeaux7, Christel Daniel1, Kerstin Forsberg8 MIE2014 2-Sept-2014 EHR4CR: 1INSERM UMRS 1142, Paris, France; 8 AstraZeneca, R&D Information, Mölndal Sweden Open PHACTS: 5School of Mathematical and Computer Sciences, Heriot-Watt University SALUS: 3Software Research, Development and Consultancy, Ankara, Turkey, 2Advanced Clinical Applications Research Group, Agfa HealthCare, Gent, Belgium W3C: 4Health Care and Life Sciences IG, 7MIT, Cambridge, MA, USA, 6Department of Computer Science, Rensselaer Polytechnic Institute, Troy, US 1 2014 Medical Informatics Europe Version 1.0 http://slideshare.net/kerfors/MIE2014
  2. 2. Objective • Show the challenging nature of mapping utilization among different terminologies. • A framework built upon existing terminology mappings to: – Infer new mappings for different use cases. – Present provenance of the mappings together with the justification information. – Perform mapping validation in order to show that inferred mappings can be erroneous. • Enable a more collaborative semantic landscape with providers and consumers of terminology mappings. 2 2014 Medical Informatics Europe http://slideshare.net/kerfors/MIE2014
  3. 3. Semantic landscape 1(3) 3 For more information about these see the reference slides in the end of this slide deck. 2014 Medical Informatics Europe http://slideshare.net/kerfors/MIE2014 Consumers and, somewhat reluctant, creators of mappings
  4. 4. Semantic landscape 2(3) 4 Providers of terminology mappings, some examples 2014 Medical Informatics Europe http://slideshare.net/kerfors/MIE2014 Consumers and, somewhat reluctant, creators of mappings
  5. 5. Semantic landscape 3(3) 5 Providers of terminology mappings, some examples Providers of terminologies, some examples 2014 Medical Informatics Europe http://slideshare.net/kerfors/MIE2014 Consumers and, somewhat reluctant, creators of mappings
  6. 6. Rationale • Challenging nature of mapping utilization, or “How hard can it be?” – Appear to the uninitiated as a simple exercise like “this term in this terminology is the same as that term in that terminology” 6 2014 Medical Informatics Europe http://slideshare.net/kerfors/MIE2014
  7. 7. Example Scenario • Challenging nature of mapping utilization, or “How hard can it be?” – Appear to the uninitiated as a simple exercise like “this term in this terminology is the same as that term in that terminology” 7
  8. 8. Example Scenario 1(3) 8 Defined Mappings
  9. 9. Example Scenario 2(3) 9 matches matches matches Defined Mappings Inferred Mappings
  10. 10. Example Scenario 3(3) 10 matches matches matches Defined Mappings Inferred Mappings matches Problematic Mappings
  11. 11. “It’s complicated”. So, we often become, somewhat reluctant, creators of our own mappings • Availability of up-to-date information to assess the suitability of a given terminology for a particular use case. • Difficulty of correctly using complex, rapidly evolving terminologies. • Differences in granularity between the source and target terminologies. • Lack of semantic mappings in order to completely and unambiguously define computationally equivalent semantics. • Lack of provenance information, i.e. how, when and for what purposes the mappings were created. • Time and effort required to complete and evaluate mappings. 11 2014 Medical Informatics Europe http://slideshare.net/kerfors/MIE2014
  12. 12. Objective: A more collaborative semantic landscape 12 Informed consumers of terminology mappings Value adding providers of terminology mappings Value adding providers of terminologies
  13. 13. Framework 13 2014 Medical Informatics Europe http://slideshare.net/kerfors/MIE2014
  14. 14. Mapping Strategies • Lexical Mappings (LOOM) generated by performing lexical comparison between preferred labels and alternative labels of terms. These mappings are represented via skos:closeMatch property. • Xref OBO Mappings Xref and Dbxref are properties used by ontology developers to refer to an analogous term in another vocabulary. These mappings are represented via skos:relatedMatch property. • CUI Mappings from UMLS are extracted by utilizing the same Concept Unique Identifier (CUI) annotation as join point of similar terms from different vocabularies. These mappings are represented via skos:closeMatch property. • URI-based Mappings are generated identity mappings between term concepts in different ontologies that are represented by the same URI. These mappings are represented via skos:exactMatch property. 14 2014 Medical Informatics Europe http://slideshare.net/kerfors/MIE2014
  15. 15. Terminology Mappings Validation Schemes
  16. 16. Collaborative semantic landscape 16 Informed consumers of terminology mappings Value adding providers of terminology mappings Value adding providers of terminologies Enabled by applications of the RDF standard
  17. 17. 17 Application of RDF for representing mappings Enabled by applications of the RDF standard
  18. 18. 18 Application of RDF for representing provenance Enabled by applications of the RDF standard
  19. 19. Applications of RDF for packaging assertions 19 (e.g. mappings) with provenance Enabled by applications of the RDF standard
  20. 20. 20 Applications of RDF for describing datasets and linksets with justifications Enabled by applications of the RDF standard
  21. 21. Example Scenario 21 matches matches matches Defined Mappings Inferred Mappings matches Problematic Mappings
  22. 22. 22 Example Scenario matches Defined Mappings Inferred Mappings
  23. 23. matches Defined Mappings Inferred Mappings 23 SKOS/RDF for representing mappings ICD9CM:999.4 skos:exactMatch SNOMEDCT:21332003 SNOMEDCT:21332003 skos:exactMatch MedDRA:10067113 ICD9CM:999.4 skos:exactMatch MedDRA:10067113
  24. 24. Nanopublication for packaging mappings and mapping provenance representations ICD9CM:999.4 skos:exactMatch MedDRA:10067113 matches Defined Mappings Inferred Mappings 24 Assertion Justification trace generated from EYE reasoning engine
  25. 25. Justification Vocabulary terms for Relating Terminology Concepts/Terms 25 ??
  26. 26. 26 Applications of RDF for describing datasets and linksets with justifications 2014 Medical Informatics Europe http://slideshare.net/kerfors/MIE2014 Enabled by applications of the RDF standard
  27. 27. Linksets: Justification Vocabulary Terms 1(3) 27 2014 Medical Informatics Europe http://slideshare.net/kerfors/MIE2014
  28. 28. Linksets: Justification Vocabulary Terms 2(3) 28 2014 Medical Informatics Europe http://slideshare.net/kerfors/MIE2014
  29. 29. Linksets: Justification Vocabulary Terms 3(3) 29 2014 Medical Informatics Europe http://slideshare.net/kerfors/MIE2014
  30. 30. CIM Workshop at ISWC2014 to discuss: Justification Vocabulary terms for Relating Terminology Concepts/Terms 30
  31. 31. Acknowledgments • Session chair • MIE2014 organizers • SALUS team: Hong Sun, Ali Anil Sinaci, Gokce Banu Laleci Erturkmen – Support from the European Community’s Seventh Framework Programme (FP7/2007–2013) under Grant Agreement No. ICT-287800, SALUS Project (Scalable, Standard based Interoperability Framework for Sustainable Proactive Post Market Safety Studies). • EHR4CR team: WP4, WPG2, WP7 members – Support from the Innovative Medicines Initiative Joint Undertaking under grant agreement n° [No 115189]. European Union's Seventh Framework Programme (FP7/2007-2013) and EFPIA companies • Open PHACTS team: Alasdair Gray • W3C HCLS team: Eric Prud’Hommeaux, Charlie Mead 31 2014 Medical Informatics Europe http://slideshare.net/kerfors/MIE2014
  32. 32. Reference material • Projects/organisations of the authors of this paper • Example – Mapping Representation using SKOS – Mapping Provenance Representation 2014 Joint Summits on Translational Science 32
  33. 33. EHR4CR Electronic Healthcare Record For Clinical Research http://www.ehr4cr.eu/ • IMI (Innovative Medicine Initiative) – Public-Private Partnership between EU and EFPIA • ICT platform: using EHR data for supporting clinical research • Protocol feasibility • Patient recruitment • Clinical trial execution: Clinical Research Forms (eCRF)/ Individual Case Safety Reports (ICSR) prepopulation • 33 European academic and industrial partners – 11 pilot sites from 5 countries – 4 millions patients 33 2014 Medical Informatics Europe http://slideshare.net/kerfors/MIE2014
  34. 34. Open PHACTS Open Pharmacology Space http://www.openphacts.org/ • IMI (Innovative Medicine Initiative) • 31 partners: 10 pharma – 21 academic / SME • The Challenge - Open standards for drug discovery data – Develop robust standards for solid integration between data sources via semantic technologies – Implement the standards in a semantic integration hub (“Open Pharmacological Space”) – Deliver services to support on-going drug discovery programs in pharma and public domain 34 2014 Medical Informatics Europe http://slideshare.net/kerfors/MIE2014
  35. 35. SALUS Sustainable Proactive Post Market Safety Studies http://www.salusproject.eu/ • European Commission (STREP) • ICT platform : using EHRs data to improve post-market safety activities on a proactive basis • Semi-automatic notification of suspected adverse events • Reporting adverse events (Individual Case Safety Reports (ICSR) prepopulation) • Post Marketing safety studies • 8 European academic and industrial partners – 2 pilot sites • Lombardia Region (Italy) and Eastern Saxony (Germany) 35 2014 Medical Informatics Europe http://slideshare.net/kerfors/MIE2014
  36. 36. W3C Semantic Web Health Care and Life Sciences Interest Group (HCLS IG) http://www.w3.org/2001/sw/ • .. 36 2014 Medical Informatics Europe http://slideshare.net/kerfors/MIE2014
  37. 37. Mapping Representation using SKOS 37 <http://purl.bioontology.org/ontology/ICD9CM/999.4> <http://www.w3.org/2004/02/skos/core#broadMatch> <http://purl.bioontology.org/ontology/MDR/10002198>, <http://purl.bioontology.org/ontology/MDR/10002199>, <http://purl.bioontology.org/ontology/MDR/10020751>, <http://purl.bioontology.org/ontology/MDR/10067484> . <http://purl.bioontology.org/ontology/MDR/10002198> a <http://www.w3.org/2004/02/skos/core#Concept>; <http://purl.bioontology.org/ontology/MDR/level> "PT"; <http://www.w3.org/2004/02/skos/core#broader> <http://purl.bioontology.org/ontology/MDR/10002220>, <http://purl.bioontology.org/ontology/MDR/10057181>; <http://www.w3.org/2004/02/skos/core#inScheme> <http://purl.bioontology.org/ontology/MDR>; <http://www.w3.org/2004/02/skos/core#notation> "10002198"; <http://www.w3.org/2004/02/skos/core#prefLabel> "Anaphylactic reaction" . <http://purl.bioontology.org/ontology/MDR/10002199> a <http://www.w3.org/2004/02/skos/core#Concept>; <http://purl.bioontology.org/ontology/MDR/level> "PT"; <http://www.w3.org/2004/02/skos/core#broader> <http://purl.bioontology.org/ontology/MDR/10002220>, <http://purl.bioontology.org/ontology/MDR/10009193>; <http://www.w3.org/2004/02/skos/core#inScheme> <http://purl.bioontology.org/ontology/MDR>; <http://www.w3.org/2004/02/skos/core#notation> "10002199"; <http://www.w3.org/2004/02/skos/core#prefLabel> "Anaphylactic shock" . <http://purl.bioontology.org/ontology/MDR/10020751> a <http://www.w3.org/2004/02/skos/core#Concept>; <http://purl.bioontology.org/ontology/MDR/level> "PT"; <http://www.w3.org/2004/02/skos/core#broader> <http://purl.bioontology.org/ontology/MDR/10027654>; <http://www.w3.org/2004/02/skos/core#inScheme> <http://purl.bioontology.org/ontology/MDR>; <http://www.w3.org/2004/02/skos/core#notation> "10020751"; <http://www.w3.org/2004/02/skos/core#prefLabel> "Hypersensitivity" . <http://purl.bioontology.org/ontology/MDR/10067484> a <http://www.w3.org/2004/02/skos/core#Concept>; <http://purl.bioontology.org/ontology/MDR/level> "PT"; <http://www.w3.org/2004/02/skos/core#broader> <http://purl.bioontology.org/ontology/MDR/10043409>; <http://www.w3.org/2004/02/skos/core#inScheme> <http://purl.bioontology.org/ontology/MDR>; <http://www.w3.org/2004/02/skos/core#notation> "10067484"; <http://www.w3.org/2004/02/skos/core#prefLabel> "Adverse reaction" .
  38. 38. Mapping Provenance Representation 38 :NanoPub_1_Supporting_2 = { [ a r:Proof, r:Conjunction; r:component <#lemma1>; r:component <#lemma2>; r:component <#lemma3>; r:component <#lemma4>; r:component <#lemma5>; r:component <#lemma6>; r:gives { <http://purl.bioontology.org/ontology/ICD9CM/999.4> skos:prefLabel "Anaphylactic shock due to serum, not elsewhere classified". <http://purl.bioontology.org/ontology/SNOMEDCT/213320003> skos:prefLabel "Anaphylactic shock due to serum". <http://purl.bioontology.org/ontology/MDR/10067113> skos:prefLabel "Anaphylactic transfusion reaction". <http://purl.bioontology.org/ontology/ICD9CM/999.4> skos:exactMatch <http://purl.bioontology.org/ontology/SNOMEDCT/213320003>. <http://purl.bioontology.org/ontology/SNOMEDCT/213320003> skos:exactMatch <http://purl.bioontology.org/ontology/MDR/10067113>. <http://purl.bioontology.org/ontology/ICD9CM/999.4> skos:exactMatch <http://purl.bioontology.org/ontology/MDR/10067113>. }]. ……. ……. ……. <#lemma13> a r:Inference; r:gives {<http://purl.bioontology.org/ontology/ICD9CM/999.4> skos:exactMatch <http://purl.bioontology.org/ontology/MDR/10067113>}; r:evidence ( <#lemma11> <#lemma12>); r:binding [ r:variable [ n3:uri "http://localhost/var#x0"]; r:boundTo [ n3:uri "http://purl.bioontology.org/ontology/ICD9CM/999.4"]]; r:binding [ r:variable [ n3:uri "http://localhost/var#x1"]; r:boundTo [ n3:uri "http://purl.bioontology.org/ontology/SNOMEDCT/213320003"]]; r:binding [ r:variable [ n3:uri "http://localhost/var#x2"]; r:boundTo [ n3:uri "http://purl.bioontology.org/ontology/MDR/10067113"]]; r:rule <#lemma14>. <#lemma14> a r:Extraction; r:gives {@forAll var:x0, var:x1, var:x2. {var:x0 skos:exactMatch var:x1. var:x1 skos:exactMatch var:x2} => {var:x0 skos:exactMatch var:x2}}; r:because [ a r:Parsing; r:source <file:///Users/sajjad/workspace/terminology-reasoning-test-case/example-term-map.n3>]. }.

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