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A Justification-based Semantic 
Framework for Representing, Evaluating 
and Utilizing Terminology Mappings 
EHR4CR, Open P...
Objective 
• Enable a more collaborative semantic landscape 
with providers and consumers of terminology 
mappings. 
– A f...
Semantic landscape 1(3) 
Consumers and, somewhat 
reluctant, creators of mappings 
Workshop on Context, Interpretation and...
Semantic landscape 2(3) 
Consumers and, somewhat 
reluctant, creators of mappings 
Providers of terminology mappings, 
som...
Semantic landscape 3(3) 
5 
Consumers and, somewhat 
reluctant, creators of mappings 
Providers of terminology mappings, 
...
Example Scenario 
• Challenging nature of mapping utilization, or 
“How hard can it be?” 
– Appear to the uninitiated as a...
Example Scenario 1(3) 
7 
Defined 
Mappings
Example Scenario 2(3) 
8 
matches 
matches 
matches 
Defined 
Mappings 
Inferred 
Mappings
Example Scenario 3(3) 
9 
matches 
matches 
matches 
Defined 
Mappings 
Inferred 
Mappings 
matches 
Problematic 
Mappings
“It’s complicated”. So, we often become, somewhat 
reluctant, creators of our own mappings 
• Availability of up-to-date i...
11 
Objective: A more collaborative 
semantic landscape 
Value adding providers 
of terminologies 
Workshop on Context, In...
Framework 
Workshop on Context, Interpretation and Meaning (CIM2014) 12 
http://slideshare.net/kerfors/CIM2014
Mapping Strategies 
• Lexical Mappings (LOOM) generated by performing lexical comparison between 
preferred labels and alt...
Terminology Mappings Validation Schemes
Collaborative semantic landscape 
15 
Informed consumers 
of terminology mappings 
Value adding providers 
of terminology ...
16 
Application of RDF to 
represent mappings 
Enabled by applications 
of the RDF standard
17 
Application of RDF to 
represent provenance 
Enabled by applications 
of RDF
Applications of RDF for packaging assertions 
18 
(e.g. mappings) with provenance 
Enabled by applications 
of RDF
19 
Applications of RDF for describing 
datasets and linksets with justifications 
Enabled by applications 
of RDF
Example Scenario 
20 
matches 
matches 
matches 
Defined 
Mappings 
Inferred 
Mappings 
matches 
Problematic 
Mappings
21 
Example Scenario, zoom in 
matches 
Defined 
Mappings 
Inferred 
Mappings
matches 
Defined 
Mappings 
Inferred 
Mappings 
22 
SKOS/RDF to represent the mappings 
ICD9CM:999.4 skos:exactMatch SNOME...
ICD9CM:999.4 skos:exactMatch MedDRA:10067113 
matches 
Defined 
Mappings 
Inferred 
Mappings 
Nanopublication/RDF for pack...
Justification Vocabulary for 
Mapping Terminology Concepts/Terms 
24 
?? 
Workshop on Context, Interpretation and Meaning ...
25 
Applications of RDF for describing 
datasets and linksets with justifications 
Enabled by applications of 
the RDF sta...
Linksets: Justification Vocabulary Terms 1(3) 
26
Linksets: Justification Vocabulary Terms 2(3) 
27
Linksets: Justification Vocabulary Terms 3(3) 
Workshop on Context, Interpretation and Meaning (CIM2014) 28 
http://slides...
Acknowledgments 
• Session chair 
• CIM2014 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/ 
• .. 
Workshop on C...
Mapping Representation using SKOS 
35 
<http://purl.bioontology.org/ontology/ICD9CM/999.4> 
<http://www.w3.org/2004/02/sko...
Mapping Provenance Representation 
36 
:NanoPub_1_Supporting_2 = { 
[ a r:Proof, r:Conjunction; 
r:component <#lemma1>; 
r...
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A Justification-based Semantic Framework for Representing, Evaluating and Utilizing Terminology Mappings

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A Justification-based Semantic Framework for Representing, Evaluating and Utilizing Terminology Mappings

  1. 1. A Justification-based Semantic Framework for Representing, Evaluating and Utilizing Terminology Mappings EHR4CR, Open PHACTS, SALUS and W3C collaboration Sajjad Hussain1, Hong Sun2, Gokce Banu Laleci Erturkmen3, Mustafa Yuksel3, Charlie Mead4, Alasdair Gray5, Kerstin Forsberg6 19-Oct-2014 EHR4CR: 1INSERM UMRS 1142, Paris, France; AstraZeneca, 6R&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, 1 Workshop on Context, Interpretation and Meaning (CIM2014) http://slideshare.net/kerfors/CIM2014 Version 1.0
  2. 2. Objective • Enable a more collaborative semantic landscape with providers and consumers of terminology mappings. – A framework built upon existing terminology mappings to: • Infer new mappings for different use cases. • Present provenance of the together with the justification for the mappings. • Perform mapping validation in order to show that inferred mappings can be erroneous. • Discuss a Justification Vocabulary for Mapping Terminology Concepts/Terms Workshop on Context, Interpretation and Meaning (CIM2014) 2 http://slideshare.net/kerfors/CIM2014
  3. 3. Semantic landscape 1(3) Consumers and, somewhat reluctant, creators of mappings Workshop on Context, Interpretation and Meaning (CIM2014) 3 http://slideshare.net/kerfors/CIM2014
  4. 4. Semantic landscape 2(3) Consumers and, somewhat reluctant, creators of mappings Providers of terminology mappings, some examples Workshop on Context, Interpretation and Meaning (CIM2014) 4 http://slideshare.net/kerfors/CIM2014
  5. 5. Semantic landscape 3(3) 5 Consumers and, somewhat reluctant, creators of mappings Providers of terminology mappings, some examples Providers of terminologies, some examples Workshop on Context, Interpretation and Meaning (CIM2014) http://slideshare.net/kerfors/CIM2014
  6. 6. 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” 6
  7. 7. Example Scenario 1(3) 7 Defined Mappings
  8. 8. Example Scenario 2(3) 8 matches matches matches Defined Mappings Inferred Mappings
  9. 9. Example Scenario 3(3) 9 matches matches matches Defined Mappings Inferred Mappings matches Problematic Mappings
  10. 10. “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. Workshop on Context, Interpretation and Meaning (CIM2014) 10 http://slideshare.net/kerfors/CIM2014
  11. 11. 11 Objective: A more collaborative semantic landscape Value adding providers of terminologies Workshop on Context, Interpretation and Meaning (CIM2014) http://slideshare.net/kerfors/CIM2014 Informed consumers of terminology mappings Value adding providers of terminology mappings
  12. 12. Framework Workshop on Context, Interpretation and Meaning (CIM2014) 12 http://slideshare.net/kerfors/CIM2014
  13. 13. 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. Workshop on Context, Interpretation and Meaning (CIM2014) 13 http://slideshare.net/kerfors/CIM2014
  14. 14. Terminology Mappings Validation Schemes
  15. 15. Collaborative semantic landscape 15 Informed consumers of terminology mappings Value adding providers of terminology mappings Value adding providers of terminologies Enabled by applications of RDF
  16. 16. 16 Application of RDF to represent mappings Enabled by applications of the RDF standard
  17. 17. 17 Application of RDF to represent provenance Enabled by applications of RDF
  18. 18. Applications of RDF for packaging assertions 18 (e.g. mappings) with provenance Enabled by applications of RDF
  19. 19. 19 Applications of RDF for describing datasets and linksets with justifications Enabled by applications of RDF
  20. 20. Example Scenario 20 matches matches matches Defined Mappings Inferred Mappings matches Problematic Mappings
  21. 21. 21 Example Scenario, zoom in matches Defined Mappings Inferred Mappings
  22. 22. matches Defined Mappings Inferred Mappings 22 SKOS/RDF to represent the mappings ICD9CM:999.4 skos:exactMatch SNOMEDCT:21332003 SNOMEDCT:21332003 skos:exactMatch MedDRA:10067113 ICD9CM:999.4 skos:exactMatch MedDRA:10067113
  23. 23. ICD9CM:999.4 skos:exactMatch MedDRA:10067113 matches Defined Mappings Inferred Mappings Nanopublication/RDF for packaging mappings together with their provenance and justification 23 Assertion Justification trace generated from EYE reasoning engine
  24. 24. Justification Vocabulary for Mapping Terminology Concepts/Terms 24 ?? Workshop on Context, Interpretation and Meaning (CIM2014) http://slideshare.net/kerfors/CIM2014
  25. 25. 25 Applications of RDF for describing datasets and linksets with justifications Enabled by applications of the RDF standard Workshop on Context, Interpretation and Meaning (CIM2014) http://slideshare.net/kerfors/CIM2014
  26. 26. Linksets: Justification Vocabulary Terms 1(3) 26
  27. 27. Linksets: Justification Vocabulary Terms 2(3) 27
  28. 28. Linksets: Justification Vocabulary Terms 3(3) Workshop on Context, Interpretation and Meaning (CIM2014) 28 http://slideshare.net/kerfors/CIM2014
  29. 29. Acknowledgments • Session chair • CIM2014 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 Workshop on Context, Interpretation and Meaning (CIM2014) 29 http://slideshare.net/kerfors/CIM2014
  30. 30. Reference material • Projects/organisations of the authors of this paper • Example – Mapping Representation using SKOS – Mapping Provenance Representation Workshop on Context, Interpretation and Meaning (CIM2014) 30 http://slideshare.net/kerfors/CIM2014
  31. 31. 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 Workshop on Context, Interpretation and Meaning (CIM2014) 31 http://slideshare.net/kerfors/CIM2014
  32. 32. 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 Workshop on Context, Interpretation and Meaning (CIM2014) 32 http://slideshare.net/kerfors/CIM2014
  33. 33. 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) Workshop on Context, Interpretation and Meaning (CIM2014) 33 http://slideshare.net/kerfors/CIM2014
  34. 34. W3C Semantic Web Health Care and Life Sciences Interest Group (HCLS IG) http://www.w3.org/2001/sw/ • .. Workshop on Context, Interpretation and Meaning (CIM2014) 34 http://slideshare.net/kerfors/CIM2014
  35. 35. Mapping Representation using SKOS 35 <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" .
  36. 36. Mapping Provenance Representation 36 :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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