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Cognitive and Social Challenges of
Ontology use in the Biomedical Domain
      SLE 2012: 5th International Conference on
           Software Language Engineering
                 Dresden, Germany


              Margaret-Anne Storey
      The CHISEL Group, University of Victoria
Studying and addressing human aspects in
  software engineering and knowledge engineering
Research methods used:
  – Mixed methods (analysis of archival data,
    interviews, grounded theory, surveys etc.)


Technologies explored:
  – Visualization techniques
  – Collaboration support
  – Social media
Focus of this talk: Providing cognitive support
  for ontology developers and users
  throughcollaborative visual user interfaces
Ontology          Ontology          Ontology
Creation           Library         Applications

     Background        BioPortal         Annotation

     Examples          Services          Search

     Tools             Mappings
Ontology          Ontology          Ontology
Creation           Library         Applications

     Background        BioPortal         Annotation

     Examples          Services          Search

     Tools             Mappings
SLE 2012 Keynote: Cognitive and Social Challenges of Ontology Use in the Biomedical Domain
The study of being
Co-opted by computer science to
 enable the explicit specification of
  Entities
   Propertiesand attributes of entities
           Relationsbetween entities
One definition…

Explicit specification of a conceptualization
  [Gruber, 1993]
ntologies, Ontologies, Ontologies
O
Ontology languages
Choice of language and choice of reasoning
  engine
Tradeoff between expressiveness, reasoning
  power, tractability and human understanding
May need inference engine to give real-time
  feedback while authoring an ontology
Why ontologies?
Awash in data….
SLE 2012 Keynote: Cognitive and Social Challenges of Ontology Use in the Biomedical Domain
SLE 2012 Keynote: Cognitive and Social Challenges of Ontology Use in the Biomedical Domain
How are ontologies used?
Challenges?
Cognitive issues:
  – Complexity, scale
  – Evolution
  – Inclusion of “upper ontologies”, or
    parts of other ontologies
Social issues:
  – One size does not fit all
  – Multiple authors
  – Input from broader set of stakeholders
Ontology          Ontology          Ontology
Creation           Library         Applications

     Background        BioPortal         Annotation

     Examples          Services          Search

     Tools             Mappings


   FMA, GO, ICD
Foundational Model of Anatomy
            (FMA)
Comprehensive ontology of
  human anatomy
Over 120K terms, 2.1M
  relationship instances (168
  relationship types)
One of the largest and best
  developed ontologies in
  biomedicine, multi-purpose


                                Slide by Mark Musen.
Slide by Mark Musen.
Gene Ontology (GO)
To unify representation of gene and gene
  product attributes across all species
For annotating genes and gene products,
  assimilate and disseminate annotation data
Contains over 24,500 terms applicable to a
  wide variety of biological organisms
A standard tool in bioinformatics
See http://www.nature.com/scitable/topicpage/ontologies-scientific-data-sharing-made-easy-77972
International Classification of Diseases (ICD)

 • An enumeration of diseasesthat forms the
   basis for medical claims and reimbursements
 • A “legacy” terminology that has its roots in
   19th century epidemiology
 • Created initially by biostatisticians with a
   pressing need to compare death statistics in
   different European countries



                                      Slide by Mark Musen.
ICD is used for lots of (too many?) things!
 • ICD is used to code all patient encounters
   with the health-care system for:
    – Billing and reimbursement
    – Institutional planning
    – Disease surveillance and public health
    – Quality assurance
    – Economic modeling
 • ICD was never intended to make the
   distinctions relevant to all these tasks!
 • Nevertheless it is widely used!
                                           Slide by Mark Musen.
ICD: An excerpt…
724 Unspecified disorders of the back
724.0 Spinal stenosis, other than cervical
724.00 Spinal stenosis, unspecified region
724.01 Spinal stenosis, thoracic region
724.02 Spinal stenosis, lumbar region
724.09 Spinal stenosis, other
724.1 Pain in thoracic spine
724.2 Lumbago
724.3 Sciatica
724.4 Thoracic or lumbosacral neuritis
724.5 Backache, unspecified
724.6 Disorders of sacrum
724.7 Disorders of coccyx
724.70 Unspecified disorder of coccyx
724.71 Hypermobility of coccyx
724.71 Coccygodynia
724.8 Other symptoms referable to back
724.9 Other unspecified back disorders


                                             Slide by Mark Musen.
ICD9 (1977): A handful of codes for
         traffic accidents




                                 Slide by Mark Musen.
ICD10 (1999): 587 codes for such accidents

V31.22 Occupant of three-wheeled motor vehicle injured
  in collision with pedal cycle, person on outside of
  vehicle, nontraffic accident, while working for income
W65.40 Drowning and submersion while in bath-tub,
  street and highway, while engaged in sports activity
X35.44 Victim of volcanic eruption, street and highway,
  while resting, sleeping, eating or engaging in other vital
  activities




                                               Slide by Mark Musen.
ICD revision process in the 20th Century…
• International and National Revision conferences
• 1-5 person delegations in International
  conferences, multi-disciplinary
• Manual curation
• Output: paper copy
• Negotiation process: decibel method of
  discussion
• ICD drafts translated into 27 languages

         See http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2950305/
ICD-11 revision: key aspects

•   Content model
•   Topic Advisory Groups – vertical and horizontal
•   Classification experts (ontology development)
•   iCAT: web based collaborative authoring tool
•   Use cases – evaluating ICD-11 in use
Deliverables
• Print versions –fit for purposein multiple
  languages
• Web portal to access, browse and maintain it
  – Input from the crowd
• Classification in formalized language
Ontology          Ontology          Ontology
Creation           Library         Applications

     Background        BioPortal         Annotation

     Examples          Services          Search

     Tools             Mappings




  FMA-Explorer, Protégé, iCAT
Foundational Model Explorer




       University of Victoria   33
Protégé ontology authoring environment

  Ontology contents need to
    be processed and interpreted
    by computers
  Interactive tools can assist
    developers in ontology
    authoring (e.g. Protégé)
SLE 2012 Keynote: Cognitive and Social Challenges of Ontology Use in the Biomedical Domain
Collaborative Protégé
iCAT web based authoring tool for ICD-11
Ontology          Ontology          Ontology
Creation           Library         Applications

     Background        BioPortal         Annotation

     Examples          Services          Search

     Tools             Mappings
National Center for Biomedical Ontology




Goal: develop innovative technology and methods that
  allow scientists to record, manage, and disseminate
  biomedical information and knowledge in both
  human readable and machine-processableform
BioPortal Library
SLE 2012 Keynote: Cognitive and Social Challenges of Ontology Use in the Biomedical Domain
SLE 2012 Keynote: Cognitive and Social Challenges of Ontology Use in the Biomedical Domain
Ontology          Ontology         Ontology
Creation           Library        Applications

     Background        BioPor           Annotation

     Examples          Services         Search

     Tools             Mappings
BioPortal services
•   Ontology recommender
•   Ontology widgets
•   Annotator
•   API access through REST services
•   Virtual appliance (custom installs, can
    be proprietary)
SLE 2012 Keynote: Cognitive and Social Challenges of Ontology Use in the Biomedical Domain
SLE 2012 Keynote: Cognitive and Social Challenges of Ontology Use in the Biomedical Domain
Ontology Widgets
Ontology Widgets (2)
SLE 2012 Keynote: Cognitive and Social Challenges of Ontology Use in the Biomedical Domain
Ontology           Ontology          Ontology
Creation          Acquisition       Applications

     Background         Library           Annotation

     Examples            Services         Search

     Tools               Mappings
SLE 2012 Keynote: Cognitive and Social Challenges of Ontology Use in the Biomedical Domain
Visualizing multiple ontologies and
             mappings
SLE 2012 Keynote: Cognitive and Social Challenges of Ontology Use in the Biomedical Domain
Mappings between terms - Matrix
Mappings between ontologies -- Graph
Ontology           Ontology          Ontology
Creation          Acquisition       Applications

     Background         Library           Annotation

     Examples            Services         Search

     Tools               Mappings
Data from STRIDE
• 1.8 million pediatric and adult patients with clinical and
  demographic data (1994 - present)
• 19 million Clinical Encounters (1994 - present)

 35 million

 22 million
 2.9 million
 1.2 million

 7 million

 137 million
 10 million




                                                Slide by Nigam Shah.
Making EMRs Unreasonably Effective
                                                                                                                                                  Text clinical note
BioPortal – knowledge graph


                                                                       Creating clean lexicons
                                         Diseases                             Frequency                   Term – 1
                                                                                                          :          Term recognition tool
                                                                                                          :            NCBO Annotator
                Procedures
                                                                                                          :                                  Annotation Workflow
                                                                            Syntactic types               Term – n


                                          Drugs

                                                                                                                                                  Terms Recognized




                                             P1     ICD9        ICD9            ICD9    ICD9       ICD9   ICD9
                                             P1     T1,     …   T5,     …       T4,     T8,    …   T6,    T1,
 Further Analysis




                                                    T2,         T4,             T3,     T9,        T8,    T2,
                                                    no T4       T3              T1      T4         T10    no T4


                                             P2
                                             P2
                                             P3                                                                                                  Negation detection
                             Cohort of
                              Interest




                                             P3
                                             :
                                             :
                                             Pn
                                             Pn
                                                       Terms form a temporal series of tags 




                                                                                                                                             Slide by Nigam Shah.
P1        ICD9                           ICD9                             ICD9          ICD9                              ICD9        ICD9
P1        T1,            …               T5,           …                  T4,           T8,               …               T6,         T1,
                                                                                                                                                                     T1   …       …    Tn
          T2,                            T4,                              T3,           T9,                               T8,         T2,
          no T4                          T3                               T1            T4                                T10         no T4
                                                                                                                                                          P1         1    0       1     1
P2
P2                                                                                                                                                        :          0    1       1     0
P3
P3                                                                                                                                                        :          0    0       0     1
:
:                                                                                                                                                         Pn         0    1       0     1
Pn
Pn




                                                                                                                                        T1    …     …          Tn                       P1   …     …     Pn
                                                                                                                    T1                  1     0.6   0.5        0.6               P1     1    0.1   0.7   0.8
                                                                                                                    :                         1     0.2        0.3               :           1     0.5   0.8
                                                                                                                    :                               1          0.1               :                 1     0.4
      Who is getting                                                                                                Tn                                         1                 Pn                      1         What is special
       these drugs,                                                                                                                                                                                                 about these
     conditions, etc?                                                                                                                                                                                                patients?
                                                                                                                                                                          Comparative
                             cephalexin                            cane
                                                                                                                                                        Drug Safety
                                                                                  doppler
                                                                             ultrasonography
                                                                                                     ultrasound
                                                                                                      imaging
                                                                                                                                                                          Effectiveness
                                       amoxicillin
                                                                                          doppler studies
                                                                     angioplasty
                                                                                                          atherectomy
                                                                            revascularization
                 wheelchair
                                                      cilostazol
                                                                                              vascular
                                                                                               surgical
                                                                                                                    bypass graft

                                                                                                                                                         Learning
                      hydralazine congestive heart
                                                                                diagnostic
                                                                                             procedures
                                                                                                                                                                              Predictions
                                                                                                                                                        from Data
          pneumonia                                                              imaging                      surgical revision
                                      failure

                                                                                                bypass
                       heart failure
                                                        nifedipine
                                                                                                                       testosterone
        amiodarone                      pravastatin                              vascular
                                                                                 diseases
                                                               carotid
                             pantoprazole insulin glargine endarterectomy
           obesity
                                                           transplantation           ramipril                  fentanyl
                                   zolpidem
                                                trimethoprim
                                                                   decompressive
                                                                      incision
                                 coronary               sulfamethoxazole
      diazepam                 angiography
                                                                           fluoroscopic
                                                heart                      angiography
                                           transplantation
                                                          tacrolimus
                                                                                    temazepam

                                                                                                                                                                                                         Slide by Nigam Shah.
Drug Safety: Detecting Risk Signals




ROR of 1.5, CI of [1.11, 2.13]
The X2 p-value <10-7

              MI      No MI
 Vioxx         a         b

No Vioxx       c         d




                                  Slide by Nigam Shah.
Ontology uses




    See http://research.microsoft.com/en-us/projects/ontology/
See http://research.microsoft.com/en-us/projects/ontology/
See http://research.microsoft.com/en-us/projects/ontology/
Nature Publishing
Ontology           Ontology          Ontology
Creation          Acquisition       Applications

     Background         Library           Annotation

     Examples            Services         Search

     Tools               Mappings
GoPubmed
Clinical Trial Search
Clinical Trial Search
Clinical Trial Search
Clinical Trial Explorer
Array Express




http://www.gehlenborg.com/aex
Ontology           Ontology            Ontology
Creation          Acquisition         Applications

     Background         Library             Annotation

     Examples            Services           Search

     Tools               Mappings




                                    What’s next?
Towards collaborative ontology
       visualization as a service
• Preserve easy-to-use visualizations of
  ontologies
• Enable flexible visual exploration and analysis
  of biomedical ontologies and data
• Support collaboration in visual exploration and
  analysis of biomedical ontologies and data
• Enable presentation of analysis artifacts on the
  web
BioMixer
An online platform for the visual exploration of
        multiple biomedical ontologies
Multiple coordinated visualizations
BioMixer architecture/vision
Demo
SLE 2012 Keynote: Cognitive and Social Challenges of Ontology Use in the Biomedical Domain
SLE 2012 Keynote: Cognitive and Social Challenges of Ontology Use in the Biomedical Domain
SLE 2012 Keynote: Cognitive and Social Challenges of Ontology Use in the Biomedical Domain
University of Victoria   81
SLE 2012 Keynote: Cognitive and Social Challenges of Ontology Use in the Biomedical Domain
Ontology          Ontology           Ontology
Creation           Library          Applications

     Background        BioPortal          Annotation

     Examples          Services           Search

     Tools             Mappings




                                   Summary
Concluding remarks
• Ontologies finally coming of age(D. McGuinness)
• With adoption, novel tools will emerge
• Users now savvy with search, visualization and
  analytics
• Anticipated benefits for translational research

  “Developers do not innovate tools, users do”
Selected References
Gruber T., A Translation Approach to Portable Ontologies. Knowledge Acquisition 5(2):199-220, 1993
ICD11: http://www.youtube.com/user/whoicd11
Ernst, N.A., Storey, M.A., Allen, P.: Cognitive support for ontology modeling. International Journal of
     Human-Computer Studies 62(5), 553–577 (2005)
Fu, B., Grammel, L., Storey, M.A.: BioMixer: A Web-based Collaborative Ontology Visualization Tool. 3rd
     International Conference on Biomedical Ontology (ICBO 2012) (2012)
Gruber, T.R.: Towards Principles for the Design of Ontologies Used for Knowledge Sharing. In: Guarino,
     N., Poli, R. (eds.) Formal Ontology in Conceptual Analysis and Knowledge Representation. vol. 43,
     pp. 907–928. Kluwer Academic Publishers (1993)
Katifori, A., Halatsis, C., Lepouras, G., Vassilakis, C., Giannopoulou, E.: Ontology visualization methods—
     a survey. ACM Computing Surveys 39(4) (2007)
Musen, M.A., Noy, N.F., Shah, N.H., Chute, C.G., Storey, M.A., Smith, B., Team, the NCBO: The National
     Center for Biomedical Ontology. Journal of the American Medical Informatics Association (In press.)
     (2012), http://bmir.stanford.edu/file_asset/index.php/1729/BMIR-2011-1468.pdf
Noy, N.F., Shah, N.H., Whetzel, P.L., Dai, B., Dorf, M., Griffith, N., Jonquet, C., Rubin, D.L., Storey, M.A.,
     Chute, C.G., Musen, M.A.: BioPortal: ontologies and integrated data resources at the click of a
     mouse. Nucleic acids research 37(Web Server issue) (Jul 2009)
Smith, B.: Ontology (Science). Nature Precedings (i) (Jul 2008)
Tudorache, T., Falconer, S., Noy, N., Nyulas, C., ¨Ust¨un, T., Storey,M.A., Musen, M.: Ontology
     development for the masses: creating ICD-11 in WebProt´eg´e. In: Knowledge Engineering and
     Management by the Masses, EKAW2010. pp. 74–89. Springer (2010)

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SLE 2012 Keynote: Cognitive and Social Challenges of Ontology Use in the Biomedical Domain

  • 1. Cognitive and Social Challenges of Ontology use in the Biomedical Domain SLE 2012: 5th International Conference on Software Language Engineering Dresden, Germany Margaret-Anne Storey The CHISEL Group, University of Victoria
  • 2. Studying and addressing human aspects in software engineering and knowledge engineering
  • 3. Research methods used: – Mixed methods (analysis of archival data, interviews, grounded theory, surveys etc.) Technologies explored: – Visualization techniques – Collaboration support – Social media
  • 4. Focus of this talk: Providing cognitive support for ontology developers and users throughcollaborative visual user interfaces
  • 5. Ontology Ontology Ontology Creation Library Applications Background BioPortal Annotation Examples Services Search Tools Mappings
  • 6. Ontology Ontology Ontology Creation Library Applications Background BioPortal Annotation Examples Services Search Tools Mappings
  • 8. The study of being
  • 9. Co-opted by computer science to enable the explicit specification of Entities Propertiesand attributes of entities Relationsbetween entities
  • 10. One definition… Explicit specification of a conceptualization [Gruber, 1993]
  • 12. Ontology languages Choice of language and choice of reasoning engine Tradeoff between expressiveness, reasoning power, tractability and human understanding May need inference engine to give real-time feedback while authoring an ontology
  • 18. Challenges? Cognitive issues: – Complexity, scale – Evolution – Inclusion of “upper ontologies”, or parts of other ontologies Social issues: – One size does not fit all – Multiple authors – Input from broader set of stakeholders
  • 19. Ontology Ontology Ontology Creation Library Applications Background BioPortal Annotation Examples Services Search Tools Mappings FMA, GO, ICD
  • 20. Foundational Model of Anatomy (FMA) Comprehensive ontology of human anatomy Over 120K terms, 2.1M relationship instances (168 relationship types) One of the largest and best developed ontologies in biomedicine, multi-purpose Slide by Mark Musen.
  • 21. Slide by Mark Musen.
  • 22. Gene Ontology (GO) To unify representation of gene and gene product attributes across all species For annotating genes and gene products, assimilate and disseminate annotation data Contains over 24,500 terms applicable to a wide variety of biological organisms A standard tool in bioinformatics
  • 24. International Classification of Diseases (ICD) • An enumeration of diseasesthat forms the basis for medical claims and reimbursements • A “legacy” terminology that has its roots in 19th century epidemiology • Created initially by biostatisticians with a pressing need to compare death statistics in different European countries Slide by Mark Musen.
  • 25. ICD is used for lots of (too many?) things! • ICD is used to code all patient encounters with the health-care system for: – Billing and reimbursement – Institutional planning – Disease surveillance and public health – Quality assurance – Economic modeling • ICD was never intended to make the distinctions relevant to all these tasks! • Nevertheless it is widely used! Slide by Mark Musen.
  • 26. ICD: An excerpt… 724 Unspecified disorders of the back 724.0 Spinal stenosis, other than cervical 724.00 Spinal stenosis, unspecified region 724.01 Spinal stenosis, thoracic region 724.02 Spinal stenosis, lumbar region 724.09 Spinal stenosis, other 724.1 Pain in thoracic spine 724.2 Lumbago 724.3 Sciatica 724.4 Thoracic or lumbosacral neuritis 724.5 Backache, unspecified 724.6 Disorders of sacrum 724.7 Disorders of coccyx 724.70 Unspecified disorder of coccyx 724.71 Hypermobility of coccyx 724.71 Coccygodynia 724.8 Other symptoms referable to back 724.9 Other unspecified back disorders Slide by Mark Musen.
  • 27. ICD9 (1977): A handful of codes for traffic accidents Slide by Mark Musen.
  • 28. ICD10 (1999): 587 codes for such accidents V31.22 Occupant of three-wheeled motor vehicle injured in collision with pedal cycle, person on outside of vehicle, nontraffic accident, while working for income W65.40 Drowning and submersion while in bath-tub, street and highway, while engaged in sports activity X35.44 Victim of volcanic eruption, street and highway, while resting, sleeping, eating or engaging in other vital activities Slide by Mark Musen.
  • 29. ICD revision process in the 20th Century… • International and National Revision conferences • 1-5 person delegations in International conferences, multi-disciplinary • Manual curation • Output: paper copy • Negotiation process: decibel method of discussion • ICD drafts translated into 27 languages See http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2950305/
  • 30. ICD-11 revision: key aspects • Content model • Topic Advisory Groups – vertical and horizontal • Classification experts (ontology development) • iCAT: web based collaborative authoring tool • Use cases – evaluating ICD-11 in use
  • 31. Deliverables • Print versions –fit for purposein multiple languages • Web portal to access, browse and maintain it – Input from the crowd • Classification in formalized language
  • 32. Ontology Ontology Ontology Creation Library Applications Background BioPortal Annotation Examples Services Search Tools Mappings FMA-Explorer, Protégé, iCAT
  • 33. Foundational Model Explorer University of Victoria 33
  • 34. Protégé ontology authoring environment Ontology contents need to be processed and interpreted by computers Interactive tools can assist developers in ontology authoring (e.g. Protégé)
  • 37. iCAT web based authoring tool for ICD-11
  • 38. Ontology Ontology Ontology Creation Library Applications Background BioPortal Annotation Examples Services Search Tools Mappings
  • 39. National Center for Biomedical Ontology Goal: develop innovative technology and methods that allow scientists to record, manage, and disseminate biomedical information and knowledge in both human readable and machine-processableform
  • 43. Ontology Ontology Ontology Creation Library Applications Background BioPor Annotation Examples Services Search Tools Mappings
  • 44. BioPortal services • Ontology recommender • Ontology widgets • Annotator • API access through REST services • Virtual appliance (custom installs, can be proprietary)
  • 50. Ontology Ontology Ontology Creation Acquisition Applications Background Library Annotation Examples Services Search Tools Mappings
  • 56. Ontology Ontology Ontology Creation Acquisition Applications Background Library Annotation Examples Services Search Tools Mappings
  • 57. Data from STRIDE • 1.8 million pediatric and adult patients with clinical and demographic data (1994 - present) • 19 million Clinical Encounters (1994 - present) 35 million 22 million 2.9 million 1.2 million 7 million 137 million 10 million Slide by Nigam Shah.
  • 58. Making EMRs Unreasonably Effective Text clinical note BioPortal – knowledge graph Creating clean lexicons Diseases Frequency Term – 1 : Term recognition tool : NCBO Annotator Procedures : Annotation Workflow Syntactic types Term – n Drugs Terms Recognized P1 ICD9 ICD9 ICD9 ICD9 ICD9 ICD9 P1 T1, … T5, … T4, T8, … T6, T1, Further Analysis T2, T4, T3, T9, T8, T2, no T4 T3 T1 T4 T10 no T4 P2 P2 P3 Negation detection Cohort of Interest P3 : : Pn Pn Terms form a temporal series of tags  Slide by Nigam Shah.
  • 59. P1 ICD9 ICD9 ICD9 ICD9 ICD9 ICD9 P1 T1, … T5, … T4, T8, … T6, T1, T1 … … Tn T2, T4, T3, T9, T8, T2, no T4 T3 T1 T4 T10 no T4 P1 1 0 1 1 P2 P2 : 0 1 1 0 P3 P3 : 0 0 0 1 : : Pn 0 1 0 1 Pn Pn T1 … … Tn P1 … … Pn T1 1 0.6 0.5 0.6 P1 1 0.1 0.7 0.8 : 1 0.2 0.3 : 1 0.5 0.8 : 1 0.1 : 1 0.4 Who is getting Tn 1 Pn 1 What is special these drugs, about these conditions, etc? patients? Comparative cephalexin cane Drug Safety doppler ultrasonography ultrasound imaging Effectiveness amoxicillin doppler studies angioplasty atherectomy revascularization wheelchair cilostazol vascular surgical bypass graft Learning hydralazine congestive heart diagnostic procedures Predictions from Data pneumonia imaging surgical revision failure bypass heart failure nifedipine testosterone amiodarone pravastatin vascular diseases carotid pantoprazole insulin glargine endarterectomy obesity transplantation ramipril fentanyl zolpidem trimethoprim decompressive incision coronary sulfamethoxazole diazepam angiography fluoroscopic heart angiography transplantation tacrolimus temazepam Slide by Nigam Shah.
  • 60. Drug Safety: Detecting Risk Signals ROR of 1.5, CI of [1.11, 2.13] The X2 p-value <10-7 MI No MI Vioxx a b No Vioxx c d Slide by Nigam Shah.
  • 61. Ontology uses See http://research.microsoft.com/en-us/projects/ontology/
  • 65. Ontology Ontology Ontology Creation Acquisition Applications Background Library Annotation Examples Services Search Tools Mappings
  • 72. Ontology Ontology Ontology Creation Acquisition Applications Background Library Annotation Examples Services Search Tools Mappings What’s next?
  • 73. Towards collaborative ontology visualization as a service • Preserve easy-to-use visualizations of ontologies • Enable flexible visual exploration and analysis of biomedical ontologies and data • Support collaboration in visual exploration and analysis of biomedical ontologies and data • Enable presentation of analysis artifacts on the web
  • 74. BioMixer An online platform for the visual exploration of multiple biomedical ontologies
  • 77. Demo
  • 83. Ontology Ontology Ontology Creation Library Applications Background BioPortal Annotation Examples Services Search Tools Mappings Summary
  • 84. Concluding remarks • Ontologies finally coming of age(D. McGuinness) • With adoption, novel tools will emerge • Users now savvy with search, visualization and analytics • Anticipated benefits for translational research “Developers do not innovate tools, users do”
  • 85. Selected References Gruber T., A Translation Approach to Portable Ontologies. Knowledge Acquisition 5(2):199-220, 1993 ICD11: http://www.youtube.com/user/whoicd11 Ernst, N.A., Storey, M.A., Allen, P.: Cognitive support for ontology modeling. International Journal of Human-Computer Studies 62(5), 553–577 (2005) Fu, B., Grammel, L., Storey, M.A.: BioMixer: A Web-based Collaborative Ontology Visualization Tool. 3rd International Conference on Biomedical Ontology (ICBO 2012) (2012) Gruber, T.R.: Towards Principles for the Design of Ontologies Used for Knowledge Sharing. In: Guarino, N., Poli, R. (eds.) Formal Ontology in Conceptual Analysis and Knowledge Representation. vol. 43, pp. 907–928. Kluwer Academic Publishers (1993) Katifori, A., Halatsis, C., Lepouras, G., Vassilakis, C., Giannopoulou, E.: Ontology visualization methods— a survey. ACM Computing Surveys 39(4) (2007) Musen, M.A., Noy, N.F., Shah, N.H., Chute, C.G., Storey, M.A., Smith, B., Team, the NCBO: The National Center for Biomedical Ontology. Journal of the American Medical Informatics Association (In press.) (2012), http://bmir.stanford.edu/file_asset/index.php/1729/BMIR-2011-1468.pdf Noy, N.F., Shah, N.H., Whetzel, P.L., Dai, B., Dorf, M., Griffith, N., Jonquet, C., Rubin, D.L., Storey, M.A., Chute, C.G., Musen, M.A.: BioPortal: ontologies and integrated data resources at the click of a mouse. Nucleic acids research 37(Web Server issue) (Jul 2009) Smith, B.: Ontology (Science). Nature Precedings (i) (Jul 2008) Tudorache, T., Falconer, S., Noy, N., Nyulas, C., ¨Ust¨un, T., Storey,M.A., Musen, M.: Ontology development for the masses: creating ICD-11 in WebProt´eg´e. In: Knowledge Engineering and Management by the Masses, EKAW2010. pp. 74–89. Springer (2010)

Editor's Notes

  1. Useful for independent explorations and comparisonsCould include video of demo here.
  2. Couldlabel the data graph (make it clear that it is our internal datastructure, which runs on the client (and the actual data can be different on each client), and we build it by calling the REST services)