Scalable representations of diseases in biomedical ontologies
Analyzing User Interactions with Biomedical Ontologies: A Visual Perspective
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Transcript of Analyzing User Interactions with Biomedical Ontologies: A Visual Perspective
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AnalyzingUserInteractionswithBiomedicalOntologies:AVisualPerspective
TuesdayTalk,14thNovember2017
MAU L I K K AMDA R , S IMON WA L K , T A N I A T U DO R A C H E , MA R K MU S E N
StanfordCenterforBiomedicalInforma:[email protected]
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Uses: Knowledge management, decision support, semantic search, data annotation, data integration, reasoning …
…
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Uses: Knowledge management, decision support, semantic search, data annotation, data integration, reasoning …
…
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hGp://bioportal.bioontology.org/
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hGp://bioportal.bioontology.org/
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hGp://bioportal.bioontology.org/
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hGp://bioportal.bioontology.org/
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hGp://bioportal.bioontology.org/
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Whatthistalkisabout…
• BiOnIC-CatalogofUserInteracRonswith
BiomedicalOntologies
• VisIOnapplicaRonwithembeddedvisualizaRons.
AnalysisofBioPortalWebUI
exploraRonandAPI
queryingstrategies,and
correlaRonwithusage.
![Page 14: Analyzing User Interactions with Biomedical Ontologies: A Visual Perspective](https://reader035.fdocuments.net/reader035/viewer/2022062401/5a66870f7f8b9ac3578b47eb/html5/thumbnails/14.jpg)
Whatthistalkisabout…
• BiOnIC-CatalogofUserInteracRonswith
BiomedicalOntologies
• VisIOnapplicaRonwithembeddedvisualizaRons.
AnalysisofBioPortalWebUI
exploraRonandAPI
queryingstrategies,and
correlaRonwithusage.
![Page 15: Analyzing User Interactions with Biomedical Ontologies: A Visual Perspective](https://reader035.fdocuments.net/reader035/viewer/2022062401/5a66870f7f8b9ac3578b47eb/html5/thumbnails/15.jpg)
BenefitsofanalyzinguserinteracRons
Ø OntologyEngineers:v IdenRfyexploraRonandqueryingpaGernsv Understandontologyusageandreusev PruneunwantedclassesandrelaRons
Ø OntologyRepositoryMaintainers:v Categorizeuserbehaviorsv Developintelligentinterfacesv ProvidetargetedrecommendaRons
Ø BiomedicalResearchers:v IdenRfytemporalresearchtrends
v IdenRfyfrequentlyaccessedclasses
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BiOnIC:ACatalogofUserInteracRonswith
BiomedicalOntologies
hGp://onto-apps.stanford.edu/bionic/datasets
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BiOnICdatasetscreaRon
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NCBO API Usage
API R
eque
sts
per M
onth
2013−O
ct
2014−J
an
2014−A
pr
2014−J
ul
2014−O
ct
2015−J
an
2015−A
pr
2015−J
ul
2015−O
ct
2016−J
an
2016−A
pr
2016−J
ul
2016−O
ct
2M8M
32M
Filtering
AccessLogs
Filtering
Ontologies
CompuRng
ClassCounts
CompuRng
Sequences
Anonymizing
Data
NCBO Website Traffic
Occ
urre
nces
per
Mon
th
2009−J
an
2010−J
an
2011−J
an
2012−J
an
2013−J
an
2014−J
an
2015−J
an
2016−J
an
010
0K20
0K
Page RequestsUnique IP Addresses
BiOnICdatasetscreaRon
• Removingrobot/invalid
requests
• Normalizingontology
idenRfiersandclassIRIs
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Filtering
AccessLogs
Filtering
Ontologies
CompuRng
ClassCounts
CompuRng
Sequences
Anonymizing
Data
BiOnICdatasetscreaRon
• January2015version.
• Ontologiesshouldhave
classesthatarereusedby
othersORreuseclasses
fromotherontologies.
• Ontologiesshouldhave
minimumof10unique
usersviaWebUIandAPI
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Filtering
AccessLogs
Filtering
Ontologies
CompuRng
ClassCounts
CompuRng
Sequences
Anonymizing
Data
BiOnICdatasetscreaRon
ClassSta:s:csDatasets
Foreachclassineachontology:
• AccessANributes:o TotalIPRequests(WebUI/API)
o UniqueIPRequests(WebUI/API)
• ReuseANributes:o Numberofontologiesreusingaclass
• StructuralANributes:o Numberofparent/child/siblingclasses
o Depthfromontologyroot
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Filtering
AccessLogs
Filtering
Ontologies
CompuRng
ClassCounts
CompuRng
Sequences
Anonymizing
Data
BiOnICdatasetscreaRon
UserInterac:onSequencesDatasets
Ontology1
Ontology2
ClassDepth->
2a
1
3a 4a
4b
4c2b
3b
3c
1’
2a’
2b’
2c’
3a’
3b’
3c’
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Filtering
AccessLogs
Filtering
Ontologies
CompuRng
ClassCounts
CompuRng
Sequences
Anonymizing
Data
BiOnICdatasetscreaRon
UserInterac:onSequencesDatasets
Ontology1
Ontology2
ClassDepth->
2a
1
3a 4a
4b
4c2b
3b
3c
1’
2a’
2b’
2c’
3a’
3b’
3c’
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Filtering
AccessLogs
Filtering
Ontologies
CompuRng
ClassCounts
CompuRng
Sequences
Anonymizing
Data
BiOnICdatasetscreaRon
UserInterac:onSequencesDatasets
Ontology1
Ontology2
ClassDepth->
2a
1
3a 4a
4b
4c2b
3b
3c
1’
2a’
2b’
2c’
3a’
3b’
3c’
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Filtering
AccessLogs
Filtering
Ontologies
CompuRng
ClassCounts
CompuRng
Sequences
Anonymizing
Data
BiOnICdatasetscreaRon
UserInterac:onSequencesDatasets
Ontology1
Ontology2
ClassDepth->
2a
1
3a 4a
4b
4c2b
3b
3c
1’
2a’
2b’
2c’
3a’
3b’
3c’
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Filtering
AccessLogs
Filtering
Ontologies
CompuRng
ClassCounts
CompuRng
Sequences
Anonymizing
Data
BiOnICdatasetscreaRon
UserInterac:onSequencesDatasets
Ontology1
Ontology2
ClassDepth->
2a
1
3a 4a
4b
4c2b
3b
3c
1’
2a’
2b’
2c’
3a’
3b’
3c’
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Filtering
AccessLogs
Filtering
Ontologies
CompuRng
ClassCounts
CompuRng
Sequences
Anonymizing
Data
BiOnICdatasetscreaRon
UserInterac:onSequencesDatasets
Ontology1
Ontology2
ClassDepth->
2a
1
3a 4a
4b
4c2b
3b
3c
1’
2a’
2b’
2c’
3a’
3b’
3c’
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Filtering
AccessLogs
Filtering
Ontologies
CompuRng
ClassCounts
CompuRng
Sequences
Anonymizing
Data
BiOnICdatasetscreaRon
UserInterac:onSequencesDatasets
Ontology1
Ontology2
ClassDepth->
2a
1
3a 4a
4b
4c2b
3b
3c
1’
2a’
2b’
2c’
3a’
3b’
3c’
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Filtering
AccessLogs
Filtering
Ontologies
CompuRng
ClassCounts
CompuRng
Sequences
Anonymizing
Data
BiOnICdatasetscreaRon
UserInterac:onSequencesDatasets
Ontology1
Ontology2
ClassDepth->
2a
1
3a 4a
4b
4c2b
3b
3c
1’
2a’
2b’
2c’
3a’
3b’
3c’
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Filtering
AccessLogs
Filtering
Ontologies
CompuRng
ClassCounts
CompuRng
Sequences
Anonymizing
Data
BiOnICdatasetscreaRon
UserInterac:onSequencesDatasets
Ontology1
Ontology2
ClassDepth->
2a
1
3a 4a
4b
4c2b
3b
3c
1’
2a’
2b’
2c’
3a’
3b’
3c’
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Filtering
AccessLogs
Filtering
Ontologies
CompuRng
ClassCounts
CompuRng
Sequences
Anonymizing
Data
BiOnICdatasetscreaRon
UserInterac:onSequencesDatasets
Ontology1
Ontology2
ClassDepth->
2a
1
3a 4a
4b
4c2b
3b
3c
1’
2a’
2b’
2c’
3a’
3b’
3c’
![Page 31: Analyzing User Interactions with Biomedical Ontologies: A Visual Perspective](https://reader035.fdocuments.net/reader035/viewer/2022062401/5a66870f7f8b9ac3578b47eb/html5/thumbnails/31.jpg)
2a’ 1’ 2b’ 3b’
2a 3a 4a 3a1
Filtering
AccessLogs
Filtering
Ontologies
CompuRng
ClassCounts
CompuRng
Sequences
Anonymizing
Data
BiOnICdatasetscreaRon
UserInterac:onSequencesDatasets
Ontology1
Ontology2
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Filtering
AccessLogs
Filtering
Ontologies
CompuRng
ClassCounts
CompuRng
Sequences
Anonymizing
Data
BiOnICdatasetscreaRon
Anonymiza:onSteps
• IPaddressesanonymizedusinguniqueSHA-224hash-encoded
useridenRfiersgeneratedfrom“user_<Random
String>_<Random_Integer>”.
• e.g.39fd4e6d569a034973g61bb392a694d4eabe1ef98c43ee68ca2fc86
• AbsoluteTime-stampsconvertedtorelaRveRme-stamps,with
respecttofirstinteracRonwithBioPortalrepository.
• e.g.0,2757,2786,3586,3618,3803,3959,4047,5111(s),…
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BiOnICschematomodelstaRsRcsandsequencesdata
countStat
bionic:CountStat
bionic:ReuseCount- reuseType
- reusingOntologies
bionic:RequestCount- accessType
- year
- totalUsers
- uniqueUsers
prov:Agent bionic:Sequence- accessType
- totalTime
- uniqueClasses
bionic:SeqEn:ty- rela6veTimestamp
bionic:Ontology- skos:prefLabel
- totalClasses
- maxDepth
owl:Class-skos:prefLabel
skos:Collec:on skos:Concept
begin
end
nextEn6ty
class
class
requests
skos:member
bionic:SeqDataset- accessType
bionic:StatDatasetdcat:Dataset
sequence
classInfo
ontology
ontology
bionic:ClassInfo- siblings
- directParents
- directChildren
- classDepth
class
subClassOf
ontology
SKOS,PROVandDCATstandardsarereusedintheBiOnICschema.
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hGp://onto-apps.stanford.edu/bionic/datasets
BiOnICdatasets
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hGp://onto-apps.stanford.edu/bionic/datasets
BiOnICdatasets
hGp://www.rdjdt.org/
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hGp://onto-apps.stanford.edu/bionic/datasets
BiOnICdatasets
hGp://www.rdjdt.org/
SPARQLServer
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hGp://onto-apps.stanford.edu/bionic/datasets
BiOnICdatasets
hGp://www.rdjdt.org/
SPARQLServer
BioPortalSPARQLEndpoint
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hGp://onto-apps.stanford.edu/bionic/datasets
BiOnICdatasets
hGp://www.rdjdt.org/
SPARQLServer
BioPortalSPARQLEndpoint
1. HowmanyagentsclickonthesubclassesaIerexploringthe
“ProteinTransmembraneAc6vity”classinGeneOntology?
2. Whatistheaverage6mespentbyagentsonclassessimilarto
“CellGrowth”classinGeneOntology?
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VisIOn(VisualizingOntologyInteracRons)WebApplicaRon
hGp://onto-apps.stanford.edu/vision
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VisualizingOntologyStructurewithCountData
Force-directedNetwork IndentedTree
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VisualizingOntologyStructurewithCountData
Force-directedNetwork IndentedTree
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PolygOntovisualizaRonsofinteracRonsequences
Kamdar,etal.VisualizingRequestandReuseDataacrossBiomedicalOntologies.JournalofWebSeman:cs,(underreview)
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PolygOntovisualizaRonsofinteracRonsequences
Kamdar,etal.VisualizingRequestandReuseDataacrossBiomedicalOntologies.JournalofWebSeman:cs,(underreview)
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PolygOntovisualizaRonsofinteracRonsequences
Kamdar,etal.VisualizingRequestandReuseDataacrossBiomedicalOntologies.JournalofWebSeman:cs,(underreview)
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PolygOntovisualizaRonsofinteracRonsequences
Kamdar,etal.VisualizingRequestandReuseDataacrossBiomedicalOntologies.JournalofWebSeman:cs,(underreview)
OntologyStructure
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PolygOntovisualizaRonsofinteracRonsequences
Kamdar,etal.VisualizingRequestandReuseDataacrossBiomedicalOntologies.JournalofWebSeman:cs,(underreview)
UserSequence
OntologyStructure
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PolygOntovisualizaRonsofinteracRonsequences
Kamdar,etal.VisualizingRequestandReuseDataacrossBiomedicalOntologies.JournalofWebSeman:cs,(underreview)
UserSequence
SingleClick
OntologyStructure
![Page 48: Analyzing User Interactions with Biomedical Ontologies: A Visual Perspective](https://reader035.fdocuments.net/reader035/viewer/2022062401/5a66870f7f8b9ac3578b47eb/html5/thumbnails/48.jpg)
Whatthistalkisabout…
• BiOnIC-CatalogofUserInteracRonswith
BiomedicalOntologies
• VisIOnapplicaRonwithembeddedvisualizaRons.
AnalysisofBioPortalWebUI
exploraRonandAPI
queryingstrategies,and
correlaRonwithusage.
![Page 49: Analyzing User Interactions with Biomedical Ontologies: A Visual Perspective](https://reader035.fdocuments.net/reader035/viewer/2022062401/5a66870f7f8b9ac3578b47eb/html5/thumbnails/49.jpg)
CharacterisRcsoftheBiOnICCatalog
• WebUIAccess:5.4Mclassrequests,1Muniqueagents
• APIAccess:67.2Mclassrequests,205Kuniqueagents
• 255biomedicalontologies
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• DoBioPortalWebUIexploraRonandAPI
queryingstrategiescorrelatewitheachother?
• DoBioPortalWebUIexploraRonandAPI
queryingstrategiesinformontologyusage?
– Ontologyusage,inthiscontext,meansreusein
otherontologies,andusageindataannotaRon.
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InterfaceinfluencesinbrowsingandqueryingNum
bero
fUniqu
eAP
IUsers(LogScale)
NumberofUniqueWebUIUsers(LogScale)
1000
10
100
10 100 1000
1
1
Certainclassesbrowsedorqueriedsignificantlymore.
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InterfaceinfluencesinbrowsingandqueryingNum
bero
fUniqu
eAP
IUsers(LogScale)
NumberofUniqueWebUIUsers(LogScale)
1000
10
100
10 100 1000
FemaleReproduc:ve
System
1
1
Certainclassesbrowsedorqueriedsignificantlymore.
Dermis
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InterfaceinfluencesinbrowsingandqueryingDysmorphicSyndrome
Nightblindness
Num
bero
fUniqu
eAP
IUsers(LogScale)
NumberofUniqueWebUIUsers(LogScale)
1000
10
100
10 100 1000
FemaleReproduc:ve
System
1
1
Certainclassesbrowsedorqueriedsignificantlymore.
Dermis
![Page 56: Analyzing User Interactions with Biomedical Ontologies: A Visual Perspective](https://reader035.fdocuments.net/reader035/viewer/2022062401/5a66870f7f8b9ac3578b47eb/html5/thumbnails/56.jpg)
ExploraRonandQueryingbehavioralpaGerns
• Certainclassesinthelowerlevelsoftheontologicalhierarchyarerarelybrowsedandqueried–thismaybeanarRfactoftheindentedtreevisualizaRon.
• Moretriangularpolygons(1parent->2childrenclasses,or2parents->1childclass)observedinWebUIAccesspolygonduetoindentedtreevisualizaRon.
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ExploraRonandQueryingbehavioralpaGerns
300,000+classes200,000+users
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DoBioPortalWebUIexploraRonandAPI
queryingstrategiescorrelatewitheachother?
• SmallproporRonsofontologicalcontentexploredorqueriedfor
severalontologies,andminimalSpearmanCorrelaRonand
JaccardSimilarityobservedbetweenconsumpRonstrategies.
• VaryingconsumpRonstrategies(triangularpolygons,blind
querying)acrosstheinterfaces–thesestrategiesaregenerallyuniformacrossontologies,withafewexcepRons(ChEBI).
• ClassesinthelowerlayersoftheontologicalhierarchyarerarelybrowsedorqueriedusingtheWebUIorAPI.
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Ontologyusage:Reuseinotherontologies
Dis:nctclasssetsreusedinotherontologies
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Ontologyusage:GWASCatalogandPubChemannotaRons
Classesinthehigherlayersoftheontological
hierarchyareveryabstractandareneverusedfor
dataannotaRons.
Commonconsensusacross12differentdatasources
inLinkedOpenDatacloud,whereChEBIontologyis
usedfordataintegraRon.
![Page 61: Analyzing User Interactions with Biomedical Ontologies: A Visual Perspective](https://reader035.fdocuments.net/reader035/viewer/2022062401/5a66870f7f8b9ac3578b47eb/html5/thumbnails/61.jpg)
Ontologyusage:GWASCatalogandPubChemannotaRons
Classesinthehigherlayersoftheontological
hierarchyareveryabstractandareneverusedfor
dataannotaRons.
Commonconsensusacross12differentdatasources
inLinkedOpenDatacloud,whereChEBIontologyis
usedfordataintegraRon.
![Page 62: Analyzing User Interactions with Biomedical Ontologies: A Visual Perspective](https://reader035.fdocuments.net/reader035/viewer/2022062401/5a66870f7f8b9ac3578b47eb/html5/thumbnails/62.jpg)
DoBioPortalWebUIexploraRonandAPI
queryingstrategiesinformontologyusage?
• MinimalcorrelaRonandsimilariResbetweenexploraRonand
queryingstrategies,andusage(reuseanddataannotaRons)
• Ontologyreuseoccursfromclasseslocatedinthehigherlayersof
theontologicalhierarchyforsemanRcinteroperabilitybetween
ontologies.
• However,theseclassesareveryabstractandnotveryrelevantfordataannotaRonordataintegraRon,whereclassesinthe
lowerlayersofhierarchyarehighlyused.
– Theseclassesarerarelyexploredorqueried,weneedbeGerinterfaces!
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NovelresearchdirecRonsmaybeenabled
throughtheBiOnICandVisIOnresources
• CategorizeuserbrowsingbehaviorsbyincorporaRngthestructuralfeaturesoftheontologyclasses.
• DeveloppersonalizeduserinterfacesforontologynavigaRon,withpredicRonsofthenextclassthatauserislikelyto
access,ortargetedrecommendaRonsbasedonusertype
(recurrentneuralnetworks,collaboraRvefiltering,…).
• DevelopadvancedmethodsforontologysummarizaRonand
modularizaRon,usingBiOnICdatasetsasfeatures.
…
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Acknowledgments
MusenLab,Stanford
BMIPhDProgram,Stanford
USNIHGrants
U54-HG004028
GM086587
[email protected]://onto-apps.stanford.edu/bionic
hGp://onto-apps.stanford.edu/vision