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Controlled vocabularies definition methodfor bridging formal ontologies
development
Paolo Ciccarese, PhDMass General Hospital / Harvard Medical School
Background
• AlzForum http://www.alzforum.org/• Semantic Web Applications in Neuromedicine
SWAN: http://swan.mindinformatics.org/SWAN Alzheimer: http://hypothesis.alzforum.org/
• Science Collaboration FrameworkSCF: http://www.sciencecollaboration.org/StemBook: http://www.stembook.org/
• HCLSIG Scientific Discourse Task Forcehttp://esw.w3.org/topic/HCLSIG/SWANSIOC
time
SWAN Ontology Ecosystem
Domain Ontologies
Qualifiers
Basic
An example of SWAN content curationSeeding neuritic plaques from
the distance: a possible role for brainstem neurons in the
development of Alzheimer's disease pathology.
Muresan Z, Muresan V
SWAN CuratorGwen Wong, PhD
Journal Article
SWAN Workbench
Triple store
SWAN Browser
CommentsQualifiers
Kim hypothesis
Graph view
An example of Research Statement
Relationships between discourse elements
Life Science Entities - 1Research Statement
refersTo
refersTo
Life Science Entities - 2Research Statement
But…
• Creating ontologies takes time long time• Creating ontologies requires skilled
knowledge engineers and skilleddomain experts
• The time needed for developingontologies is influencing the applicationdevelopment
• Is creating ontologies always theoptimal solution?
SWAN Additional Annotation - 1Research Statement
qualifiedBy
qualifiedBy
Mechanisms Taxonomy
Pathogenic Narrative
Hypothesis
Claim
qualifiedBy
Other Additional Annotation - 2
* Nature Reports - Stem Cells Cheat SheetNature Publishing Group
Need for controlled vocabularies
• Using terms coming from controlledvocabularies is a good compromise inthe case of high quality human curatedscientific content
• Maybe we can use controlledvocabularies as an easy andincremental method to get to formalontologies
Requirements
• Controlled vocabularies• Controlled vocabularies should be easy and
fast to be defined by “not ontologists”• Link the terms to existing (or future)
ontologies and keep track ofprovenance/authoring
• OWL-DL but without impacting thereasoning
• Share the vocabularies in RDF format
Agile definition and mapping
• We don’t want users “not ontologists” todeal with classes, properties andrestrictions
• Taxonomies are often enough forsimple classifications and can bedefined easily (terms + definitions)
• We want trained ontologists to figureout how to map the terms to existingontologies (if we have resources to doso)
Possible solution: SKOSThe Simple Knowledge Organization System provides amodel for expressing the basic structure and content ofconcept schemes such as thesauri, classification schemes,subject heading lists, taxonomies, folksonomies, and othersimilar types of controlled vocabulary.
How to refer to formal ontologies?
? ?
An example
er
skos:Concept qualifiers:Meaning
owl:Thing
qualifiers:exactMeaningqualifiers:broaderMeaningqualifiers:narrowerMeaning
qualifiers:meaningURI
Mapping to formal ontology
HSC Haematopoietic stem cells (blood-forming stem cells that reside in bone
marrow) 2009-01-28T00:00:00+05:00 2009-01-29T10:00:00+05:00 Paolo Ciccarese
Meaning Of A Tag (MOAT) - 1
Meaning Of A Tag (MOAT) - 2
http://moat-project.org/
Alignment with MOATMeaning
moat:Meaningqualifiers:Meaning
moat:hasMeaning
hasMeaning
qualifiers:hasExactMeaning
meaningURI
moat:meaningURIqualifiers:meaningURI
range
domain
ConclusionsEasy to implement (alsoat application level)OWL-DL (with OWL2 -punning)ProvenanceMapping to existingontologiesDoesn’t changereasoning (unless we post-process the annotation)Aligned with MOAT
Introduces a level ofcomplexity (but wecan always post-process theannotation)
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