SlideShare a Scribd company logo
#VIVOifest15
Karma data integration:
creating semantic web
compliant VIVO data
Violeta Ilik @violetailik
Galter Health Sciences Library
Feinberg School of Medicine
Northwestern University Clinical and
Translational Sciences Institute (NUCATS), Chicago, IL
https://galter.northwestern.edu/staff/Violeta-Ilik
http://vivo.vivoweb.org/display/n10603
#VIVOifest15
Outline:
•  Examine your data
•  Clean your data
•  Create local ontology extensions (optional)
•  Model your data
•  Load your data
Violeta Ilik @violetailik
#VIVOifest15
Examine your data
Accommodate within existing ontologies most of your
data
Opt for local extensions if necessary
•  Local unique identifiers (people & organizations)
•  Specific needs (publication types; non-traditional
scholarly outputs …)
Violeta Ilik @violetailik
#VIVOifest15
Clean your data
•  Utilizing local resources and skills
– polyglot programing skills (Python, Perl,
XSLT, SAS, R, OpenRefine)
Violeta Ilik @violetailik
#VIVOifest15
Ontology: VIVO core
Violeta Ilik @violetailik
#VIVOifest15
VIVO local ontology extensions
Violeta Ilik @violetailik
#VIVOifest15
Modeling organizations/units data
Violeta Ilik @violetailik
#VIVOifest15
Modeling organizations/units data
Violeta Ilik @violetailik
#VIVOifest15
Modeling person data
Violeta Ilik @violetailik
#VIVOifest15
Modeling person data
Violeta Ilik @violetailik
#VIVOifest15
Modeling person’s positions data
Violeta Ilik @violetailik
#VIVOifest15
Modeling person’s positions data
Violeta Ilik @violetailik
#VIVOifest15
Modeling publications data –
academic articles
Violeta Ilik @violetailik
#VIVOifest15
Modeling publications data –
comparative study
Violeta Ilik @violetailik
#VIVOifest15
References:
•  https://github.com/vioil/ontology_extensions
•  https://github.com/vioil/R2RML-Karma
• https://www.youtube.com/channel/
UCb9vsw2XvZDzZtEwe0aH9eA
•  http://www.isi.edu/integration/karma/
Violeta Ilik @violetailik
#VIVOifest15
Discussion
Thank you
Violeta Ilik
Violeta Ilik @violetailik

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