Presentation at RDA P11 IGAD pre-meeting – Berlin, March 2018

1. FAIR data requires FAIR ontologies,
how do we do?
Clement Jonquet, PhD
Assistant Professor – LIRMM, University of Montpellier
Visiting Scholar at Stanford University
RDA P11 IGAD pre-meeting – Berlin, March 2018

2. As any data, ontologies need to be FAIR
• The FAIR principles have established the importance of using standards
vocabularies or ontologies to describe FAIR data and to facilitate interoperability
and reuse…
• Explosion of the number of ontologies/vocabularies
• Cumbersome to identify
the ontologies we need
and manage their overlap.

3. Review of ontology metadata practices:
Methods
• Conducted three different studies:
1. Analysis of the existing metadata vocabularies for describing ontologies & literature survey
• More than 23 vocabularies, around 450 properties reviewed
2. Analysis of the uses of metadata vocabularies in describing the ontologies (by the ontology
developers)
• 805 ontologies analyzed
3. Analysis of the uses of metadata vocabularies in various ontology repositories
• 12 libraries
C. Jonquet – RDA P11 IGAD pre-meeting – Berlin, March 2018

4. Review of ontology metadata practices:
Findings
• Developers use a variety of metadata vocabularies (e.g., DC, DCT, PROV,VOID, DCAT, SCHEMA)
• Interestingly: the only ontology specific metadata OMV (first published in 2005) is found to be hardly used by the community
• No existing vocabularies really covers enough aspects of ontologies to be used solely and despite
• Despite a few exceptions, metadata vocabularies do not rely on one another although there is a strong overlap
observed
• Multiple properties to capture similar information (e.g., dc:license, and cc:license)
• Strong overlap in all the vocabularies (25 properties available for dates)
• Reviewed libraries uses, to some extent, some metadata elements but do not always use standard metadata vocabularies
• 16% of ontologies did not use any metadata properties, 43% use less than 10 properties
• Properties facilitated by ontology editors are more frequent
• General purpose elements (e.g., rdfs:comment, owl:versionOf and owl:imports) are found to be the most frequently
used elements
• Confusion of use: DC/DCT or SKOS documentation properties used to describe ontologies
C. Jonquet – RDA P11 IGAD pre-meeting – Berlin, March 2018

5. Ontology repositories help
to make ontologies FAIR

8. Linked Open Data cloud in
2017
(http://lod-cloud.net)
NCBO BioPortal
data as of 2013

9. Ontology repositories help to make ontologies FAIR
InteroperableFindable Accessible Re-usable

10. Ontology libraries, registries, repositories
• Ontology libraries defined as
• “a library system that offers various functions for managing, adapting and
standardizing groups of ontologies. It should fulfill the needs for re-use of ontologies. In
this sense, an ontology library system should be easily accessible and offer efficient
support for re-using existing relevant ontologies and standardizing them based on
upper-level ontologies and ontology representation languages.” [Ding & Fensel, 2001]
• Ontology repositories defined as
• “a structured collection of ontologies (…) by using an Ontology MetadataVocabulary.
References and relations between ontologies and their modules build the semantic
model of an ontology repository.Access to resources is realized through semantically-
enabled interfaces applicable for humans and machines.Therefore a repository
provides a formal query language” [Hartmann, Palma, Gomez-Perez, 2009]

11. What are the ontology libraries out there?
• Ontology repositories / portal
• NCBO BioPortal
• Ontobee
• AberOWL
• EBI Ontology Lookup Service
• OKFN Linked OpenVocabularies
• ONKI Ontology Library Service
• MMI Ontology Registry and Repository
• ESIPportal
• AgroPortal
• SIFR BioPortal
• CISMEF HeTOP
• OntoHub
• Web indexes
• Watson, Swoogle,
Sindice, Falcons
• Ontology libraries / listings (more or less updated)
• OBO Foundry
• WebProtégé
• Romulus
• DAML ontology library
• Colore
• FAOVEST Registry
• BioSharing
• DERIVocabularies , OntologyDesignPatterns,
Semanticweb.org,W3C Good ontologies
• ANDS
• Platform technology
• Mondeca ITM, LexEVS, SKOSMOS, SissVoc
• Abandoned projects
• Cubboard, Knoodl, Schemapedia, SchemaWeb,
OntoSelect, OntoSearch,TONES

12. Focus on NCBO BioPortal : a “one stop shop” for biomedical
ontologies
• Web repository for biomedical ontologies
• Make ontologies accessible and usable –
abstraction on format, locations, structure, etc.
• Users can publish, download, browse, search,
comment, align ontologies and use them for
annotations both online and via a web services
API.

13. • Online support for
ontology
• Peer review & notes
• Versioning
• Mapping
• Search
• Resources
• Annotation
• Open source technology
• Packaged in a “virtual
appliance”
• Set up your own
“bioportal” in a few
hours

14. http://bioportal.bioontology.org
Ontology
Services
• Search
• Traverse
• Comment
• Download
Widgets
• Tree-view
• Auto-complete
• Graph-view
Annotation
Data Access
Mapping
Services
• Create
• Upload
• Download
Term recognition
Search data
annotated with a
given term
http://data.bioontology.org

15. Who has been reusing NCBO technology so far?
• Recently
• AgroPortal (http://agroportal.lirmm.fr) – agronomy, food, plant sciences, biodiveristy
• SIFR/French BioPortal (http://bioportal.lirmm.fr) – French biomedical ontologies & terminologies
• BiblioPortal (http://biblio.ontoportal.org) – libraries and metadata standards
• EcoPortal – ongoing discussion with the Lifewatch/LTER projects for a more focused portal on ecology & biodiversity
• Historically
• NCI term browser (https://nciterms.nci.nih.gov) – BioPortal first, then LexEVS
• Open Ontology Repository (OOR) Initiative (http://www.oor.net) – Now stopped. Looked also at OntoHub
• Marine Metadata Interoperability Ontology Registry and Repository (http://mmisw.org)
• ESIPPortal (Earth Science Information Partners - http://semanticportal.esipfed.org )
• And a few hospitals, research labs, with private data and specific needs (often in-house annotation)

16. AgroPortal: a vocabulary and ontology
repository for agronomy

17. AgroPortal: a vocabulary and ontology repository for agronomy
http://agroportal.lirmm.fr
• Develop and support a reference ontology repository
• Primary focus on the agronomy & close related domains (food, plant sciences and biodiversity)
• Reusing the NCBO BioPortal technology
• Avoid to re-implement what has been done, facilitate interoperability
• Reusing the scientific outcomes, experience & methods of the biomedical domain
• Enable straightforward use of agronomy ontologies
• Respect the requirements & specificities of the agronomic community
• Fully semantic web compliant infrastructure
• Enable new science
Jonquet, C., Toulet, A., Arnaud, E., Aubin, S., DzaléYeumo, E., Emonet, V., Graybeal, J.,
Laporte, M.-A., Musen, M.A., Pesce, V., Larmande, P., AgroPortal: A vocabulary and
ontology repository for agronomy. Comput. Electron. Agric. 144, (Jan 2018).

18. AgroPortal an ontology
repository for
agronomy, food, plant
sciences & biodiversity
Publish, search,
download
Browse, visualize
Peer review
Versioning
Annotation
Recommendation
Mapping
Notes
Projects
80 ontologies, 95 candidates
5 driving use cases
~90 registered users
http://agroportal.
lirmm.fr

19. AgroPortal
Annotator
identifies ontology
concepts within plain
text for semantic
indexing

20. Align ontologies one another
concept
by
concept

21. AgroPortal
Recommender
get the most relevant
ontologies for your data

22. Harnessing the power of metadata to
facilitate the comprehension of the
agronomical ontology landscape

23. A new metadata model to
better support description of
ontologies and their relations
• Building a list of properties to
describe ontologies
• Pickup properties and relations
from 23 existing vocabularies
• Existing properties in ontology
repositories (especially BioPortal)
• Non specific properties that “belong
to the ontology”
346 relevant properties that could be
used to described ontologies
127 used to build a new metadata
model inside AgroPortal
Ontology
repositories
metadata
Other Interesting
vocabularies (e.g.,
IDOT, PAV, SD,
DOAP, …)
Standards &
Relevant (e.g.,
DC, DCAT, SKOS,
OWL, PROV,
OMV,VOID,
VOAF, MOD …)

24. Describe ontologies with
semantic metadata
• Display “per ontology”
• Ontology specific properties => viewable and
editable within the ontology specific page
• Everything you need to know about an ontology
• URIs used in the backend to store the information
• e.g., CC-BY =>
https://creativecommons.org/licenses/by-nd/4.0/
• Get my metadata back button

25. Browse and select
ontologies
• Allows to search, order and select ontologies using
a facetted search approach, based on the metadata
• 4 additional ways to filter ontologies in the list
• 2 new options to sort this list (name, released
date).

26. AgroPortal Landscape page
Display “per property”
• Global presentation of the properties
• Synthesis diagrams & listing
• Metadata automatically extracted from the files and authored by us and
the ontology developpers
• Allows to explore the agronomical ontology landscape by automatically
aggregating the metadata fields of each ontologies in explicit
vizualizations (charts, term cloud and graphs).
Jonquet, C., Toulet, A., Dutta, B., Emonet, V.: Harnessing the power of unified
metadata in an ontology repository: the case of AgroPortal. Data Semant.
UNDER REVIEW.

27. All of it accessible thru JSON-LD API

28. On going work within RDA groups

29. Involvement in several groups
• Several IGAD interest groups interested by AgroPortal:
• Agrisemantics,
• Wheat/Rice Data Interoperability
• Synchronization with FAIRsharing
• Ontology-metadata Task Group inside Vocabulary and Semantic
Services Interest Group (VSSIG)

30. • Metadata vocabulary for Ontology
Description and publication (v.1.2)
• 88 properties, only 13 new ones
• https://github.com/sifrproject/MOD-
Ontology
• To be discussed within the RDA
Vocabulary and Semantic Services Interest
Group (VSSIG)
Generalizing this with
MOD
Dutta, B., … Jonquet, C.: New Generation Metadata vocabulary for
Ontolog yDescription and Publication. 11th Metadata and Semantics
Research Conference, MTSR’17. , Tallinn, Estonia (2017).

31. Conclusion
• Good ontologies are required for FAIR data
• Metadata are important to FAIR ontologies
• Continue our work on repository ontologies to ease the sharing of FAIR ontologies
and vocabularies
• Measure FAIRness level
for ontologies with metrics

32. Credits
• Anne Toulet,Vincent Emonet
LIRMM – University of Montpellier, France
• Biswanath Dutta
Documentation Research andTraining Centre (DRTC)
Indian Statistical Institute, Bangalore, India
• RDA Vocabulary and Semantic Services Interest Group (VSSIG)
Ontology-metadataTask Group
• The same +
• Barbara Magagna
Ecosystem Research & Environmental Information Management
Ökosystemforschung & Umweltinformationsmanagement

33. Thank you!
jonquet@lirmm.fr
@jonquet_lirmm