1. Enhancing the discoverability and inter-operability of multi-disciplinary semantic repositories
Doron Goldfarb & Yann LE FRANC
EUDAT receives funding from the European Union's Horizon 2020 programme - DG CONNECT e-Infrastructures. Contract No

2. Question: Why multitude of repos, why not only one impl for all?
Answer from „Normalized access to ontology repositories„, Viljanen et al.
x) Different ontos and user needs require different functionalities
x) Some ontologies not available as file but only as service
x) Security/Business -> internal onto repos
x) Informal ontos not really in Repos

3. Problem: Where to find semantic RESOURCES
Semantic Repositories (Ontology Libraries, -Registries [d'Aquin&Noy, 2012])
Question: Why multitude of repos, why not only one impl for all?
Answer from „Normalized access to ontology repositories„, Viljanen et al.
x) Different ontos and user needs require different functionalities
x) Some ontologies not available as file but only as service
x) Security/Business -> internal onto repos
x) Informal ontos not really in Repos

4. GROWING LANDSCAPE OF SEMANTIC REPOSITORIES
LOV
Question: Why multitude of repos, why not only one impl for all?
Answer from „Normalized access to ontology repositories„, Viljanen et al.
x) Different ontos and user needs require different functionalities
x) Some ontologies not available as file but only as service
x) Security/Business -> internal onto repos
x) Informal ontos not really in Repos

5. POSES CHALLENGES for various applications
Semantic Annotation Where can I find the most suitable concept for annotating my data? Example: B2Note
Creation/Maintenance of own semantic resources Are there existing resources covering concepts relevant to my domain? Example: Environmental Thesaurus
In which repository can relevant resources be found?
Question: Why multitude of repos, why not only one impl for all?
Answer from „Normalized access to ontology repositories„, Viljanen et al.
x) Different ontos and user needs require different functionalities
x) Some ontologies not available as file but only as service
x) Security/Business -> internal onto repos
x) Informal ontos not really in Repos

6. SOLUTION: AGGREGATION OF SEMANTIC REPOSITORIES
LOV
Aggregator
Search, Align, etc

7. DISTRIBUTED VS CENTRALIZED ACCESS
LOV
BioPortal API Search „Human“
AgroPortal API Search „Human“
EBI-OLS API Search „Human“
FINTO/SKOSMOS API Search „Human“
LOV API Search „Human“
Aggregator
Search „Human“

8. distributed VS CENTRALIZED ACCESS
LOV
BioPortal API Search „Human“
AgroPortal API Search „Human“
EBI-OLS API Search „Human“
FINTO/SKOSMOS API Search „Human“
LOV API Search „Human“
Aggregator
Search „Human“
Normalized Ontology Repositories (NOR)

9. distributed VS CENTRALIZED ACCESS
LOV
Retrieve extracts from available info about all concepts in all ontologies in all repositories
Aggregator
Store extracts in database
Search index

10. distributed VS CENTRALIZED ACCESS
LOV
Retrieve extracts from available info about all concepts in all ontologies in all repositories
Aggregator
Store extracts in database
Semantic Service
"Manual" search
Cross Repository Analytics (Concept Reuse, etc.)
Search index
Ranking

11. distributed VS CENTRALIZED
Uris
Uri of the ontology class.
Labels
Human readable label of the ontology class.
Description
Definition of the ontology class.
Short_form
Short form of the ontology class.
Synonyms
List of synonym labels referenced for the ontology class.
Ontology_acronym
Acronym of the ontology the class pertains to.
Ontology_iri
IRI of the ontology the class pertains to.
Ontology_name
Name of the ontology the class pertains to.
Ontology_vdate
Date of most recent version of the ontology
Ontology_version
Version ID of most recent version of the ontology
Acrs_of_ontologies_reusing_uri
List of acronyms for the ontologies reusing the class.
Domains 
Scientific domain covered by the ontology
distributed VS CENTRALIZED
LOV
Retrieve extracts from available info about all concepts in all ontologies in all repositories
Local resource
Concept 1
Concept 2
Concept 3 .
Concept N
Aggregator
Store extracts in database
Repeated queries
Cross Repository Analytics (Concept Reuse, etc.)
Search index
Ranking

12. CHALLENGE: HETEROGENEOUS REPOSITORY APIs
Different Query/Reponse Syntaxes Example: Heterogeneous version information (also within one and the same repository)
Desired information not always available Example: Currently only Ontology level information available
Different combinations of queries necessary Example: Retrieve all ontologies, for each ontology three additional calls: version category terms

13. CHALLENGE: API CALL SEQUENCES

14. DIFFERENT APPROACHES
„Plug-in“/Wrapper style: Create individual retrieval logic for each repository Flexible but technically challenging
Find high level „description language“ for available apis Less effort for integration, but less expressive
Foster common standards for ontology/concept metadata and for repository APIs Common Metadata Description Common API Framework

15. PROOF OF CONCEPT APPROACH SpecIfiy API via JSONPath
"_comment": "From
"repo" : {
"name": "Bioportal" },
"ontologies": {
"url": "
"next": "links.nextPage",
"ontolist": "$",
"ontourl":
"ontoprefix": "acronym",
"ontoname": "name",
"ext1":{
"url": "
"token": "<ONTOID>",
"input": "ontoprefix",
"fields": {
"ontoversion": "version",
"ontovdate": "released" }
"terms„: {
"url": "
"ontotoken": "<ONTOID>",
"termlist": "collection",
"termid":
"label": "prefLabel",
"description": "definition",
"synonyms": "synonym",
"obsolete" : "obsolete"

16. Proof of concept: Aggregate BioPortal, Agroporal and ebi-ols
AgroPortal (63/64)
BioPortal (534/586)
EBI-OLS (189/193)
Total
1,198,472/1,200,845
7,569,311/8,130,580
4,893,030/4,894,758
Unique URI
1,186,681
6,659,704
4,235,425
Unq. Label
1,122,242
5,379,485
3,938,468
Instances missing in statistics
Not as easy to be harvested as classes (at least in bio-/agroportal)
Not as structured info available

17. Proof of concept: Aggregate BioPortal, Agroporal and ebi-ols
AgroPortal (63/64)
BioPortal (534/586)
EBI-OLS (189/193)
Total
1,198,472/1,200,845
7,569,311/8,130,580
4,893,030/4,894,758
Unique URI
1,186,681
6,659,704
4,235,425
Unq. Label
1,122,242
5,379,485
3,938,468
“Beta Cell Genomics Ontology”:
“bcgo” (EBI-OLS) “obi_bcgo“ (BioPortal)
“aeo”:
“Agricultural Experiments Ontology” (AgroPortal)
“Anatomical Entity Ontology” (EBI-OLS/BioPortal)

18. Proof of concept: Aggregate BioPortal, Agroporal and ebi-ols
AgroPortal (63/64)
BioPortal (534/586)
EBI-OLS (189/193)
Total
1,198,472/1,200,845
7,569,311/8,130,580
4,893,030/4,894,758
Unique URI
1,186,681
6,659,704
4,235,425
Unq. Label
1,122,242
5,379,485
3,938,468
“Beta Cell Genomics Ontology”:
“bcgo” (EBI-OLS) “obi_bcgo“ (BioPortal)
“aeo”:
“Agricultural Experiments Ontology” (AgroPortal)
“Anatomical Entity Ontology” (EBI-OLS/BioPortal)

19. Proof of concept: Aggregate BioPortal, Agroporal and ebi-ols
AgroPortal (63/64)
BioPortal (534/586)
EBI-OLS (189/193)
Total
1,198,472/1,200,845
7,569,311/8,130,580
4,893,030/4,894,758
Unique URI
1,186,681
6,659,704
4,235,425
Unq. Label
1,122,242
5,379,485
3,938,468
“Beta Cell Genomics Ontology”:
“bcgo” (EBI-OLS) “obi_bcgo“ (BioPortal)
“aeo”:
“Agricultural Experiments Ontology” (AgroPortal)
“Anatomical Entity Ontology” (EBI-OLS/BioPortal)

20. Conclusions
A centralized index of concept extracts from multiple resources in multiple repositories enables
Central access to multi-disciplinary concepts/terminology for semantic services
Identification/cross-repo search of unique and overlapping resources in different repositories
Global overview on concept-reuse  improved ranking of search results  increased re-use
Open Challenges:
Scale
Versioning
Common metadata standards
Common API framework

21. Conclusions Need for international collaboration
A centralized index of concept extracts from multiple resources in multiple repositories enables
Central access to multi-disciplinary concepts/terminology for semantic services
Identification/cross-repo search of unique and overlapping resources in different repositories
Global overview on concept-reuse  improved ranking of search results  increased re-use
Open Challenges:
Scale
Versioning
Common metadata standards
Common API framework
Need for international collaboration

22. Conclusions RDA Vocabulary and Semantic Service Interest Group
Based on effort initiated by EUDAT Semantic Web Working Group
Open community of different stakeholders (Repositories, Research communities, etc.)
Task forces on different topics:
Strategies for aggregating vocabularies
Vocabulary API White paper
Ontology metadata standard
Ontology Governance: Requesting changes
Strategies for selecting from vocabularies

23. Thank YOU Contact & Information
Doron Goldfarb
Environment Agency Austria
Yann le Franc
e-Science Data Factory
EUDAT receives funding from the European Union's Horizon 2020 programme - DG CONNECT e-Infrastructures. Contract No