Ontology-­‐based  services  and  knowledge  management  in  the  

Agronomic  Domain  

Pierre  Larmande  Ins-tute  of  Research  for  Development  (IRD)  

Head  of  data  integra-on  group  at  the  Ins-tute  of  Computa-onal  Biology  pierre.larmande@ird.fr  

 

Outline

•  Data integration challenges in the Life Sciences

•  Ontologies/ Semantic Web Technologies

•  AgroPortal a proposition for ontology-based services in the agronomic domain

•  Agronomic Linked Data project

Data landscape in the Life Sciences

•  The availability of biological data has increased

•  Advancements in:•  computational biology•  genome sequencing•  high-throughput technologies

•  Integrative approaches are necessary to understand the functioning of biological systems

•  Lack of effective approaches to integrate data that has created a gap between data and knowledge

•  Need for an effective method to bridge gap between data and underlying meaning

•  Harvest the power of overlaying different data sets

Data integration challenges

Semantic Web Technology

•  An extension of the current Web technologies.

•  Enables navigation and meaningful use of digital resources.

•  Support aggregation and integration of information from diverse sources.

•  Based on common and standard formats.

Resource Description Framework (RDF)

•  Framework for representing information about resources on the Web

•  Provides a labeled connection between two resources

•  Uses Unique Resource Identifiers (URI)

•  Statements take the form of triples:

Subject   Predicate   Object  

<Gene_A>   <codes_for>   <Protein_A>  

RDF  Triple  

•  Combining the triples results in a directed, labeled graph.

<Gene_A>  

<Protein_A>  <has_funcFon>  

<BP_A>  

<MF_A>  

<Gene_X>  

<regulates>  

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AgroPortal    a  proposi(on  for  ontology-­‐based  services  in  the  agronomic  domain  

Clément  Jonquet,    Esther  Dzalé-­‐Yeumo,    Elizabeth  Arnaud,    Pierre  Larmande  

 

ObjecFves  of  AgroPortal  project  

•  Develop  and  support  a  reference  ontology  repository  for  the  agronomic  domain  –  One-­‐stop-­‐shop  for  plant/agronomic  related  ontologies    –  Primary  focus  on  the  agronomic  &  plant  domain  

•  Reusing  the  NCBO  BioPortal  technology  –  Avoid  to  re-­‐implement  what  has  been  done  –  Facilitate  interoperability  –  Reusing  the  scien-fic  outcomes,  experience  &  methods  

of  the  biomedical  domain    

•  Enable  straighUorward  use  of  agronomic  related  ontologies  –  Respect  the  requirements  of  the  agronomic  community    –  Fully  seman-c  web  compliant  infrastructure  

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HOW  DOES  IT  LOOKS?  

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Available  ontologies  

•  Already  29  ontologies…  and  we  expect  around  40  soon.  –  (half  are  not  included  in  the  NCBO  BioPortal)  

•  Ontologies  are  organized  in  Groups  and  Categories  

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Recommender  

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Mappings  

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Community  based  func-onali-es  

Atelier  InOvive  2015  –  Rennes  –  29  juin  2015   18  

REST  Web  Service  API:  hhp://data.agroportal.lirmm.fr/documenta-on    

Atelier  InOvive  2015  –  Rennes  –  29  juin  2015   19  

SPARQL  endpoint:  hhp://sparql.agroportal.lirmm.fr    

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AN  ONTOLOGY  REPOSITORY…  WHO’S  GONNA  USE  IT?  

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4  Driving  Agronomic  Use  Cases  •  IBC  Rice  Genomics  

–  data  integra-on  and  knowledge  management  related  to  rice  

 •  RDA  Wheat  Data  Interoperability  working  group  

–  common  framework  for  describing,  represen-ng,  linking  and  publishing  wheat  data  with  respect  to  open  standards  

•  INRA  Linked  Open  Vocabularies,  LovInra  –  publish  vocabularies  produced  or  co-­‐produced  by  

INRA  scien-sts  and  foster  their  reuse  beyond  the  original  researchers  

•  The  Crop  Ontology  project  –  publishes  ontologies  required  for  describing  crop  

germplasm,  traits  and  evalua-on  trials.  

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Each  use  case  has  a  specific  group  in  AgroPortal  

•  Feature  to  come:  slices  – Specific  “entry”  in  the  AgroPortal  

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AgroLD    The  Agronomic Linked

Data project

Aravind  Venkatensan,  Gildas  Tagny,  

Nordine  El  Hassouni,  Manuel  Ruiz,  

 Pierre  Larmande    

Agronomic Linked Data (AgroLD)

•  Semantic web based system that integrates data from South Green Bioinformatics node

•  Aim:

•  Capability to answer complex real life questions

•  Efficient information integration / retrieval.

•  Easy extensibility.

•  Aid in holistic understanding of domain

AgroLD

•  AgroLD will be developed in phases –

•  Website: www.agrold.org

•  Phase I: includes data on:•  Rice (Oryza spp).

•  Oryza barthi•  Oryza brachyantha•  Oryza Sativa•  Oryza glaberimma

•  Arabidopsis thaliana•  Sorghum (Sorghum bicolor)•  Maize/Corn (Zea mays)•  Wheat

•  Triticum astivum•  Triticum urartu

Data  sources  in  AgroLD  

Ontologies  in  AgroLD  

Knowledge in AgroLD AgroLD  

Ontologies  

www.agrold.org

Search  and  browse  AgroLD  

Plant  height  

Sparql  query  editor  

Sparql  query  editor  

Results  are  annotated  with  evidence_code    

hhp://geneontology.org/page/guide-­‐go-­‐evidence-­‐codes  

VisualisaFon  of  queries  

Advanced  form-­‐based  search  

Results  are  combined  with  external  services    

Please  send  us  your  Feedback!  

Your  answers  will  help  us  to  improve  the  applicaton  

Acknowledgements  

Elizabeth  Arnaud,    Leo  Vale\e,    Marie-­‐Angelique  Laporte,    Julian  Pietragalla  

Manuel  Ruiz,  

Nordine  El  Hassouni  

Aravind  Venkatesan,  Gildas  Tagny  

Esther  Dzalé-­‐Yeumo,  Cyril  Pommier  

Patrick  Valduriez  

Clement  Jonquet  

Pierre  Larmande  

Contact:  pierre.larmande@ird.fr