Life Sciences Linked Open Data Query Federation Query Engine Data Cataloguing Data Linking a posteriori integration

1. Improving discovery in Life Sciences
Linked Open Data Cloud
Ali Hasnain

2. We want to query the content, not the source
Proteins
Molecules
Genes
Diseases

3. A Linked Life Sciences Roadmap
Proteins
Molecules
Genes
Diseases
:Protein
:Molecule
:Gene
:Disease
Uniprot
PDB
Pfam PROSITE
ProDom
Uniref
UniPark Daily
medDrug
Bank ChemBL
Pub
Chem KEGG
Gene
Ontology
GeneID
Affy
metrix
Homo
gene
MGI
Disea
some
SIDER

4. 2- Possible Solutions
To assemble queries over multiple graphs at multiple endpoints,
either
vocabularies and ontologies are reused, Or
translation maps between different terminologies are created (“a posteriori
integration”)

5. a-priori v.s a-posteriori Integration

6. Hypothesis
"Given a heterogeneous Life Sciences Linked Open Data
corpus, an active Compendium containing concepts from
distinct endpoints and properties connecting these
concepts, that can be (partially) leveraged to achieve "a
posteriori" integration"

7. Methodology
Cataloguing and Linking Life Sciences
LOD Cloud.
Ali Hasnain, Ronan Fox, Stefan Decker
and Helena F. Deus
18th International Conference on
Knowledge Engineering and Knowledge
Management (EKAW 8 - 12 October
2012), Galway, Ireland

8. Describing DataSets- an Extract from Catalogue

9. BioFed- Query Engine

10. BioFed: Federated Query Processing over Life
Sciences Linked Open Data
BioFed: Federated Query Processing
over Life Sciences Linked Open Data
Ali Hasnain, Qaiser Mehmood, Syeda
Sana e Zainab, Muhammad Saleem,
Claude Warren and Stefan Decker
JBMS-2015 (under review)

11. FedViz System Architecture
15
FedViz is an online application that
provides Biologist a flexible visual
interface to formulate and execute both
federated and non-federated,
SPARQL queries.
It translates the visually assembled
queries into SPARQL equivalent and
execute using query engine (FedX,
BioFed).

12. Linked Biomedical DataSpace

13. Catalogue Results

14. Linking Results

15. BioFed Evaluation- Dataset Used

16. Evaluating BioFed – simple queries

17. Evaluating BioFed – complex queries

18. Conclusion and Future Work
• Cataloguing and Linking – Compendium of Life sciences
Datasets
• BioFed and FedViz a Particle Applications
• Improving Catalogue/ Adding Statistical/ Latency etc
information for customised and targeted query processing.
• Evaluating BioFed with other available Query Engines
including Anapsid, Splendid etc.