Presentation given at the UK Ontology meeting 2014. See programme at: http://ced.aston.ac.uk/ukont2014/programme.html

1. Linked Experimental Data
in Life Sciences
Alejandra González-Beltrán, PhD
Oxford e-Research Centre, University of Oxford
alejandra.gonzalezbeltran@oerc.ox.ac.uk @alegonbel
UKON 2014 April 24th, 2014 Birmingham, UK

2. Data
Scientist
Visualization
Analysis
Planning
Data
Management
Data CollectionPublication
Use existing
data
Perform new
experiment
Experimental workflow

3. Data
Scientist
Visualization
Analysis
Planning
Data
Management
Data CollectionPublication
Use existing
data
Perform new
experiment
metadata
data
+
Experimental workflow

4. Data
Scientist
Visualization
Analysis
Planning
Data
Management
Data CollectionPublication
Use existing
data
Perform new
experiment
metadata
data
+
Data Interoperability
Experimental workflow

5. Data
Scientist
Visualization
Analysis
Planning
Data
Management
Data CollectionPublication
Use existing
data
Perform new
experiment
Data
Scientist
Visualization
Analysis
Planning
Data
Management
Data CollectionPublication
Use existing
data
Perform new
experiment
Data Reusability
Experimental workflow

6. Formats & Database Fragmentation Publication

7. 5
) infrastructureThe Investigation/Study/Assay (
generic format for experimental
description and data exchange
open source software toolscommunity engagement

8. 6

9. Experimental workflow - graph representation
H. Sapiens
33 Years
H1
H2
H1.sample1
H1.sample2
H2.sample1
Labeling
Labeling
H1.sample1.labeled
H2.sample1.labeled
h1-s1.cel
h1-s2.cel
h2-s1.cel
H. Sapiens
35 Years
Scanning
Scanning
Scanning
...
...
...

10. Spreadsheets for end-users
vocabulary for the description of the experimental workflow
H. Sapiens
33 Years
H1
H2
H1.sample1
H1.sample2
H2.sample1
Labeling
Labeling
H1.sample1.labeled
H2.sample1.labeled
h1-s1.cel
h1-s2.cel
h2-s1.cel
H. Sapiens
35 Years
Scanning
Scanning
Scanning
...
...
...
H. Sapiens
H. Sapiens
H. Sapiens
H1
H1
H2
35
35
33
Years
Years
Years
H1.sample1
H1.sample2
H2.sample1
Labeling
Labeling
H1.sample1.labeled
H2.sample1.labeled
h1-s1.cel
h1-s2.cel
h2-s1.cel
Scanning
Scanning
Scanning
...
Experimental workflow - graph representation

11. Spreadsheets for end-users
vocabulary for the description of the experimental workflow
syntactic interoperability
across biological experiments of different types
H. Sapiens
33 Years
H1
H2
H1.sample1
H1.sample2
H2.sample1
Labeling
Labeling
H1.sample1.labeled
H2.sample1.labeled
h1-s1.cel
h1-s2.cel
h2-s1.cel
H. Sapiens
35 Years
Scanning
Scanning
Scanning
...
...
...
H. Sapiens
H. Sapiens
H. Sapiens
H1
H1
H2
35
35
33
Years
Years
Years
H1.sample1
H1.sample2
H2.sample1
Labeling
Labeling
H1.sample1.labeled
H2.sample1.labeled
h1-s1.cel
h1-s2.cel
h2-s1.cel
Scanning
Scanning
Scanning
...
Experimental workflow - graph representation

12. Spreadsheets for end-users
vocabulary for the description of the experimental workflow
syntactic interoperability
across biological experiments of different types
H. Sapiens
33 Years
H1
H2
H1.sample1
H1.sample2
H2.sample1
Labeling
Labeling
H1.sample1.labeled
H2.sample1.labeled
h1-s1.cel
h1-s2.cel
h2-s1.cel
H. Sapiens
35 Years
Scanning
Scanning
Scanning
...
...
...
H. Sapiens
H. Sapiens
H. Sapiens
H1
H1
H2
35
35
33
Years
Years
Years
H1.sample1
H1.sample2
H2.sample1
Labeling
Labeling
H1.sample1.labeled
H2.sample1.labeled
h1-s1.cel
h1-s2.cel
h2-s1.cel
Scanning
Scanning
Scanning
...
Experimental workflow - graph representation
Support for Ontology
Annotation

13. H1
semantic interoperability
across biological experiments of different types
H1.sample1
H1.sample2
Machine-readable representation
Graph + Semantics
obi:material
entity
tax:homo
sapiens
bfo:derives
from
obi:material
sample
bfo:derives
_from
labeling1
obi:material
processing
obi:is_specified
_input _of
obi:processed
material
H1.sample1.
labeled
obi:is_specified
_output _of
h1-s1.cel
isa:raw data
file
obi:planned
process
scanning1
obi:is_specified
_input _of
obi:is_specified
_output _of
H1.sample2.
labeled
labeling2 scanning2
obi:is_specified
_input _of
obi:is_specified
_output _of obi:is_specified
_input _of
obi:is_specified
_output _of h1-s2.cel
labeling protocol
obi:protocol
isa:executes

14. more, e.g. MS Excel, OpenOffice
ISA config
files
ISA-Tab files ISA mapping
files
Graph
Analyzer
Conversion
Engine
ISA model
Ontology
Lookup
IRI
Generator
ISA Mapping
Parser
ISA graph
IRIs
ISA mappings

15. -­‐ Ontology
search
and
automated
tagging
-­‐ (relying
on
NCBO
BioPortal
services
and
also
LOV
services
in
the
2nd
version)
on
Google
Spreadsheets
-­‐
Collabora?ve
annota?on;
support
for
distributed
users
-­‐
Version
control
history
OntoMaton:(a(Bioportal(powered(
Ontology(widget(for(Google(
Spreadsheets(
Maguire(et(al,((2013(
Bioinforma?cs(

16. OntoMaton:(a(Bioportal(powered(
Ontology(widget(for(Google(
Spreadsheets(
Maguire(et(al,((2013(
Bioinforma?cs(

17. OntoMaton:(a(Bioportal(powered(
Ontology(widget(for(Google(
Spreadsheets(
Maguire(et(al,((2013(
Bioinforma?cs(

18. OntoMaton:(a(Bioportal(powered(
Ontology(widget(for(Google(
Spreadsheets(
Maguire(et(al,((2013(
Bioinforma?cs(

19. OntoMaton:(a(Bioportal(powered(
Ontology(widget(for(Google(
Spreadsheets(
Maguire(et(al,((2013(
Bioinforma?cs(

20. ISA$OBI'mapping'
Ontology for Biomedical
Investigations

21. ISA$OBI'mapping'
Ontology for Biomedical
Investigations
Also mappings to SIO, PROV-O

23. investigation studies assays
measurement technology

24. investigation studies assays
measurement technology
Underlying RDF representation

25. Bio-GraphIIn web application

26. Bio-GraphIIn web application

27. http://isa-tools.github.io/soapdenovo2/

28. !18
http://isa-tools.github.io/stato/
• General-purpose statistics ontology
• Coverage for processes (e.g. statistical tests and their condition of
application) and information needed or resulting from statistical
methods (e.g. probability distributions, variable, spread and
variation metrics)
• STATO also benefits from: (i) extensive documentation with the
provision of textual and formal definitions; (ii) an associated R
code snippets using the dedicated R-command metadata tag,
aiming at facilitating teaching and learning while relying of the
popular R language; (iii) query examples documentation,
highlighting how the ontology can be harnessed for reviewers/
tutors/student alike.
Developed in collaboration with Dr Burke, Senior Statistician,
Nuffield Department of Population Health, University of Oxford

29. !18
http://isa-tools.github.io/stato/
• General-purpose statistics ontology
• Coverage for processes (e.g. statistical tests and their condition of
application) and information needed or resulting from statistical
methods (e.g. probability distributions, variable, spread and
variation metrics)
• STATO also benefits from: (i) extensive documentation with the
provision of textual and formal definitions; (ii) an associated R
code snippets using the dedicated R-command metadata tag,
aiming at facilitating teaching and learning while relying of the
popular R language; (iii) query examples documentation,
highlighting how the ontology can be harnessed for reviewers/
tutors/student alike.
Developed in collaboration with Dr Burke, Senior Statistician,
Nuffield Department of Population Health, University of Oxford

30. Linked Experimental Data
• Importance of data interoperability for experimental data
• Fragmentation of formats and databases
• ISA-TAB for syntactic interoperability
• ISA-OWL for semantic interoperability
• Decoupling conversion engine from semantic framework
• Support for data integration, uniform semantic queries
across experiments enabled by a common semantic
framework (provided by ISA2OWL)
• Application: Bio-GraphIIn, SOAPdenovo2 use case
• STATistical Ontology for annotation of statistical analysis
results

31. funders

32. Questions?
You can email us...
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http://www.isa-tools.org
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http://github.com/ISA-tools
Thanks for your attention!