Neurodevelopmental disorders according to the dsm 5 tr
Capturing the context: one small(ish step for modellers, one giant leap for mankind.
1. One small(ish) step for modellers, one
giant leap for mankind
Capturing the context
Mihai Glonț
Reproducible and Citable Data and Models
Warnemuende
September 2015
2. A simple(?) question
How easy is it to find reusable models?
Reusable should entail, at least
– Reproducible
– Friendly licence
– Understandable
4. Problems
How do we recognise concepts? Is
adenosine5PrimePhospate a better variable name than a?
Do all modellers know the same amount information about
ATP?
How can we uniquely identify the concepts involved in a
modelling exercise?
5. A brief (and biased) history of the Web
Web 1.0 - basic HTML pages (personal web sites on Geosites)
6. Web 2.0
●
Prevalence of content generators
●
Social media
●
Rich user interfaces
●
Folksonomies
●
Software as a service
7. Web 3.0
●
Semantic Web
●
“The Semantic Web provides a common framework that
allows data to be shared and reused across application,
enterprise, and community boundaries" (W3C)
●
Machines understand the data on the web and can reason
about it
●
Implicit knowledge is captured in a machine-processable
manner
●
What holiday options are there for a family of four for 10
days, somewhere sunny and close to the sea, with good
food and a budget of EUR 3000?
8. Semantic web overview
●
Taxonomies and ontologies define
concepts (resources) and
ontologies
●
Identification through URIs
●
Data is exchanged as RDF
11. RDF Primer
●
Resource Description Framework
●
Documents consist of a series of statements
●
Statements (triples) follow the following syntax
●
Subject - Predicate – Object
https://sems.uni-rostock.de/reproducible-and-citable-data-and-models/
http://example.com/someOntology/hasLocation
https://en.wikipedia.org/wiki/Warnemunde
12. A selection of ontologies for life scientists
●
ChEBI: http://www.ebi.ac.uk/chebi/
●
GO: http://geneontology.org/
●
BRENDA Tissue Ontology: http://www.brenda-enzymes.org/
●
FMA: http://bioportal.bioontology.org/ontologies/FMA
●
Human disease ontology: http://disease-ontology.org/
●
TEDDY: http://purl.bioontology.org/ontology/TEDDY/
●
KiSAO: http://co.mbine.org/standards/kisao
●
SBO: http://www.ebi.ac.uk/sbo/
https://www.ebi.ac.uk/ontology-lookup/
13. Identifiers, identifiers, identifiers
●
Is http://purl.uniprot.org/taxonomy/9606
the same as
http://www.ncbi.nlm.nih.gov/Taxonomy/Browser/w
wwtax.cgi?mode=Info&id=9606
or
http://taxonomy.bio2rdf.org/describe/?url=http://
bio2rdf.org/taxonomy:9606
●
What if the URIs change?
●
What if the URIs don't point to anything?
14. Introducing identifiers.org
●
The aim of the identifiers.org project is to provide unique,
stable, resolvable and location-independent URIs to identify
and to locate scientific data
●
Community-driven
●
Free to use
16. Creating unique URIs
• Homo sapiens in Taxonomy
(9606)
http://identifiers.org/taxonomy/9606http://identifiers.org/taxonomy/9606
[Data
collection]
[Entity
identifier]
17. Creating resolvable URIs
http://identifiers.org/taxonomy/
9606
http://identifiers.org/taxonomy/
9606
• URI to identify the entity 'Homo sapiens' in the
data collection Taxonomy
http://www.ncbi.nlm.nih.go
v/Taxonomy/Browser/wwwtax.
cgi?mode=Info&id=9606
http://www.uniprot.org/taxon
omy/9606
http://www.ebi.ac.uk/ena/dat
a/view/Taxon:9606
ResourceResource ResourceResource ReferenceReference
Primary
http://info.identifiers.org/taxonomy/
9606
http://info.identifiers.org/taxonomy/
9606
18. Inter-conversion of identifier
schemes
• Registry records different identifier schemes
• Web service for inter-conversion between
identifier schemes
http://purl.obolibrary.org/obo/GO_000588
6
http://purl.obolibrary.org/obo/GO_000588
6
http://bio2rdf.org/go:0005886http://bio2rdf.org/go:0005886
http://identifiers.org/go/GO:000588
6
http://identifiers.org/go/GO:000588
6
19. Support for different formats
TaxonomyTaxonomy
htmlhtml
htmlhtml
RDFRDF
jsonjson
• The Registry records the formats provided by the
various data resources
26. Quo vadis?
●
Model curation is hard
●
Model annotation is laborious
●
We moved from lack of methods to scalability and usability
issues
●
Towards semi-automated annotation based on model
clustering
●
User-friendly tools for annotating models