And now, for something completely different…. Web 2.0 + Web 3.0 = Web 5.0? The HSFBCY + CIHR +...
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Transcript of And now, for something completely different…. Web 2.0 + Web 3.0 = Web 5.0? The HSFBCY + CIHR +...
And now, for somethingcompletely different…
Web 2.0 + Web 3.0 = Web 5.0?
The HSFBCY + CIHR + Microsoft Research SADI and CardioSHARE Projects
Mark Wilkinson & Bruce McManusHeart + Lung Institute
iCAPTURE Centre, St. Paul’s Hospital, UBC
Who am i?
Mark Wilkinson
Carole Goble
“Shopping for …data should be as
easy as shopping for shoes!!”
Carole Goble
Carole’s Shoes
My shoes
It is hard to fill Carole’s shoes!
Who am i?
Geneticist &Molecular Biologist
Informatician
Software
Middleware
Robert Stevens
Shouldn’t be
seen!
Then why am I presenting to you?
enablesuseful
and excitingbehaviours
Cool!
For cardiovascularresearchers
Please indulge meas I expose
my underwear
…BRIEFly ;-)
(sorry, I couldn’t resist)
The Problem
The Problem
The Holy Grail:(circa 2002)
Align the promoters of all serine threonine kinases involved exclusively in the regulation of cell sorting during wound healing in blood vessels.
Retrieve and align 2000nt 5' from every serine/threonine kinase in Mus musculus expressed exclusively in the tunica [I | M |A] whose expression increases 5X or more within 5 hours of wounding but is not activated during the normal development of blood vessels, and is <40% homologous in the active site to kinases known to be involved in cell-cycle regulation in any other species.
The Problem
The Problem
The Solution??
Not really…
Why not?
Heart
Heart
Occam’s Razor
“Pluralitas non est ponenda sine neccesitate.”
“Plurality should not be posited without necessity."
“Biology is hard!”
So… what can we do?
What we need
Our “information systems” areDATA-centric
Our “information systems” are NOTKNOWLEDGE-centric
(Source: Clarke and Rollo, Education and Training, 2001)
The REAL Solution
KnowledgeMachine-readableKnowledge
How do we make knowledge machine-readable?
Ontology
Ontology (Gr: “things which exist” +-logy)An explicit formal specification of how to represent the objects, concepts and other entities that are assumed to exist in some area of interest and the relationships that
hold among them.
Problem…
Ontology Spectrum
Catalog/ID
SelectedLogical
Constraints(disjointness,
inverse, …)
Terms/glossary
Thesauri“narrowerterm”relation
Formalis-a
Frames(Properties)
Informalis-a
Formalinstance
Value Restrs.
GeneralLogical
constraints
Originally from AAAI 1999- Ontologies Panel by Gruninger, Lehmann, McGuinness, Uschold, Welty; – updated by McGuinness.Description in: www.ksl.stanford.edu/people/dlm/papers/ontologies-come-of-age-abstract.html
WHY?
Because I say so!
Because it fulfils XXX
My Definition of Ontology (for this talk)
Ontologies explicitly define the things that exist in “the world”
based on what properties each kind of thing must have
Ontology Spectrum
Catalog/ID
SelectedLogical
Constraints(disjointness,
inverse, …)
Terms/glossary
Thesauri“narrowerterm”relation
Formalis-a
Frames(Properties)
Informalis-a
Formalinstance
Value Restrs.
GeneralLogical
constraints
My goal with this talk
Clay Shirky
“Ontology is Over-rated”
http://www.shirky.com/writings/ontology_overrated.html
COST
Catalog/ID
SelectedLogical
Constraints(disjointness,
inverse, …)
Terms/glossary
Thesauri“narrowerterm”relation
Formalis-a
Frames(Properties)
Informalis-a
Formalinstance
Value Restrs.
GeneralLogical
constraints
COMPREHENSIBILITY
Catalog/ID
SelectedLogical
Constraints(disjointness,
inverse, …)
Terms/glossary
Thesauri“narrowerterm”relation
Formalis-a
Frames(Properties)
Informalis-a
Formalinstance
Value Restrs.
GeneralLogical
constraints
Likelihood of being “right”
Catalog/ID
SelectedLogical
Constraints(disjointness,
inverse, …)
Terms/glossary
Thesauri“narrowerterm”relation
Formalis-a
Frames(Properties)
Informalis-a
Formalinstance
Value Restrs.
GeneralLogical
constraints
Here’s my argument…
Semantic Web?
An information system where machines can receive information from one source, re-interpret it, and correctly use it for a purpose that the source had
not anticipated.
Semantic Web?
If we cannot achieve those two things, then IMO we don’t have a “semantic web”, we only have a distributed (??), linked database… and that isn’t
particularly exciting…
Where is the semantic web?
Catalog/ID
SelectedLogical
Constraints(disjointness,
inverse, …)
Terms/glossary
Thesauri“narrowerterm”relation
Formalis-a
Frames(Properties)
Informalis-a
Formalinstance
Value Restrs.
GeneralLogical
constraints
REASON: “Because I say so” is not open to re-interpretation
The games we have been playing for ~2 years
Find. Integrate. Analyse.
Founding partner
SADI
Data + Knowledge for Cardiologists.
Founding partner
CardioSHARE
Brief History of
CardioSHARE
Automating the interaction between biologists andtheir preferred data and analytical resources
(Running since 2002)
Moby defines an ontology of datatypes, and a WS registry that is
aware of that ontology
I’m studying a mutation in my favorite organism
I want to know what mutations in the equivalent gene look like in
another organism
Oh no…
The Moby Semantic Web Service Approach
WORKFLOW
Analytical Workflow constructionUsing Moby
No explicit coordination between providers
Automated discovery of appropriate tools
Automated execution of selected tools
The machine “understands” the data-type you have in-hand, and assists you in choosing the next step
in your analysis.
This got me thinking…
Datatypes…
Biology?!?!?
CardioSHARE
The Cardiovascular Semantic Health And Research Environment
Theatre Analogy
The Components of a Play
The Script
The Stage
The Casting Director & directors
The Actors
The Components of CardioSHARE
Cardiovascular Ontologies (The Scripts)
SHARE (The Stage & Set Decorator)
SADI (The Casting Director)
Data (The Actors)
DATA
the “actors” in CardioSHARE
ACTORS:
No intelligence
No Use or Function(…without a script)
more successfulwhen clean!!
No Intelligence?No Use?
Data exhibits “Late binding”
Late binding:
“purpose and meaning” of the data is
not determined untilthe moment it is required
benefit/Consequenceof Late binding:
data is amenable toconstant re-interpretation
How do we achieve this?
Because weDO NOT CLASSIFY
our data…we simply hang properties on it
Catalog/ID
SelectedLogical
Constraints(disjointness,
inverse, …)
Terms/glossary
Thesauri“narrowerterm”relation
Formalis-a
Frames(Properties)
Informalis-a
Formalinstance
Value Restrs.
GeneralLogical
constraints
These are classification systems
These are axioms that enable interpretation
The Components of CardioSHARE
Cardiovascular Ontologies (The Scripts)
SHARE (The Stage & Set Decorator)
SADI (The Casting Director)
Data (The Actors)
SADI
“Semantic AutomatedDiscovery and Integration”
SADI =…but smarter…
SADI
Instead of specifyingthe analysis or database
you specify theBiological/clinicalRELATIONSHIP
of interest
“Take this gene sequence, run the BLAST algorithm to
search for genes with similar sequence, and give me the result”
SADI“get me the homologues for this gene”
SADI knows that the BLAST algorithm is used to search for homologous
gene sequences
SADI finds a BLAST server on the Web and executes your search for you
SADI
By analogy:
SADI, the casting director, knows which actors are best able to fit the part,
automatically finds them, and casts them in the play
SADI Web ServicesWS Discovery is aided by reasoning
WS interfaces are defined in OWL as two classes: Input and Output
Input and Output classes include the property restriction axioms that define
the input to/output from the service
“mini ontology”
SADI Web Services
The WS consumes input data (native RDF) and adds a new property (predicate+object) to it.
The Components of CardioSHARE
Cardiovascular Ontologies (The Scripts)
SHARE (The Stage & Set Decorator)
SADI (The Casting Director)
Data (The Actors)
SHARE
SHARE is a completely generic “stage”upon which a “play” is going to be
performed
It’s the place where the actors are assembled to do their thing for an
audience
SHARE
Simply a place where you can askANY question (i.e. the Play)
and see the result
SHARE
At the moment it isn’tparticularly impressive…
By analogy, we have a stage, but we haven’t hired any set decorators yet!
You’ll see what I mean in a minute…
DEMO
Recapwhat we just saw
A SPARQL database query was entered into the SHARE environment
The query was passed to SADI and was interpreted based on the properties being asked-about
SADI searched-for, found, and accessed the databases and/or analytical tools required to generate those
properties
“The play was performed”
Recapwhat we just saw
We asked, and answered a complex “database query”
WITHOUT A DATABASE!!
The Holy Grail:
Align the promoters of all serine threonine kinases involved exclusively in the regulation of cell sorting during wound healing in blood vessels.
Retrieve and align 2000nt 5' from every serine/threonine kinase in Mus musculus expressed exclusively in the tunica [I | M |A] whose expression increases 5X or more within 5 hours of wounding but is not activated during the normal development of blood vessels, and is <40% homologous in the active site to kinases known to be involved in cell-cycle regulation in any other species.
The Components of CardioSHARE
Cardiovascular Ontologies (The Scripts)
SHARE (The Stage & Set Decorator)
SADI (The Casting Director)
Data (The Actors)
CardiovascularOntologies:
Allow us to refer to complex clinical/molecular phenomenon inside of our query
(i.e. Biological Knowledge!)
Allows experts to define these concepts, and then have their expert-knowledge re-used by
non-experts in their own queries.
HUH?
WORKFLOW
QUERY:
Retrieve images of mutations from genes in organism XXX that share homology to this gene in
organism YYY
Concept:
“Homologous Mutant Image”
Phrased in terms of properties:
Find image P where {
Gene Q hasImage image P
Gene Q hasSequence Sequence Q
Gene R hasSequence Sequence R
Sequence Q similarTo Sequence R
Gene R = “my gene of interest” }
…but these are simply axioms…
HomologousMutantImage is {
Gene Q hasImage image P
Gene Q hasSequence Sequence Q
Gene R hasSequence Sequence R
Sequence Q similarTo Sequence R
Gene R = “my gene of interest” }
QUERY:
Retrieve homologous
mutant images for gene XXX
CardioSHARE
We construct small, independent OWL classes representing these kinds of concepts
These classes simplify the construction of complex queries by “encapsulating” data discovery, retrieval,
and analysis pipelines into simple, easy-to-understand words and phrases.
CardioSHARE
These Classes are shared on the Web such that third-parties, potentially with different
expertise, can utilize the expertise of the person who designed the Class.
Easily share your expertise with others!
Easily utilize the expertise of others!
CardioSHARE
We are not building massive ontologies!
Publish small, independent Class definitions
Cheap
Scalable
Flexible
Don’t try to describe all of biology!
Importantly!
CardioSHARE/SADI releases Semantic Systemsfrom the constraints of pure logical reasoning
If the defining property restriction of your class maps to e.g. a statistical or other analytical
service, then classification into that class can be achieved through non-logical means
Biology is hard!(Too hard to define purely logically)
DEMO #2
The Holy Grail:
Align the promoters of all serine threonine kinases involved exclusively in the regulation of cell sorting during wound healing in blood vessels.
Retrieve and align 2000nt 5' from every serine/threonine kinase in Mus musculus expressed exclusively in the tunica [I | M |A] whose expression increases 5X or more within 5 hours of wounding but is not activated during the normal development of blood vessels, and is <40% homologous in the active site to kinases known to be involved in cell-cycle regulation in any other species.
CardioSHARE architecture: Increasingly complex ontological layers organize data into richer concepts, even hypotheses
Blood Pressure
Hypertension
Ischemia
Hypothesis
Database 1 Database 2 AnalysisAlgorithmXX
SADIWeb
“agents”
Recap
SADI interprets queries (SPARQL + OWL Class Definitions)
Determine which properties are available, and which need to be discovered/generated
Discovery of services via on-the-fly “classification” of local data with small OWL
Classes representing service interfaces
Recap
CardioSHARE encapsulates individual data retrieval and analysis workflows into
OWL Classes
An ontology of 1 class
Low-cost, high accuracy
Semantic Web
An information system where machines can receive information from one source, re-interpret it, and correctly use it for a purpose that the source had
not anticipated.
What we achieve
Re-interpretation :
The SADI data-store simply collects properties, and matches them up with OWL Classes in a SPARWL query and/or
from individual service provider’s WS interface
What we achieve
Novel re-use:
Because we don’t pre-classify, there is no way for the provider to dictate how their
data should be used. They simply add their properties into the “cloud” and
those properties are used in whatever way is appropriate for me.
What we achieve
Data remains distributed – no warehouse!
Data is not “exposed” as a SPARQL endpoint greater provider-control over
computational resources
Yet data appears to be a SPARQL endpoint… no modification of SPARQL or
reasoner required.
RecapCardioSHARE allows researchers to:
- Ask questions in natural, intuitive ways
- Execute complex analyses without a bioinformatician
- Access output from databases and analytical tools in exactly the same way
- Share hypotheses and models in an EXPLICIT manner
- Evaluate other’s hypotheses over your own data
Join us!
SHARE and SADI are Open-Source projectsundertaken with the collaboration of,
and for the benefit of, the biological and bioinformatics research community.
YOUR participation is welcome as we move from prototype
to “the real world”!
Fin