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