Semantic Web Services

snufflevoicelessInternet and Web Development

Oct 22, 2013 (3 years and 8 months ago)

138 views

22/10/2013

BioAID

1

e
-
science is…

Legos



“Science is built up of facts, as a house is built of
stones; but an accumulation of facts is no more a
science than a heap of stones is a house.”






Henri Poincaré,

Science and Hypothesis, 1905



http://adaptivedisclosure.org



Who will annotate the
annotators themselves?

facilitating resource management
with (semantic) web services

M. Scott Marshall

Examples on web


Example of less accessible: WSDL list for AIDA
services

http://ws.adaptivedisclosure.org/

(these
services “annotate”)



Human
-
readable service info:
http://xml.ddbj.nig.ac.jp/wsdl/index.jsp




But not machine
-
readable..

Outline



Vision


an e
-
science virtual laboratory



Some definitions



Some requirements



Essential concepts of semantic web



facets for interfaces



Conclusions

The Vision:

Scientist as knowledge worker


For Knowledge Workers:


Knowledge is the data (i.e. rules, relations, properties,
hypotheses, etc.)



For Today's Biologist:


Numbers, sequences, organisms(!), and images are the data



Manipulate knowledge instead of data


Find support for relations between concepts instead of
discovering table and column names and numbers.



In the virtual laboratory, everything is a resource that can
be described and manipulated with semantics

User


....?


End users


scientists using our applications


API users


programmers extending and using
our code


System administrators


setting up services,
grids etc.


Other classes...



If you’re not sure which one someone
means please shout and ask them!

Slide courtesy of Tom Oinn, OMII
-
EBI Workshop

Service Oriented Architecture (SOA)


A way of doing computing where services are
somehow combined to perform some overall
function



Implies a communication framework between the
services



Used because it’s easier to reconfigure the
arrangement of a set of services than to rewrite a
script


Services as LEGO bricks


Slide courtesy of Tom Oinn, OMII
-
EBI Workshop

Grid


Not just Globus, or EGEE, or Naregi...


No such thing as ‘the grid’


Unlike ‘the internet’ which does exist!



We mean :


A computational facility, normally comprising multiple
computers, which provides some combination of
compute and data storage capacity and which can
abstract over its inner workings in some fashion


Very loose definition!



Can be
part of
a Service Oriented Architecture

Slide courtesy of Tom Oinn, OMII
-
EBI Workshop

Knowledge

“data”, “information”, “facts”,
“knowledge”


Knowledge is a statement that can be
tested for truth.


(by a machine)

RDF : a web format for knowledge

RDF is a W3C language to express

statements.


RDF Triple:


Subject Predicate Object

Graph of Knowledge:


Node Edge Node


OWL : The Web Ontology Language

A W3C standard for ontology

representation based on description

logic.

Resources are shared on the web


Shared:



CPU time



network bandwidth



memory



storage space


But also:


Data


Knowledge


Services

Computational experiment:

what we want to do with the resources

Database

Computational experiment

in workflow environment

Database

Database

...

What are the tasks?


Search


discovering resources that
match our needs


Workflow composition


Data integration


Enactment/Deployment


Access control


Registry of a resource


Issues raised by computational
experimentation


How will we find relevant data?



How will we automatically integrate such data
into our experiment?



How will we find apropriate services?



How will we integrate our results as usable data
for a new (computational) experiment?



-
> annotation

22/10/2013

BioAID

17

Finding the stone…

Where is the piece
that

is red, has a triangular
top, and was previously
used to build a roof?

Computational Experiments

Anticipated needs of the data consumer


Data integration
-

combining different types of data


Data annotation: beyond formats



Not only:



Data types

(integer, string, etc.)



But also:



Data semantics
:
What do the data represent?

»
Determined by the experimental design



Provenance
:
What has been done to the data?

»
Description of the procedure(s) that produced/transformed the data



Discover and enact appropriate (web) services with appropriate
data



Reuse results from a computational experiment as data in another
computational experiment


derived

data is “
tagged
” and put into the repository

Anticipated needs of the data supplier
(and consumer)


Data in:


Simple submission/registration of data to e
-
science repository


Semi
-
automatic annotation



Data out:


Easy search and retrieval of previous datasets (my personal
and my group’s data)



Easy search and retrieval of
relevant

datasets from public
repository



Combining data:


Different types and different sources


Example: Intersecting views of data


data mapped to physical or semantic space (Examples follow..)



The Semantic Gap

User

Resources

Middleware

Application

The Model in the middle

User

Resources

Middleware

Application

My Model

Model

Model

Why
semantic

annotation?

We want annotation to be “machine
-
readable”:



Free text


arbitrary text tags generated by users won’t always
match up


Simplest problem: Finding a “named” object


Hyponyms
-

Different names exist for the same object in different contexts
and roles.


Synonyms
-

The same name is used for different objects.



Which name should I use?



Standardized vocabulary list


can only find literal matches


Example: Using data types to search for services will find too many!



Semantic tags


allow searching for
similar

items:


“Find items like this one.”


allow searching with a description:


“Find items with these properties.”


semantic description of service (SA
-
WSDL) as well as data (OWL)


What is an ontology?

Definitions:



A collection of things that are defined in terms of their properties and relations to
other things.



A specification of a conceptualization that is designed for reuse across multiple
applications and implementations (Gruber ’93, ‘95, Guarino’ ‘96, Guarino and
Giaretta ‘95)






General applications:



Searching for objects that are resources, documents, concepts, experimental data,
or collections of these things.


Knowledge capture


Example: Biological model with hypothetical knowledge


Common applications in bioinformatics:



Annotation of database entries (e.g. gene products)


Categorization of clustered elements (e.g. genes)



Inheritance in ontologies


Often represented as DAG’s (Directed Acyclic Graphs) or
hierarchies (trees)


Power of inheritance


Subsumption relations (ISA) apply transitivity to create
inheritance of class and properties downward along chains in
the hierarchy.


Use an element as a metadata tag for semantic annotation
(
ontotag
)


An
ontotag

serves as a pointer into a “
semantic space


Animal

Mammal

Bird

Robin

Heron

Penguin

Gene Ontology

Mouse
p53
:

{List of GO identifiers}

Process:

apoptosis, DNA damage
response, signal transduction
by p53 class mediator...

Component:

cytoplasm, cytosol...

Function:

DNA binding, protein binding...

Cluster of genes X from micro array analysis

Collection of {List of GO identifiers} per gene in cluster

Þ
Most prevalent GO identifiers:

Þ
Apoptosis, Cytosol, Protein Binding

Þ
Significant relationships between GO classes

(e.g. cell death and DNA damage response)

Semantic annotation
-

ontotags

Workflow provenance

Author

Evidence

Scientific Model

Data type

Data value(s)

Metadata

Evidence
Ontology

Gene
Ontology

Author

Provenance

KSinBIT’06


Resource mngmt use case: data integration

Finding a basis for relation

Epigenetic
Mechanisms

Transcription

Chromatin

Histone
Modification

Transcription
Factors

Transcription Factor
Binding Sites

position

“There is a relation”

Common Domain

Instances

Classes

Hypothesis

KSinBIT’06


Scenario: A Use Case is born


E
-
scientist explains benefits of semantic web to
(wet lab) biologist



Biologist wants to see a demonstration with
actual data



=> Use Case: Find evidence of a relation
between transcription and histone modifications



Our approach: Annotate data with our own
semantic types so that we can issue a query
using our own terms

KSinBIT’06


E
-
science perspective on data integration:

From cartoon to model to semantic data integration

Biological
concepts
(‘
my
Model’)

Data

Biologist
readable
model

Computer
readable
model

Some of the pieces we need



knowledge representation


triples




pointing at things: EPR's and URI's, not just the things
but the statements about the things




unification and reasoning




annotation: linking knowledge to resources

Provenance


example in Taverna

Computational experiment

Database

Some provenance should
be added by the
module/service itself

Database

Database

...

22/10/2013

BioAID

34

The
AIDA

toolbox

for knowledge extraction and knowledge management

reusable components to enhance science

Living examples:

dynamic interfaces


http://aida.science.uva.nl:9999/search/AID



Yahoo Pipes interface to AIDA medline search:

http://pipes.yahoo.com/pipes/pipe.info?_id=cv7nIBpw3BGw4
NOLJphxuA



MeSH facet interface from Exhibit:

http://aida.science.uva.nl:9999/search/json_test.html




W3C Health Care and Life Sciences KB (unofficial URL):
http://www.w3.org/2001/sw/hcls/notes/kb/

http://esw.w3.org/topic/HCLS/Banff2007Demo



Conclusions



The Web is a collection of resources: resource
sharing



Disclosure of semantic models can greatly enhance
resource sharing and resource management



Semantic annotation can be applied to any type of
resource: data and (web)services.



Semantic annotation and provenance can be added by the
(web)services themselves.



Need text mining for web services (to support semantic
annotation)



Need web services for text mining


The End



“Science is built up of facts, as a house is built of
stones; but an accumulation of facts is no more a
science than a heap of stones is a house.”






Henri Poincaré,

Science and Hypothesis, 1905



http://adaptivedisclosure.org