Semantic grid From Concepts to Implementation

1
Semantic gridFrom Concepts to Implementation

• Nguyen Thanh Vu
• Hoang Song Cam Thach
• Cu Nguyen Phuong Ha

2
Outline

• Introduction
• Semantic Web
• S-OGSA
• Implementation ( e-Science myGrid )

3
What is the Semantic Gird?

• An extension of the current Grid in which
  information and services are given well-defined
  and explicitly represented meaning, so that it
  can be shared and used by humans and machines,
  better enabling them to work in cooperation.

4
Why we need the Semantic Grid?

• It is a truth universally acknowledged, that
  an application in possession of good middleware,
  must be in want of meaningful metadata.
• --
  prof. C. Goble

5
Why we need the Semantic Grid?

• Example To illustrate, consider if a machines
  operating system is described as SunOS or
  Linux. To query for a machine that is Unix
  compatible, a user either has to
• 1. Explicitly incorporate the Unix
  compatibility concept into the request
  requirements by requesting a disjunction of all
  Unix-variant operating systems, e.g.,
  (OpSysSunOS OpSysLinux), or
• 2. Wait for all interesting resources to
  advertise their operating system as Unix as well
  as either Linux or SunOS, e.g., (OpSysSunOS,
  Unix), and then express a match as
  set-membership of the desired Unix value in the
  OpSys value set, e.g., hasMember(OpSys, Unix).

6
Why we need the Semantic Grid?

• Example (cont)
• Apply Semantics
• - Knowledge base SunOS and Linux are types
  of Unix operating system
• - Request Need the Unix compatibility OS

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Semantic Web

• Current Web ( WWW )
• - Is a huge library of interlinked documents
  that are transferred by computers and presented
  to people.
• - Anyone can contribute to it.
• - Quality of information or even the
  persistence of documents cannot be generally
  guaranteed.
• - Contains a lot of information and
  knowledge, but machines usually serve only to
  deliver and present the content of documents
  describing the knowledge.
• - People have to connect all the sources of
  relevant information and interpret them
  themselves.

Machine can Process the
content
But Machine cant Understand
content
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Semantic Web

• Definition
• The Semantic Web is an extension of the
  current web in which the semantics of information
  and services on the web is defined, making it
  possible for the web to understand and satisfy
  the requests of people and machines to use the
  web content.
• 
  --- Tim Berners-Lee

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Semantic Web

• Definition ( cont )
• Semantic web is an effort to enhance current
  web so that computers can process the information
  presented on WWW, interpret and connect it, to
  help humans to find required knowledge

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Semantic Web

• Semantic Web is a project that should provide a
  common framework that allows data to be shared
  and reused across application, enterprise, and
  community boundaries.
• Is led by World Wide Web Consortium (W3C).

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Semantic Web Architecture (1)

• URI (Uniform Resource Identifier) is a string of
  a standardized form that allows to uniquely
  identify resources.
• Unicode is a standard of encoding international
  character sets and it allows that all human
  languages can be used (written and read) on the
  web using one standardized form.

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Semantic Web Architecture (2)

• XML ( Extensible Markup Language) layer makes
  sure that there is a common syntax used in the
  semantic web.

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Semantic Web Architecture (3)

• RDF stands for Resource Description Framework.
• RDF is a graphical formalism ( XML syntax
  semantics)
• for representing metadata
• for describing the semantics of information in a
  machine- accessible way
• Provides a simple data model based on triples
  subject-predicate-object

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RDF Data model

• Statements are ltsubject, predicate, objectgt
  triples
• ltJoe, hasFamilyName,Smith gt
• Can be represented as a graph.
• Statements describe properties of resources
• A resource is any object that can be pointed to
  by a URI
• Properties themselves are also resources (URIs)

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RDF Syntax

• RDF has an XML syntax that has a specific
  meaning
• - Every Description element describes a
  resource
• - Every attribute or nested element inside
  a Description is a property of that Resource
• - We can refer to resources by URIs

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RDF Example
English Statement http//www.example.org/index.ht
ml has a creation-date whose value is August 16,
1999 Triple representation exindex.html
extermscreation-date "August 16,
1999" RDF Graph representation
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RDF Example (cont)
RDF/XML syntax
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Semantic Web Architecture (4)

• RDFS (RDF Schema) is extending RDF vocabulary to
  allow describing taxonomies of classes and
  properties.

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RDFS ( cont)

• RDF does not give any special meaning to
  vocabulary such as subClassOf or type (supporting
  OO-style modelling).
• RDF Schema extends RDF with a schema vocabulary
  that allows you to define basic vocabulary terms
  and the relations between those terms
• Class, type, subClassOf,
• Property, subPropertyOf, range, domain
• it gives extra meaning to particular RDF
  predicates and resources
• this extra meaning, or semantics, specifies how
  a term should be interpreted.

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Semantic Web Architecture (5)

• OWL stands for Web Ontology Language.
• OWL is a language derived from description
  logics.
• OWL provides additional standardized vocabulary.
• OWL provide reasoning support

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Semantic Web Architecture (6)

• RIF/SWRL rule languages are being standardized
  for the semantic web.
• Provide rules beyond the constructs available
  from RDFS OWL.

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Semantic Web Architecture (7)

• SPARQL stands for Simple Protocol And RDF Query
  Language.
• SPARQL is used to query RDF data as well as RDFS
  and OWL ontologies with knowledge bases.

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S-OGSA

• Why
• What
• How
• Design Principles
• S-OGSA
• Conclusions and future works
• Reference
• QA

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Why Semantic Grid ?

• Currently, Grid metadata is generated and used in
  an ad hoc fashion , represented in different
  formats.
• Its hard to share
• Its hard to reuse
• Its hard to reinterpret
• Semantic Grid is an extension of the Grid
  increases interoperability and greater
  flexibility

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What is Semantic Grid

• An extension of the Grid
• Rich metadata is exposed and handled explicitly,
  shared, and managed via Grid protocols

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What is Semantic Grid

• The Semantic Grid uses metadata to describe
  information in the Grid.
• Turning information into something more than just
  a collection of data means understanding the
  context, format, and significance of the data.
• Therefore
• Understand information
• Discovery and reuse

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Semantic?

• Semantic metadata meaning
• Metadata explicitly exposed as a first class
  object in a machine processable form.
• Controlled vocabularies or knowledge models (aka
  Ontologies) for describing metadata in a machine
  processable form.
• Schemas for structuring metadata in a machine
  processable form.
• Rules over metadata.
• Possibly using Semantic Web technologies
• For people and machines

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Design Principles for a Reference Semantic Grid
Architecture

• Parsimony
• lightweight
• minimize the impact on legacy Grid infrastructure
  and tooling.
• Extensibility
• Uniformity (of the mechanisms)
• manageability of S-OGSA entities
• Have both stateless and stateful Grid services
  like OGSA
• S-OGSA services are OGSA-observant Grid services.
  

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Design Principles for a Reference Semantic Grid
Architecture

• Diversity
• Mixed ecosystem of Grid and Semantic Grid
  services
• Services ignorant of semantics
• Services aware of semantics but unable to process
  them
• Services aware of semantics and able to process
  (part of) them

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Design Principles for a Reference Semantic Grid
Architecture

• Heterogeneity (of semantic representation)
• Any resources property may have many different
  semantic descriptions
• captured (or not) in different representational
  forms (text, logic, ontology, rule).

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Design Principles for a Reference Semantic Grid
Architecture

• Enlightenment
• minimal impact on adding explicit semantics to
  current Grid entities
• Grid entities should not break if consume and
  process Grid resources but cannot consume and
  process associated semantics
• Grid entities can incrementally acquire, lose and
  reacquire explicit semantics during their
  lifetime

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S-OGSA

• Defined by
• Information model
• New entities
• Capabilites
• New functionalities
• Mechanisms
• How it is delivered

Model
provide/ consume
expose
Capabilities
Mechanisms
use
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S-OGSA

• How to provide
• Just give the semantic metadata to those services
• Or we can have the semantic services by SOGSA
  own.

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S-OGSA

• There are no big differences
• if the service can understand semantic (e.g.,
  they support semantic API), then itself can be a
  S-OGSA service.

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S-OGSA

• A Grid usually consist of several different
  services by OGSA
• VO management service
• Resource discovery and Management service
• Job Management service
• Security service
• Data Management service
• The S-OGSA should (will) provide the metadata
  semantic services to those services.

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S-OGSA

• The Solution
• Attached the semantic to Grid entities.
• Binding them together by semantic binding
  service.
• Normal grid services can be semantic by the
  semantic binding service.

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S-OGSA Model. Semantic Bindings
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S-OGSA
Application 1
Application N
Optimization
Security
Data
OGSA
Execution Management
Semantic-OGSA
Semantic Provisioning Services
Resource management
Information Management
Infrastructure Services
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S-OGSA
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S-OGSA Model and Capabilities
WebMDS
Annotation Service
Metadata Service
Ontology Service
OGSA-DAI
Grid Service
Semantic BindingProvisioning Service
Is-a
Knowledge Service
Reasoning Service
Is-a
CAS
Is-a
Is-a
Is-a
Semantic ProvisioningService
Knowledge Entity
Grid Entity
1..m
1..m
SAMLfile
uses
Is-a
Ontology
Is-a
Semantic aware Grid Service
Knowledge Resource
Grid Resource
DFDL file
Rule set
1..m
1..m
consume
produce
JSDL file
0..m
0..m
Semantic Binding
0..m
0..m
Is-a
Knowledge
Semantic Grid
Grid
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S-OGSA Model and Capabilities

• Grid Entities
• Resources and services
• Knowledge Entities
• Grid Entities that represent or could operate
  with some form of knowledge (e.g ontologies,
  rules, knowledge bases )
• Semantic Bindings
• entities associatie of a Grid Entity with one or
  more Knowledge Entities

42
S-OGSA Model and Capabilities

• Semantic Grid Entities (all entitites in the
  binding model)
• Semantic Provisioning Services
• provisioning and management of explicit semantics
  and its association with Grid entities
• creation, storage, update, removal and access of
  different forms of knowledge and metadata
• Knowledge provisioning services
• ontology services , reasoning services .
• Semantic binding provisioning services
• metadata services, annotation services .

43
S-OGSA Model and Capabilities

• Semantically Aware Grid Services
• Be able to consume Semantics Bindings and being
  able to take actions based on knowledge and
  metadata .
• Sample Actions
• Metadata aware authorization of a given identity
  by a VO Manager service .
• Execution of a search request over entries in a
  semantic resource catalogue .
• Incorporation of a new concept in to an ontology
  hosted by an ontology service .
• Reduction of an annotated scientific data set to
  a smaller subset by a scientist.

44
S-OGSA Mechanisms

• Treating Knowledge Entities and Semantic Bindings
  as Grid Resources
• Common Information Model (CIM) Resource Model
• Grid Entities class CIM-ManagedElement in the
  CIM Model.
• Knowledge Entities class S-OGSA-KnowledgeEntity
  
• S-OGSA-SemanticBindingSemantic Binding, the
  association between a Grid Entity
  (CIM-ManagedElement) and a Knowledge Entity
  (S-OGSA-KnowledgeEntity).

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S-OGSA Mechanisms
46
S-OGSA Mechanisms

• S-Stateful Services mechanisms for the delivery
  of Semantic Bindings for resources
• Based on Web Services Resource Framework (WSRF)

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Retrieving and Querying Semantic Bindings of
Resources
Query/Retrieval Result
Metadata Service
Ontology Service
Metadata Retrieval/Query Request
Obtain schema for Semantic Bindings
Semantic Binding Ids Retrieval Request
Metadata Seeking Client
Resource Specific
Lifetime
State/properties/metadata access port
Resource

• A Feta ODE-SGS, OWL-S, WSMO service desc
• FOAF Profile
• .

Semantic Binding Ids
Service

• Deliver Metadata pointers through resource
  properties
• Zero impact on existing protocols

. . .
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Conclusions and future works

• Extensions to current Grid models to deal with
  flexible forms of explicit metadata
• The central component Semantic Binding
• Define a set of services (Semantic Provisioning
  Services) that play an important role in the
  exposure, delivery and generation of metadata
• ontology management and reasoning services,
  metadata services and annotation services.
• The actual mechanisms to be used for treating
  the new components as Grid entities and for
  delivering them as part of existing Grid service
  frameworks.

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Conclusions and future works

• Design principles
• The Semantic Grid is the Grid.
• The Semantic Grid has a spectrum of Semantic
  Capabilities.
• Painless migration to the Semantic Grid.
• Semantic Grid lifecycle.
• Multiple semantics.

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Conclusions and future works

• Challenges
• Technical
• architectural or theoretical foundations, the
  maturity of Semantic and Grid technologies,
• improving the performance of creating and
  retrieving semantically-encoded metadata
• Operational
• gathering and maintaining the semantic content
• Sociological and political
• legal, security and privacy implications of
  clearly exposed metadata and automated reasoning

51
QA
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Implementation

• e-Science
• myGrid

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e-Science

• e-Science is about global collaboration in key
  areas of science, and the next generation of
  infrastructure that will enable it.
• e-Science will change the dynamic of the way
  science is undertaken.
• John Taylor, DG of UK OST
• The Grid intends to make access to computing
  power, scientific data repositories and
  experimental facilities as easy as the Web makes
  access to information.
• Tony Blair, 2002

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UK e-Science Grid
55
UK e-Science Initiative

• 180M Programme over 3 years
• 130M is for Grid Applications in all areas of
  science and engineering
• Particle Physics and Astronomy (PPARC)
• Engineering and Physical Sciences (EPSRC)
• Biology, Medical and Environmental Science
• 50M Core Program to encourage development of
  generic industrial strength Grid middleware

56
Some UK e-Science Projects

• GRIDPP (PPARC)
• ASTROGRID (PPARC)
• Comb-e-Chem (EPSRC)
• DAME (EPSRC)
• DiscoveryNet (EPSRC)
• GEODISE (EPSRC)
• myGrid (EPSRC)
• RealityGrid (EPSRC)

• Climateprediction.com (NERC)
• Oceanographic Grid (NERC)
• Molecular Environmental Grid (NERC)
• NERC DataGrid (NERC OST-CP)
• Biomolecular Grid (BBSRC)
• Proteome Annotation Pipeline (BBSRC)
• High-Throughput Structural Biology (BBSRC)
• Global Biodiversity (BBSRC)

57
Some UK e-Science Projects

• Biology of Ageing (BBSRC MRC)
• Sequence and Structure Data (MRC)
• Molecular Genetics (MRC)
• Cancer Management (MRC PPARC)
• Clinical e-Science Framework (MRC)
• Neuroinformatics Modeling Tools (MRC)

• Interdisciplinary Research Collaborations Grand
  Challenge
• Advanced Knowledge Technologies
• Medical Images and Signals
• Equator
• DIRC (Dependability)

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Content

• e-Science
• myGrid
• Context
• Workflows, repository, registry and provenance
• Concept services
• Using concepts
• Discovering workflows and services
• Workflow composition support
• Discovering and linking experimental components
• Linking provenance logs
• Remarks

59
myGrid

• EPSRC UK e-Science pilot project
• Open Source Upper Middleware for Bioinformatics
• Knowledge-driven Middleware for data intensive in
  silico experiments in biology
• (Web) Service-based architecture -gt OGSA Grid
  services
• Targeted at Tool Developers, Bioinformaticians
  and Service Providers
• http//www.mygrid.org.uk

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Data intensive bioinformatics

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Graves DiseaseAutoimmune disease of the thyroid
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Services and toolkit
63
Workflows as in silico experiments

• Freefluo workflow enactment engine
• WSFL
• Scufl
• Workflow discovery
• Finding workflows that others have done, and that
  I have done myself
• Workflow creation
• Finding classes of services
• Guiding service composition
• We dont do automated composition
• Dynamic workflow enactment service discovery and
  invocation
• Choose services instances when running workflow
• User involvement

64
FreeFluo and Taverna environments

• Freefluo workflow enactment engine
• WSFL
• Scufl
• Taverna development environment

65
Investigation set of experiments metadata

• Experimental design components
• workflow specifications query specifications
  notes describing objectives applications
  databases relevant papers the web pages of
  important workers,
• Experimental instances that are records of
  enacted experiments
• data results a history of services invoked by a
  workflow engine instances of services invoked
  parameters set for an application notes
  commenting on the results
• Experimental glue that groups and links design
  and instance components
• a query and its results a workflow linked with
  its outcome links between a workflow and its
  previous and subsequent versions a group of all
  these things linked to a document discussing the
  conclusions of the biologist

• Life Science IDs URIs
• RDF-based annotations
• DAMLOIL -gt OWL ontologies

66
Bio in silico experiments service types

• Making in silico experiments
• workflow
• distributed database query processing.
• Managing experimental outcomes
• information management
• managing metadata
• Scientific method
• provenance management
• change notification
• personalisation

• Sharing experiments
• semantic services for discovering services and
  workflows, and managing metadata
• third party service registries and federated
  personalised views over those registries,
• ontologies and ontology management.
• The base services that tools that will constitute
  the experiments
• third party services such databases,
  computational analyses, simulations .
• specialised services such as AMBIT text
  extraction.

67
Experiment life cycle
68
Sharing info ? Sharing meaning

• Metadata
• Data describing the content and meaning of
  resources and services.
• But everyone must speak the same language
• Terminologies
• Shared and common vocabularies
• For search engines, agents, curators, authors and
  users
• But everyone must mean the same thing
• Ontologies
• Shared and common understanding of a domain
• Essential for search, exchange and discovery

• A common vocabulary of terms
• Some specification of the meaning of the terms
• A shared understanding for people and machines

69
myGrid Service Stack
70
myGrid Service Stack
71
W3C Ontology and Metadata languages

• OWL (and DAMLOIL)
• The Web Ontology Language OWL
• Family of languages OWL Lite, OWL DL OWL Full
• OWL DL DAMLOIL
• Expressive language for describing concepts,
  relationships, constraints and axioms
• Sound and complete, and efficient, reasoning over
  expressions to infer relationships between
  concepts rather than assert them (including the
  hierarchy).
• OWL is W3C Candidate recommendation.
• RDF
• Resource Description Framework
• W3C language for describing metadata on the Web
• Triples (subject, predicate, object) forming
  graphs
• Associate URIs (LSIDs) with other URIs (LSIDs)
• Associate URIs with OWL concepts (which are URIs)
• RDQL
• Triple store RDF implementations (e.g. Jena)
• http//www.w3.org/RDF

72
Concept services Ontology Services

• Ontology server for concept expressions
• Ontology development environments
• OilEd
• FaCT reasoner for inferring over concept
  expressions
• Imprecise matchmaking for best effort
  substitutability
• Reasoning over descriptions
• Generating classification structures
• Matchmaker and ranking for matching concept
  expressions
• Instance store for indexing instances of concept
  expressions in registries and databases

73
Concept services Annotation services

• RDF repositories
• Jena Toolkit
• RDF query languages RDQL
• myGrid Information Repository
• Version 1 Relational (DB2)
• Version 2 Federated architecture.
• Browsers for annotating objects and viewing
  annotations
• Automated tools for marking up objects with
  annotations.

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myGrid Information Repository

• Stores experimental components
• Workflow specs as XML Scufl docs
• Data
• XML notes
• Types
• XML docs
• Relational
• RDF (like)
• Every entry has Dublin Core provenance attributes
• Every entry can have (multiple) concept OWL
  concept expressions
• Multiple mIRs

75
Registries

• Publishes experimental components services,
  workflows and (distributed query plans in the
  future?)
• Multiple 3rd party registries
• Multiple 3rd party metadata

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Using Concepts

• Controlled vocabulary for advertisements for
  workflows and services
• Indexes into registries and mIR
• Semantic discovery of services and workflows
• Semantic discovery of repository entries
• Type management for composition
• Semantic workflow construction guidance and
  validation
• Navigation paths between data and knowledge
  holdings
• Semantic glue between repository entries
• Semantic annotation and linking of workflow
  provenance logs

77
Semantic discovery services workflows

• Services and workflows in registry have RDF and
  OWL descriptions
• Selection by the types of inputs they use,
  outputs they produce, the bioinformatics tasks
  they perform
• Querying using RDQL over RDF UDDI registry for
  operational metadata
• Matching using FaCT OWL classification for
  concept-based metadata

A registry browser
A workflow wizard
78
Find Components
79
Workflow construction

• Outputs and inputs of chained services are
  compatible
• OWL Concept
• XSD Type
• Data Format
• Workflows are constructed in collaboration with
  Scientist
• No automated workflow creation
• Find service being embedded into Taverna by end
  October like Geodise approach

80
Linking objects to objects via concepts
81
Reference

• Professor Carole Goble and the myGrid consortium,
  Knowledge-based Middleware for BioGrid services
  from the myGrid Project
• Professor Carole Goble and the myGrid consortium,
  The Role of Concepts in myGrid
• http//www.mygrid.org.uk
• http//www.semanticgrid.org
• http//www.w3.org
• An overview of S-OGSA a Reference Semantic Grid
  Architecture
• Oscar Corcho, Pinar Alper, Ioannis Kotsiopoulos,
  Paolo Missier, Sean Bechhofer and Carole Goble
  School of Computer Science The University of
  Manchester, Manchester, UK
• The Semantic Grid
• Wei Xing1 , Marios Dikaiakos2 (1School of
  Computer Science University of Manchester,
  2Department of Computer Science University of
  Cyprus)