semantic web and the grid brian matthews. 2 eurocris seminar 2004 2 contents a changing environment...

Semantic Web and the Grid

Brian Matthews

2Brian Matthews 2euroCRIS seminar 2004

Contents

• A Changing Environment for Research

• The Semantic Web

• The Grid

• The Semantic Grid

• What does that mean for CRIS and OA?

• Conclusion

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A Future Environment for Research

• OA and CRIS as drivers for the management and access to information

• Need for shared metadata and exchange mechanisms

• Central control impossible/undesirable– a loosely coupled federated approach– based on common interchange and access standards– W3C, GGF, IETF, OASIS, EuroCRIS, WfMC etc

• Changes in technology– resource discovery– enables access

• Two leading technology opportunities– Semantic Web and the GRID

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The Semantic WebAdding machine readable information about the web, to the

web.

• The Web is chaotic - why are resources are linked?– Imagine a library where all the books have the same text on the cover, and the only catalogues are

compiled by photocopying the books, cutting up the copies, and arranging the words in the order of frequency. Johan Hjelm

• Google is great at returning all the pages on the web that mention "Tim Berners-Lee“

– But what about returning those pages written by Tim Berners-Lee?

• The Semantic Web adds well-defined meaning to describe the Web (Metadata).

The Semantic Web is an extension of the current web in which the information is given well-defined meaning, better enabling computers and people to work in cooperation

– Tim Berners-Lee, James Hendler and Ora LassilaThe Semantic Web, Scientific American, May 2001

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Add Meaning to Resources

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Semantic Web:A Layered Architecture

Basic Syntax of the Web

Language of triples for describing resources

Formalism for defining and sharing vocabularies

Reasoning over statements about resources

“The Web of Trust”

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Machine Readable Meaning

• Meaning becomes machine readable - so software agents can use it for: – Improving searches (indexing, cataloguing)– Convey information on the usage of the resource

(access control, IPR). – Convey information on the actors involved (user

preferences, device profiles, privacy preferences) – Give third party opinions on the content of another

site (rating services, brokering).

• Essentially, Metadata of all kinds

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Progress so far

• A lot more than you might think!• Base standards are now mature:

– RDF, RDF Schema, OWL– many others reaching maturity:

• Many shared vocabularies emerging– DC, DMoz, Prism, FOAF, VCard, SKOS, RSS….

• Lots of RDF out there!– Mozilla, Adobe, RSS,

• Still a lot of work to do – reasoning, trust, provenance, tools,

• But we are getting there!

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Example: SKOS• Community effort led by

CCLRC/W3C• A vocabulary to represent

Thesauruses• Heavily used in the library

community– but traditionally locked up in institutional

databases

• Allow people to share controlled vocabularies for cataloguing resources

• Examples– GEMET – environmental data– GCL – e-Government– English Heritage – W3C glossary

CRIS 2

CRIS 1

CRIS portal

Query distributor

and collator

Users

Thesaurus Service

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Example: Simile• Project of MIT + HP Labs + W3C• Publishing digital library information onto the semantic

web. • Make semantic interoperability of metadata a reality for

digital libraries by:– providing reusable software for browsing, searching and mapping

heterogeneous metadata– using semantic web technologies– identifying issues, gaps and best practices

• allow libraries to share information• Provide semantic web browser, and RDF based datasets

– for art history information– combined from different sources

• Using SKOS as the thesaurus format.

• OA within the Semantic Web

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Semantic Web and OA

• Semantic web provides an underlying mechanism to support OA:– common metadata – data exchange mechanism– searching and browsing across web – query language and logic– interoperability– lose coupling.

• Can also support CRIS this way too.– CERIF in OWL (Lopatenko)

• And also Data Sets– CCLRC Metadata format – also in RDF Schema

• But that is not the only main technology change

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The GridThe Grid provides an environment that enable software

applications to integrate instruments, displays, computational and information resources that are managed by diverse

organisations in widespread locations.

• Provide access to a global distributed computing environment– via authentication, authorisation, negotiation, security

• Identify and allocate appropriate resources– interrogate information services -> resource discovery– enquire current status/loading via monitoring tools– decide strategy - eg move data or move application– (co-)allocate resources -> process flow

• Schedule tasks and analyse results– ensure required application code is available on remote machine– transfer or replicate data and update catalogues– monitor execution and resolve problems as they occur– retrieve and analyse results - eg using local visualization

• So far typically in large-scale science and engineering.

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To make this happen you need . . .

• agreed protocols (cf WWW -> W3C)• defined application programming interfaces (APIs)• existence of directories for both system and

application• distributed data management• availability of current status of resources • monitoring tools• accepted authentication procedures and policies• network traffic management

provided by Grid-based toolkits and services

Brian Matthews 14euroCRIS seminar 2004

GRID History

• mid 90s – Globus• The GRID Bible• Based on “traditional”

protocols (IETF)• Taken up by e-

Science • Standardised via

GGF• Now converging with

Web– Web Services - WSRF

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Computer simulations

real-timecollection

Multi-sourceData Analysis

desktop & VR clients with shared controls

Unitary Plan Wind Tunnel

Example: NASA IPG

archival storage

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Example: DataGrid

• LHC will produce several PBs of data per year for at least 10 years from 2005 .

• Data analysis will be carried out by farms of 1000’s of commodity processors (the “computing fabric”) in each of about 10 regional Tier1 centres - RAL is UK Tier1

• Each Tier1 centre will need to hold several PBs of raw data and results of physics analysis

• Strong focus on middleware and testbeds - open source

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What Next? The Semantic Grid

Semantic Grid

distributed computation

GRIDWEB

Semantic Web

ma

chin

e re

ada

ble

se

man

tics

thanks to Dave de Roure

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What Next? The Semantic Grid• Current GRID is

“hand-crafted”– users have to know a lot

about the available resources

– users have to “write scripts” to use the GRID

• Add machine readable semantics (metadata)– The Semantic GRID

Semantic Grid

distributed computation

GRIDWEB

Semantic Web

mac

hine

rea

dabl

e se

man

tics

thanks to Dave de Roure“the GRID is an application

of the Semantic Web”de Roure, Goble

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But what does that mean?

• more automation

• more negotiation

• more autonomy

• more self-monitoring and control

• use of autonomous agents

• Will make the Grid much more like the electricity Grid– You don’t need to know where the stuff comes from.

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• Major UK e-Science project– Bio-informatics– In-silico experimentation – www.mygrid.org.uk

• Based on a GRID architecture• Uses Semantic Web Tools for

– Workflow and service discovery • Prior to and during enactment• Semantic registration

– Workflow assembly• Semantic service typing of inputs and outputs

– Provenance of workflows and other entities– Experimental metadata glue– Use of RDF, RDFS, DAML+OIL/OWL

• Instance store, ontology server, reasoner• Materialised vs at point of delivery reasoning.

– myGrid Information Model

• About to join them to work on workflow

Semantic Grid Example

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What does this mean for CRIS & OA?

Portal with knowledge-assisted user interface

Digital Curation Facility

SCIENTIFIC DATASETS

metadata

PUBLICATIONS

metadata CRISmetadata

publish

validate

GRIDs

Ambient, Pervasive Access

The Semantic Grid is what makes this work!

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Example: Validation

• Validate results from paper– need to access paper (OA)– need to link to data (and metadata)– need to access analysis and visualisation tools– need common metadata and access to resources

across Grid.

Grid middleware

Local data

Local metadata

DA 1

Data Portal Pub Portal

Local data

Local metadata

DA 2

Local data

Local metadata

IR 1

Local data

Local metadata

IR 2

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Example: Science as a process

• Within a Grid environment

Submit proposal

Prepare experiment

Generateresults

Analyseresults

Write report

Provenancemetadata + access

conditionsdata

description ++ +datalocation

Related material

Collecting the metadata can then become part of the experimental support environment

CRISDA IR

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Example: the Nature of a Publication

• Traditional publication as continuous text, with static graphs and images

• Change the notion of the content of the publication– hypertext– include active components – links to simulations, visualisations

• a much more dynamic document– a multimedia presentation

• How will publishers cope?• How will publication archives cope?

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So how to achieve this?• Resource discovery

– good metadata– common formats– standards

• Resource negotiation– for data and services

• Quality of service guarantees

• Policies and contracts• Security and trust• Provenance• Monitoring and

payment

• Work flow• Reasoning tools• Autonomous agents• Autonomic systems• Links to legacy

– especially database systems

– querying systems

• Collaborative working environments

• Design methods

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Progress

• Moving quite fast on this from many different directions– e-Science– Next Generation Grid Report– FP6/7– Semantic Grid at GGF– OA initiatives– Digital Curation a major concern

• Real exciting opportunity to pull it all together

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Conclusions

• Semantic Grid and Open Access– enables – enabling

• CRIS as an information coordinator• Archiving and curation

– need to archive much more– data, programs, visualisation and analysis tools, formats,

calibrations, versions, OS ……

• Workflow a key component• Metadata collection and maintenance is a big

problem.

B.M.Matthews@rl.ac.uk