David De Roure

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• David De Roure

Reflections and Projections
cloud
grid
Mexico Edition
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• David De Roure

SemanticGrid
Cloud?
Mexico Edition
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e-Science is about global collaboration in key
areas of science and the next generation of
infrastructure that will enable it
John Taylor
There are a number of grid applications being
developed and there is a whole raft of computer
technologies that provide fragments of the
necessary functionality. However there is
currently a major gap between these endeavours
and the vision of e-Science in which there is a
high degree of easy-to-use and seamless
automation and in which there are flexible
collaborations and computations on a global scale.
Semantic Grid Report 2001
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Scientists
Need something here

• Grid Infrastructure

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Map of talk... Mind the Gap!

• This talk is about our adventures in the gap
• Looking downSemantic Grid
• Looking up Science 2.0
• Looking forward the ecosystem evolves

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1. Semantic Grid
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Why Semantic Web?
Original slide but still true!

• Huge potential for Science
• making data reusable, interlinked
• making connections between decoupled content
• generating new intelligence
• Automation requires machine-processable
  descriptions
• Grid community talking about metadata and
  knowledge

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My Chemistry Experiment

• Box of Chemists

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The Semantic Datagrid

• Holistic approach
• Accelerates time-to-experiment
• Semantic Web works well for data where flexible
  schema required
• Complete provenance trail from lab to scholarly
  output
• Makes outputs reusable
• Built a web not a warehouse

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Grid Research Projects under FP6
international cooperation
supporting the Grid community
EU Funding 130 M
Grid services, business models
trust, security
BeinGrid business experiments
platforms, user environments
data, knowledge, semantics
XtreemOS Linux based Grid operating system
Wave 2 start 2006
Integrated project
Network of excellence
Specific targeted research project
Specific support action
Wave 1 start 2004

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Semantic OGSA
Application 1
Application N

• Semantic Grid Reference Architecture
• A low-impact extension of OGSA
• Everything is OGSA compliant
• Mixed ecosystem of Grid and Semantic Grid
  services
• Services ignorant of bindings
• Services binding aware but unable to process them
• Services binding aware and capable of processing

Optimization
Security
Data
Execution Management
Semantic Services
Resource management
Information Management
Infrastructure Services
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Service-Oriented Knowledge Utility
NGG3
The architecture comprises services which may be
instantiated and assembled dynamically, hence the
structure, behaviour and location of software is
changing at run-time
A utility is a directly and immediately useable
service with established functionality,
performance and dependability, illustrating the
emphasis on user needs and issues such as trust
Services are knowledge-assisted (semantic) to
facilitate automation and advanced functionality,
the knowledge aspect reinforced by the emphasis
on delivering high level services to the user
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2. Web 2.0
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Note to Reader. The next slides are not intended
to be anti-grid. Everyone working on Grid is
doing great work.
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use Web 2.0 here?
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use Web 2.0 here?
Grid
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use Web 2.0 here
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N
N2
N
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N
One Middleware
2N
N
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N
Middleware
Middleware
Middleware
?
Middleware
Polynomial involving N1,N2 and M
Middleware
Middleware
N
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Its a long haul(?)

• Distributed computing is difficult
• As demonstrated by CORBA, OGSA, ...
• Were getting there slowly

• Err, excuse me, the Web works!

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• David De Roure

How Repositories can avoid Failing like the Grid
2.0
Repository Fringe
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So has the Grid failed?

• There have been successes BUT...
• Theres a usability problem
• For both developers and users
• Theres a relevance problem
• Not solving the problems that people really want
  solved
• Providing solutions where other solutions may
  already exist

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3. Evolution
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Changing circumstances

• Things are really moving on
• Technology e.g. multicore, virtualisation
• Thinking and practice e.g. Open Science,
  data-intensive science
• Deployed systems e.g. HPC, Cloud, Repositories
• Community, especially across disciplines
• See examples on following slides...
• Observing growing emphasis on data and software
  over computation

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Understanding future requirements

• Atkinson E-Science Directors forum CIR strategy
• De Roure New e-Science
• Goble The Future of Research

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Linked data
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Scientists
Really simple interfaces to data, automation,
computation, annotation and sharing.Ease of
assembly.
e.g. Web 2.0, Workflows and Semantic Web

• e-Infrastructure

HPC
Google
Multicore desktop
Virtualisedservers
Grid
Repositories(data, workflows, software)
Amazon
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Our Research Agenda

• Our users want e-Laboratories in which to conduct
  their research
• We are making these easy to build
• Our approach is based on
• Usercentricity
• Utility services
• Research Objects
• In fact we are building an e-Laboratory factory!
• Semantic Web for Research Objects, annotation and
  operational support

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Your Research Agenda

• Many of the challenges of Grid computing remain
  as relevant as ever or more so
• Cloud and Grid are DIFFERENT. They solve
  different problems. They are not straight
  alternatives. And there are lots of cloud papers
  to be written!
• Compare with standards-based Semantic Web and
  community-based Web 2.0 being seen 2 years ago as
  competing futures now they are symbiotic
• Important new challenges in
• Ease of assembly of tools, services and software
• Data quality, curation and stewardship
• Assistance and automation

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Take Homes

• Cloud and Grid are DIFFERENT
• Utility computing lives (see cloud)
• Virtual Organisations live (still a difficult
  sociotechnical problem)
• Need really simple interfaces to data,
  automation, computation, annotation and sharing.
  Ease of assembly.
• Linked data has traction
• Lots of research challenges!

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Good computer science makes things simpler, not
more complicated
me
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• For papers see
• wiki.myexperiment.org
• Contact
• David De Roure
• dder_at_ecs.soton.ac.uk
• Carole Goble
• carole.goble_at_manchester.ac.uk