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Case Study in e-Social Science

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Case Study in e-Social Science Rob Allan (CCLRC Daresbury Laboratory) Rob Crouchley (University of Lancaster) Building Collaborative e-Research Environments – PowerPoint PPT presentation

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Title: Case Study in e-Social Science


1
Case Study in e-Social Science
Rob Allan (CCLRC Daresbury Laboratory) Rob
Crouchley (University of Lancaster)
  • Building Collaborative e-Research Environments
  • JISC Consultation Workshops, 23/2/04 and 5/3/04

2
Specific Social Scientists Problems
  • They have much less experience and expertise in
    the use of the Grid than those typically from
    other research council areas
  • There is a significant intellectual gap between
    such disciplines and computer science
  • Distributed systems are also inherently complex
    and associated middleware products are not easy
    to use
  • The Open Middleware Infrastructure Institute
    (OMII) is likely to provide generic (open-source)
    middleware and associated services.
  • E-Science middleware currently not specifically
    targeted for the social science community.

3
Social Scientists Need
  • Help to develop a more computer-literate
    collaborative culture
  • Help to develop component-based software, visual
    composition tools and scripting languages which
    are easy to use
  • To exploit state-of-the-art software development
    technologies such as aspect-oriented programming
    to enhance flexibility.
  • Middleware could be the catalyst for re-use and
    sharing in the e-Social Sciences. Some examples
    and ideas follow.

4
Some Features of Social Science Research
  • Research motivated by a desire to determine
    causality
  • Involves
  • identifying the various factors which influence
    the behaviour or outcome of interest and
    quantifying their effects
  • controlling for all the different confounding
    factors which would otherwise result in spurious
    relationships and misleading results.
  • Randomised experiments not feasible, we cannot
    randomly allocate individuals to different levels
    of training in order to evaluate programs.
  • We rely on observational data, i.e. data that
    have been obtained from surveys and censuses.
  • This is different to exact sciences like
    physics and chemistry where repeatable
    experiments can be performed.

5
3 related Aspects of Soc. Sci. Research
6
Soc. Sci. needs Comprehensive Models
  • Interdependent sub models, we need joint models
    for the data complexities and the core processes
    we want to understand
  • Models are not linear in the parameters, require
    special procedures and are highly computationally
    intensive due to the high dimensionality and the
    interdependent sub models.
  • Simple analyses are usually very misleading about
    the role of the controls, eth, sex etc.
  • Soc. Sci. research is complex - large parameter
    space, many interpretations and models which need
    to be tested. Cannot be done in isolation
  • Increasing need to link components and access
    large computers/ data sets from desktop.

7
E-Science Technology can link Components!
8
New Tools The Analysis Cycle
Main ESDS Data Sets
TTWA Data, NOMIS
Select Data Set and Appropriate Variables
Merge Files Add Variables
Contextual Data
Working Data
Results
9
New Tools Simultaneous Analysis
Example research in educational attainment
10
E-Science can enhance Collaboration!
  • Particularly important in qualitative research
  • Enable comparison of different markup/
    interpretation
  • Direct access to datasets for validation
  • Direct input of data from fieldwork involving
    questionnaires, photography etc.
  • Delivery/ input devices (some mobile) may
    include portals, Access Grid, PC tablets, PDA,
    camera, phone etc.

11
New Tools Collaboration in Video Markup
VIDGRID Multiple video streams can be delivered
into an AG or portlet environment
12
Training and Awareness in e-Social Science!
  • Project ReDReSS Resource Discovery for
    Researchers in e-Social Science
  • to accelerate the development and awareness of
    a new kind of computing and data infrastructure
    for the Social Sciences, and to support the
    increasingly national and global collaborations
    emerging in many areas of Social Science
  • To help illustrate appropriate methodologies and
    software that admits the full complexity of
    substantive problems
  • To help articulate the middleware needs of social
    researchers
  • To help nurture and support a community of social
    researchers
  • To help to provide critical mass and improve the
    efficiency of interactions between the interested
    researchers, thus reducing the number of lost
    opportunities for social science.


13
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14
We will use/ contribute to existing technologies
  • Resource discovery
  • Sharing tools
  • Personalised workspaces
  • Flexibly delivery

15
Samples showing use of CHEF framework for ReDReSS
and delivery of lecture material by video
16
E-Science enabling a Virtual Research Environment!
  • to make the use of e-Science technologies,
    methodologies and resources easier and more
    transparent than simply developing bespoke
    applications on an infrastructure toolkit (such
    as Globus GT2 or OGSI/ WSRF).
  • We need to
  • Bridge the gap between different types of
    technology (database management, computational
    methods, data collection, networks, Condor
    resources, visualization systems, collaborative
    working, Access Grid, etc.)
  • Build on pilot projects and take input from other
    disciplines
  • Link to core JCSR clusters and resources at other
    e-Science Centres
  • Provide an environment to enhance the
    programmability and usability of such a Grid by
    integrating work from a number of ongoing
    projects and encourage community input.

17
The Grid Client Problem
Many clients want to access a few Grid-enabled
resources
Grid Core
Consumer clients PC, TV, video, AG
Middleware e.g. Globus
Workplace desktop clients
Portable clients phones, laptop, pda, data
collection
Grid Core
18
Some VRE Functions
  • Authentication, Authorisation and Accounting
    use Shibboleth and Permis in line with JISC
    proposals
  • Community development of content - Content
    Management and Editing tools
  • Access to middleware resources and documentation,
  • Access to training materials and resources,
  • Enable shared development of services/
    applications,
  • Access to a consultancy/ support service,
  • Application Management Services - user access via
    pre-defined tools and applications to the UK
    e-Science Grid
  • Data Management Services discovery,
    authorisation, transfer, replication, upload,
    validation, curation
  • Access to Broadcasts - on the Access Grid
    network
  • Management Functions - for experts to maintain
    the system and guide non-experts, e.g. via expert
    systems and workflow.

19
Functionality/Content of the VRE
20
Sanity Check
  • However a number of areas significant for a
    production Grid environment have hardly yet been
    tackled. Issues include
  • Grid information systems, service registration,
    discovery and definition of facilities
  • Security, in particular role-based authorisation
  • Portable parallel job specifications
  • Meta-scheduling, resource reservation and on
    demand access
  • Dynamic linking and interacting with remote data
    sources
  • Wide-area computational/ exprtimental steering
  • Workflow composition and optimisation for complex
    procedures
  • Distributed user and application management
  • Data management and replication services
  • Grid programming environments, PSEs and user
    interfaces
  • Auditing, advertising and billing in a Grid-based
    resource market
  • Semantic and autonomic tools
  • Usability issues, ethics, etc

21
Human Factors
  • Customised delivery may be key to long-term
    uptake
  • Use an environment familiar to the researchers,
    e.g.
  • Web portals - training, awareness, search tools
    (search engines are popular)
  • Libraries - e.g. C for programmers
  • Programming environment e.g. R for statistical
    analysis with well-known packages
  • Sound, video for virtual collaboration (TV is a
    popular medium)
  • Bottom line
  • There is a lot we can/ need to do, but
  • Social Science is already hard the scientists
    need tools that do not make it harder!

22
UK E-Social Science Programme
  • There is currently a growing body of work and
    projects in this area
  • Pilot projects - ESRC
  • ReDRESS Resource Discovery for Researchers in
    e-Social Science JISC
  • UK National Grid Service e-Science Grid - JCSR
    and DTI Core Programme
  • NCeSS National Centre for e-Social Science -
    ESRC
  • CQeSSS Centre for Quantitative e-Social Science
    Support - ESRC ( future NCeSS nodes)
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