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
• JISC Consultation Workshops, 23/2/04 and 5/3/04

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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.

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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.

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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.

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3 related Aspects of Soc. Sci. Research
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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.

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E-Science Technology can link Components!
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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
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New Tools Simultaneous Analysis
Example research in educational attainment
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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.

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New Tools Collaboration in Video Markup
VIDGRID Multiple video streams can be delivered
into an AG or portlet environment
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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.

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We will use/ contribute to existing technologies

• Resource discovery
• Sharing tools
• Personalised workspaces
• Flexibly delivery

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Samples showing use of CHEF framework for ReDReSS
and delivery of lecture material by video
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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.

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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
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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.

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Functionality/Content of the VRE
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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

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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!

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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)