R e D R e S S Case Study in e-Social Science Building Collaborative e-Research Environments JISC...
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Transcript of R e D R e S S Case Study in e-Social Science Building Collaborative e-Research Environments JISC...
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S Case Study in e-Social Science
Building Collaborative e-Research Environments JISC Consultation Workshops, 23/2/04 and 5/3/04
Rob Allan (CCLRC Daresbury Laboratory)
Rob Crouchley (University of Lancaster)
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SSpecific Social Scientists Problems
1. They have much less experience and expertise in the use of the Grid than those typically from other research council areas;
2. There is a significant intellectual gap between such disciplines and computer science;
3. Distributed systems are also inherently complex and associated middleware products are not easy to use;
4. 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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SSocial Scientists Need
1. Help to develop a more computer-literate collaborative culture;
2. Help to develop component-based software, visual composition tools and scripting languages which are easy to use;
3. 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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SSome Features of Social Science
Research
• Research motivated by a desire to determine causality• Involves
1. identifying the various factors which influence the behaviour or outcome of interest and quantifying their effects;
2. 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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S3 related Aspects of Soc. Sci. Research
Observational Data, usually full of holes-missing data-measurement error-dropout
Substantive Theory-what determines what-not comprehensive-often contradictory
Methodology-only partially developed
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SSoc. 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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DataManagement
A
DataManagement
B
DataManagement
C
Analysis A Analysis B Analysis C
Middleware
E-Science Technology can link Components!
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SNew Tools: The Analysis Cycle
Main ESDS Data Sets
Select Data Set and Appropriate Variables:
TTWA Data, NOMIS
Merge Files: Add Variables
Working Data
Contextual Data
Results
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SNew Tools: Simultaneous Analysis
National Pupils Database
Psychologists Analysis
Geographers Analysis AnalysisLocational Analysis B
Economists Analysis
Educationalists Analysis
Example: research in educational attainment
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SE-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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VideoCorpus
Researcher A
Researcher B
Researcher C
VIDGRID: Multiple video streams can be delivered into an AG or portlet environment
New Tools : Collaboration in Video Markup
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STraining 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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SWe will use/ contribute to existing
technologies
• Resource discovery
• Sharing tools
• Personalised workspaces
• Flexibly delivery
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SE-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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SThe Grid “Client Problem”
Grid Core
Consumer clients: PC, TV, video, AG
Workplace: desktop clients
Portable clients: phones, laptop, pda, data collection
Middleware
e.g. Globus
Grid Core
Many clients want to access a few Grid-enabled resources
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SSome 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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Middleware/Software Library
Access GRID
Security Authorisation Authentication
Text Mining/ Data services
UK GRID Services
D
JJISC PortalJISC Portal
Portal Management
Semantic GRID Services
VLE Portal VRE
Portal
Awareness Raising Resources
Workshops
Functionality/Content of the VRE
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SSanity 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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SHuman 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, butSocial Science is already hard – the scientists need tools
that do not make it harder!
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SUK 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)• …