uptake and sustainability of e-research technologies
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Uptake and Sustainability of e-Research Technologies. Alexander Voss [email protected] National Centre for e-Social Science and e-Science Institute. e-Science. - PowerPoint PPT PresentationTRANSCRIPT
25th Oct., 2006
Uptake and Sustainability of e-Research Technologies
Alexander Voss
National Centre for e-Social Science and e-Science Institute
25th Oct., 2006 2
e-Science
…the large scale science that will increasingly be carried out through distributed global collaborations enabled by the Internet. Typically, a feature of such collaborative scientific enterprises is that they will require access to very large data collections, very large scale computing resources and high performance visualisation back to the individual user scientists.
(Research Councils UK)
Goal: to enable better research in all disciplines, to enable research that was not feasible previously
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Drivers
Technical– Faster, cheaper devices, higher resolutions, increased
throughput, cheaper and higher capacity storage, increased bandwidth, etc.
Research Process: coping with the data deluge– Finding and accessing data– Independent provision and ownership, local policies– Linking data– Processing data– Interpreting data – Presenting results
Increased international collaboration Doing what was previously impossible
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e-Research in the UK
UK e-Science Programme (since 2001)
International Programmes (esp. US, EU)
Supported data and information services
Access to scientific facilities Communities developing
resources, systems and practices
Pilot projects in most areas Core middleware development
and code repositories
Replace with google map
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Grid Technologies
‘An infrastructure that enables flexible, secure, coordinated resource sharing among dynamic collections of individuals, institutions and resources.’
(Ian Foster and Carl Kesselman)
Like the power grid, the Grid makes services available through common interfaces without the user having to worry about the details of how these services are provided.
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Grid Technologies
What characterises a grid?– Coordinated resource sharing– Standard, open, general-purpose protocols and interfaces– Delivering non-trivial qualities of service
Vision of “the Grid” not yet achieved and there are reasons why it may never be, but many ‘grids’ which each support one or more…
‘Virtual organisations’: people in different organisations seeking to cooperate and share resources across their organisational boundaries
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The Web, the Grid and the Internet
The Web provides access to documents (at least that is what it has been designed for)
Communication between remote servers and person using web browser
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The Web, the Grid and the Internet
The Web provides access to documents (at least that is what it has been designed for)
Communication between remote servers and person using web browser
The Grid provides access to resources - data, computation, experimental apparatus, etc.
Communication between resources brought together to perform an overall task
Does not replace but rather complements the Web
The Internet is the common underlying infrastructure for both - it provides connectivity and basic management of networks independent of their use.
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Grid Middleware
Resources
Applications
Grid Middleware
Grids support a vast range of applications accessing a range of different resources.
Grid Middleware provides the ‘glue’ that binds them together.
Open, standardised interfaces reduce the complexity of the interface between resources and applications.
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Related (but not identical) concepts
Internet computing (e.g., FightAIDS@Home) Peer-to-peer computing (e.g., Napster) Utility computing (e.g., Sun, IBM) Cluster computing (e.g., supercomputing, reliability) Distributed systems (e.g., e-Business) Groupware (e.g., Lotus Notes)
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What is e-Research?
Extension of the concept of e-Science into other domains (social sciences, arts & humanities) and an extension from large research institutions into all parts of life where research might be conducted (e.g. in schools or at home).
Recognising the ‘small steps’ that are sometimes crucial in ‘big science’.
Grid technologies are not sufficient on their own to enable the vision of e-Science, other elements are needed, e.g., data sharing agreements, changed reward structures, domain standards, etc.
Focus more on uses of ICTs in research than on the technology per se.
e-Research is an emerging phenomenon - we all make use of modern ICT infrastructures in our daily research activities.
Example 1: Integrative Biology
Integrative Biology VRE 13
Overview - Integrative Biology IB is an EPSRC-funded e-
Science project tackling UK’s two biggest killers: cancer and heart disease through large-scale multi-scale simulations.
Globally distributed and inter-disciplinary community: US, Europe, New Zealand
Developing a web-services based grid infrastructure providing tailored access to compute and data resources.
Courtesy of Matthew Mascord, Oxford e-Research Centre
14
Heart ModellingRequires access to compute resource, data management facilities, visualisation capability and collaborative working tools.Typically solving coupled systems of PDEs (tissue level) and non-linear ODE’s (cellular level) for the electrical potential.Complex three-dimensional geometries
Partners:Oxford, Sheffield,NewOrleans, Washington Lee, UCSD,UCLA, Baltimore, Monash, AucklandGraz, Utrecht
Partners:Oxford, Sheffield,NewOrleans, Washington Lee, UCSD,UCLA, Baltimore, Monash, AucklandGraz, Utrecht
Image is part of a study to figure out the arrangement of different cell types in the heart wall that accounts for the shape of the T wave in the ECGCourtesy of Richard Clayton, Sheffield
Courtesy of Tulane/Oxford
Investigation of how ischemic tissue interacts with electric shocks in order to improve defibrillation efficacy in patients with coronary heart disease (Tulane/Oxford
Visualization of Cardiac
Virtual Tissue
Courtesy of the Integrative Biology Consorium, funded by EPSRC
Example 2: e-Social Science
(Grid-enabled microeconomic data analysis)
• Researchers frequently have to use more than one data set in order to obtain a more complete answer to their questions
• One data set may provide a large sample of the target population, but offer incomplete coverage of the topics of interest
• Another data set with coverage of the topics of interest may not sample the target population adequately
Background
Social Science Problem And Policy Issue
What do we know about ethnic minority economic welfare when it is disaggregated by group and geography
Census data can lack direct measures of income
Survey data yield minority samples that may be too small for meaningful results to be obtained
Courtesy of Simon Peters
Data The British Household Panel Survey (BHPS) provides
the small scale survey data.
•BHPS is a longitudinal (panel) study with yearly waves.
The Sample of Anonymised Records (SARs) provides the large scale Census data.
•SARs are a random sample of individuals and households from the UK Census
Uses 1991 data because of projected confidentiality restrictions on the publicly available version of the 2001 SARs.
•2% sample of individuals, 1% sample of households.
Courtesy of Simon Peters
Courtesy of S
imon P
eters
Courtesy of S
imon P
eters
Example 3: Environmental e-Science
(Grid for Ocean Diagnostics Interactive Visualisation and
Analysis)
Exploring environmental data with Google Maps and Google Earth
• “Godiva2” website provides very quick visualisations of numerical model and satellite data
• Scientists use an interactive website to select dataset to visualise on a draggable, zoomable map
– can view data at large range of scales• Can then view same data in Google
Earth– 3-D globe– Lightweight, easy to use GIS tool– Can visualise alongside other
datasets• Don’t have to download any data!• Images generated dynamically on the
server• Spin-off from GODIVA project
Courtesy of Jon Blower
Example 4: Archaeology
(Silchester Roman Town)
25th Oct., 2006 24Courtesy of Michael Fulford
25th Oct., 2006 25Courtesy of Michael Fulford
25th Oct., 2006 26Courtesy of Michael Fulford
25th Oct., 2006Silchester: A VRE for Archaeology
Integrated Archaeological Database
Courtesy of Michael Fulford
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Examples have show instances of:
Use of public datasets Confidentiality issues Use of high-performance computing Fieldwork - not all research happens inside! Mapping geographies Record linkage (coping with incomplete data) Use of national infrastructures Collaborative activities Various web-base, desktop and mobile user interfaces Management of large datasets Meta-data: where is data from, what can be said about it? Mining data Using data previously thought worthless or intractable
Research Challenges
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Dealing with complexity and heterogeneity
Just four examples have highlighted the complexity and heterogeneity of what is meant by ‘e-Research’.
There tend to be similarities as well as differences between the needs of different researchers.
This is where the chance lies for building common infrastructures while supporting – a wide range of different research activities– and different kinds of resources,– across organisational contexts.
Need to know about the different cultures in, say, particle physics and sociology.
Teasing out the similarities and differences is an important part of realising e-Research.
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We need to know more about:
The early adopters, the interested, the disengaged What motivates people to collaborate and share What the barriers to entry are and how they can be overcome How e-Science endeavours can be effectively and efficiently
managed in different organisational contexts How we can manage user-designer relations to ensure what we
build is useful and usable. How we can ensure people have reasonable expectations of what
can and cannot be done How we engage future generations of researchers to engage in
research in the first place and to make use of the vast potential of e-Research.
And other socio-technical issues
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Broad themes
Supporting Innovation and Diffusion Improving usability Fostering new forms of research and community Deployability, configurability and sustainability National and International Comparisons Measuring Impact of e-Research
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Commodification
The process that transforms the market from a collection of individual, proprietary and idiosyncratic products to one that defines open standards and provides competing but interoperable implementations.
Aims are to:– Flatten the learning curve– Easy deployment– Centrally provide functionality– Overcome / leverage network effects
OGF - engaged in standardisation OMII - repository of production software NGS - national service providing a compute grid and operations
support Role that University Computing Services play: centrally and locally
provided services will be required.
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Project Management
Proposals are sales documents! Project funding assumes a project plan is in place and work can
start soon This is routinely not the case E-Research projects tend to differ from other IT development
projects, e.g.:– Multiple stakeholders with only partially aligned agendas– Raised expectations– Different ways of working and professional cultures– Short timelines (funding)
Project management often tells us what to do but not how to do it. Need to pay attention to the ‘seen but unnoticed’ skills of good
project managers:– e.g., tackling problems arising from peoples’ different motivations and
professional identities and languages
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Democratic e-Research
How we communicate with the wider public is crucial where we touch upon potentially contentious issues or make use of personal data.
This requires further interdisciplinary work involving, e.g., ethicists and social science researchers– EthOx centre in Oxford– Innogen in Edinburgh
Also, involvement of the wider public as active participants in research activities.
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Democratic e-Research
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User-Designer Relations in e-Research
Designers of e-Research systems need to be familiar with the working practices and concerns of researchers
Researchers need to understand what is possible, what is feasible and what is not, what the tradeoff between different options are
This involves a degree of familiarity with the research domain and e-Research technologies. This can be achieved through:– Training (e.g., bioinformatics, Grid literacy)– Boundary spanning (e.g., researchers employed on projects)– Facilitation (e.g., workplace studies)– Shared practice (co-location, corealisation)
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eSI Theme Activities
Establish and consolidate what we already know– e-Research BOK: Formulating e-Research practices– 1st step: Realising e-Research Endeavours, call to be issued
end November, workshop in March ‘07, write-up soon after
Identify major gaps and address through– Targeted research (focused observational studies, interviews,
surveys, depending on the issue at hand)– in collaboration with other projects as well as– seeking additional grants
Workshops and Visitors as input and control mechanism Raise awareness of e-Research in the communities Aim to drive technical development
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Prior Work
Usability Task Force: Usability Research Challenges in e-Science
JISC Human Factors Audit of Selected e-Science Projects
Angela Sasse and Brock Craft: Security and Usability of Grid Projects: Implications for e-Science
Paul David: Towards a Cyberinfrastructure for Enhanced Scientific Collaboration: providing its ‘soft’ foundations may be the hardest part
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Related Activities
Projects funded under EPSRC Usability Call AVROSS (EU Strep): e-Social Science JISC e-Infrastructure Call (Issued end Sept.)
– Barriers to Uptake– Service Usage Models (practice templates)
SUPER: informing prioritisation of e-Infrastructure work Usability Task Force Portal: assembling a network of
people working in this area and disseminating results
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Outlook
There is still much to be done to deliver the promise of e-Science and to extend its uptake. Each step requires work. More research communities will need to agree their methods of collaboration. The technology requires further development, in particular to make it more usable, versatile and economic. And production support requires more operational experience and extension of arrangements for sharing. It is now time to expand its application across the academic world and to introduce it to students as well as to academics.
(Malcolm Atkinson writing in THES)
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Credits
Malcolm Atkinson, e-Science Envoyand Director of the e-Science Institute
Anna Kenway, Deputy Director of the e-Science Institute Rob Procter, Research Director, NCeSS Tom Rodden, University of Nottingham and Usability
Task Force Colleagues who have kindly allowed me to use their
slides
Questions, please…