Town Hall Presentation, February 9, 2009, London
Building a UK Foundation for the Transformative Enhancement of Research and Innovation Report of the International Panel for the 2009 Review of the UK Research Councils e-Science Programme D. E. Atkins, Chair atkins@umich.edu
Panel Members Daniel Atkins, Chair Nathan Bindoff Christine Borgman Mark Ellisman Stuart Feldman Ian Foster Albert Heck Dieter Heermann Julia Lane Luciano Milanesi Jayanth Paraki Wolfgang von R端den Alexander Szalay Paul Tackley Han Wensink Anders Ynnerman
(left to right) Anders Ynnerman Linköping University, Sweden
Paul Tackley
ETH Zürich, Switzerland
Albert Heck Utrecht University, Netherlands
Dieter Heermann U. of Heidelberg, Germany
Ian Foster
ANL & U. of Chicago, USA
Mark Ellisman
U. of California, San Diego, USA
Wolfgang von Rüden CERN, Switzerland
Christine Borgman U. of California, Los Angeles, USA
Daniel Atkins
Text
University of Michigan, USA
Alexander Szalay
Johns Hopkins University, USA
Julia Lane
US National Science Foundation
Nathan Bindoff
University of Tasmania, Australia
Stuart Feldman Google, USA
Han Wensink ARGOSS, The Netherlands
Jayanth Paraki
Omega Associates, India
Luciano Milanesi National Research Council, Italy
International Panel for 2009 Review of the RCUK e-Science Program
Please Note: Send any comments or corrections you would like considered for the final version of the report to atkins@umich.edu NOT LATER THAN February 13, 2010 The slides for this presentation will be made available in pdf on the EPSRC website. If you want Mac Keynote of MS Powerpoint versions contact me via email.
Background and Context What we are talking about today is very important.
Definition should likely now be made more agnostic wrt technology
Original UK Definition of e-science by Sir John Taylor
Sir John Taylor Prof. Dan Atkins
Cyberinfrastructure Genealogy & Movement Collaboratories KDI PACI HPCC Digital Libraries GRIDS
ITR E-science
2nd Edition www.mkp.com/grid2 Cyberscience
D. E. Atkins • University of Michigan • atkins@umich.edu
IT & Future of Higher Education
NSF Blue Ribbon Advisory Panel on Cyberinfrastructure
Daniel E. Atkins, Chair University of Michigan Kelvin K. Droegemeier University of Oklahoma Stuart I. Feldman IBM Hector Garcia-Molina Stanford University Michael L. Klein University of Pennsylvania David G. Messerschmitt University of California at Berkeley Paul Messina California Institute of Technology Jeremiah P. Ostriker Princeton University Margaret H. Wright New York University
“a new age has dawned in scientific and engineering research, pushed by continuing progress in computing, information, and communication technology, and pulled by the expanding complexity, scope, and scale of today’s challenges. The capacity of this technology has crossed thresholds that now make possible a comprehensive “cyberinfrastructure” on which to build new types of scientific and engineering knowledge environments and organizations and to pursue research in new ways and with increased efficacy.”
http://www.nsf.gov/oci
Organisms
10 10 10
Cell s Biopolymers
10
0
10
DNA replication Ab initio Quantum Chemistry
6
Enzyme Mechanisms Protein Folding
Empirical force field Molecular Dynamics
3
Homologybased Protein modeling
First Principles Molecular Dynamics
0
-15
10
The accompanying requirement for multi-disciplinary, multi-investigator, multi-institutional approach (often international in scope).
Evolutionary Processes
Cell signalling
6
3
10
10
Electrostatic continuum models
0
10
Ecosystems and Epidemiology
Organ function
6
3
10
Discrete Automata models
Finite element models
0
10
10
The Complexity of Biosystems
6
3
10
Atoms
The inherent complexity, multi-scale, and multi-science nature of today’s frontier science challenges.
Number Scale (over size scale from Angstroms to Km)
e-science (research enabled by e-infrastructure/ICT) is increasingly essential for meeting 21st century challenges in scientific discovery and learning
10-12
10-9
10-6
10-3
100
Time Scale (seconds)
103
106
109
Geologic & Evolutionary Timescales
The high data intensity and heterogeneity from simulations, digital instruments, sensor nets, and observatories. 7$18,#)'&,5#'3$8,#5$)$/,)/
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The increased scale and value of data and demand for semantic federation, active curation and long-term preservation of access.
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And the need to engage more students in high quality, authentic, passion-building science and engineering education.
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e-science
CI-enabled science
Virtual Environments
Data & High Performance Visualization/ Interaction Computing Learning & Work Force Needs & Opportunities
Note: Many other reports on discipline-specific visions of and drivers for e-Science are available at www.nsf.gov/oci
a new vision for Science Global challenges with high societal impact Data deluge… wet-labs versus virtual-labs Improved scientific process Cross-disciplinarity
networking grids instrumentation computing data curation…
revolution in science & engineering, research & education
value added of distributed collaborative research (virtual communities)
Application pull
Technology push
Virtual Research Communities
•••
building Science through collaboration Research Communities common goals, complementary and shared information, tools and knowledge, awareness of research protocols, effective means of collaboration, interest in being part of the community
Virtual research from empirical, experimental, theoretical and computational science… to intensive use of data… abstraction… models… simulation… e-Science
Virtual communities no geographical, time or institutional boundaries
Globalisation Global challenges, global dimension, win-win situation
•••
ICT for Science: e-Infrastructures Connecting the finest minds Sharing and federating the best scientific resources Building global virtual communities Weather Forecast community
Biomedics
Astrophysics
community
community
Sharing and federating scientific data Sharing computers, instruments and applications Linking at the speed of the light
.......
â&#x20AC;˘â&#x20AC;˘â&#x20AC;˘
http://research.microsoft.com/en-us/collaboration/fourthparadigm/
The Fourth Paradigm: Data-Intensive Scientific Discovery
Opportunities for Research and NIH by Francis S. Collins, Director
POLICYFORUM RESEARCH AGENDA
Opportunities for Research and NIH Francis S. Collins
The power of the molecular approach to health and disease has steadily gained momentum over the past several decades and is now poised to catalyze a revolution in medicine. The foundation of success in biomedical research has always been, and no doubt will continue to be, the creative insights of individual
High-Throughput Technologies
In the past, most biomedical basic science projects required investigators to limit their scope to a single aspect of cell biology or physiology. The revolution now sweeping the field is the ability to be comprehensive—for example, to define all of the genes of the human or a model organism, all of the human proteins and their structures, all of the common variations in the genome, all of the major pathways for signal transduction in the cell, all of the patterns of gene expression in the brain, all of the steps involved in early development, or all of the components of the immune system. Further development of technologies in areas such as DNA sequencing, imaging, nanotechnology, proteomics, metabolomics, small-molecule screening, and RNA interference are ripe for aggressive investment. Furthermore, these technologies will spur the production of massive and complex data sets and will require major investments in computational biology. As one example, the Cancer Genome Atlas (1) is now poised to derive comprehen-
sive information about the genetic underpinnings of 20 major tumor types. This information will likely force a complete revision of diagnostic categories in cancer and will usher in an era where abnormal pathways in specific tumors will be matched with the known targets of existing therapeutics. Another example is the opportunity to understand how interactions between ourselves and the microbes that live on us and in us (the “microbiome”) can influence health and disease (2). Translational Medicine
Critics have complained in the past that NIH is too slow to translate basic discoveries into new diagnostic and treatment advances in the clinic. Some of that criticism may have been deserved, but often the pathway from molecular insight to therapeutic benefit was just not discernible. For many disorders, that is now changing. Three major factors have contributed to this: (i) the discovery of the fundamental basis of hundreds of diseases has advanced dramatically; (ii) with support from the NIH Roadmap, academic investigators supported by NIH now have access to resources to enable them to convert fundamental observations into assays that can be used to screen hundreds of thousands of candidates for drug development; (iii) public-private partnerships are being more widely embraced in the drugdevelopment pipeline to enable biotech and pharmaceutical companies to pick up promising compounds that have been effectively “de-risked” by academic investigators and to
Interdisciplinary, team-based e-Science
investigator-initiated projects and large-scale community resource programs. For both individual and large-scale efforts, it is appropriate to identify areas of particular promise. Here are five such areas that are ripe for major advances that could reap substantial downstream benefits.
National Institutes of Health, Bethesda, MD 20892, USA. E-mail: collinsf@mail.nih.gov
36
bring them to clinical trials and U.S. Food and Drug Administration (FDA) approval. As one example, the NIH Therapeutics for Rare and Neglected Diseases (TRND) (3) program will allow certain promising compounds to be taken through the preclinical phase by NIH, in an open environment where the world’s experts on the disease can be involved. Furthermore, as information about common diseases increases, many are being resolved into distinct molecular subsets, and so the TRND model will be even more widely applicable. The first human protocol (for spinal cord injury) involving human embryonic stem cells (hESCs) was approved by the FDA in 2009, and the opening up of federal support for hESC research will bring many investigators into this field. The capability of transforming human skin fibroblasts and other cells into induced pluripotent stem cells (iPSCs) opens up a powerful strategy for therapeutic replacement of damaged or abnormal tissues without the risk of transplant rejection (4–6). Although much work remains to be done to investigate possible risks, the iPSC approach stands as one of the most breathtaking advances of the last several years, and every effort should be made to pursue the basic and therapeutic implications with maximum speed. Benefiting Health Care Reform
U.S. expenditures on health care now represent 17% of our Gross Domestic Product, are continuing to grow, and are excessive as a percentage of per capita gross income com-
1 JANUARY 2010 VOL 327 SCIENCE www.sciencemag.org Published by AAAS
Downloaded from www.sciencemag.org on January 7, 2010
But increasingly those investigators are working in teams, accelerated by interdisciplinary approaches and empowered by open access to tools, databases, and technologies, so a careful balance is needed between
CREDITS: (LEFT TO RIGHT) ODOM AND O’HALLORAN/NORTHWESTERN UNIVERSITY; LINDA BARTLETT/NCI, NIH; BILL BRANSON/NCI,NIH; NASA; BILL BRANSON/NIDCR, NIH
T
he mission of the National Institutes of Health (NIH) is science in pursuit of fundamental knowledge about the nature and behavior of living systems and the application of that knowledge to extend healthy life and to reduce the burdens of illness and disability. The power of the molecular approach to health and disease has steadily gained momentum over the past several decades and is now poised to catalyze a revolution in medicine. The foundation of success in biomedical research has always been, and no doubt will continue to be, the creative insights of individual investigators. But increasingly those investigators are working in teams, accelerated by interdisciplinary approaches and empowered by open access to tools, databases, and technologies, so a careful balance is needed between investigator-initiated projects and large-scale community resource programs. For both individual and large-scale efforts, it is appropriate to identify areas of particular promise. Here are five such areas that are ripe for major advances that could reap substantial downstream benefits.
investigators.
1 Jan 2010, vol. 326 SCIENCE www.sciencemag.org
The promise of fundamental advances in diagnosis, prevention, and treatment of disease has never been greater.
1 Jan 2010, vol. 326 SCIENCE www.sciencemag.org
Five Special Opportunities for Biomedical Research by Francis S. Collins, Director US NIH High-throughput Technologies for comprehensive studies The revolution now sweeping the field is the ability to be comprehensiveâ&#x20AC;&#x201D;for example, to define all of the genes
of the human or a model organism, all of the human proteins and their structures, all of the common variations in the genome, all of the major pathways for signal transduction in the cell, all of the patterns of gene expression in the brain, all of the steps involved in early development, or all of the components of the immune system.
Translational Medicine Making the pathway from molecular insight to therapeutic benefit more discernible
Focusing More on Global Health It is also critical to go beyond the focus on the â&#x20AC;&#x153;big threeâ&#x20AC;? diseases to neglected tropical diseases of low-income countries that contribute to staggering levels of morbidity and mortality
Benefiting Health Care Reform Comparative effectiveness research Prevention and personalized medicine Health disparities research Pharmacogenomics Health research economics
Reinvigorating and Empowering the Biomedical Research Community to be More Innovative Emphasis on innovation Robust training programs for next generation of basic and clinical scientists
e-Infrastructure and e-Science as a Platform for Meeting Grand Challenges Digital economy
Nanoscale: engineering to app
Aging research: lifelong health & wellbeing
Global Security
Living with environmental change
Energy
Grand Challenge Research Initiatives
Further Opportunities??
e-research e-urgent response e-science e-arts & humanities e-infrastructure (shared & specific)
e-learning
The Research University in the Digital Age
e-Science
e-Humanities & Arts e-Learning e-Development
This report was in part motivated by and highly leverages e-science and e-learning research
Transforming American Education: Learning Powered by Technology Soon to be released Report to the President and Congress from the U.S. Department of Education
GLOBAL
Transparency
TECHNICAL
Embodiment of standards Built on an installed base
Reach & scope
e-infrastructure has history and theory
Links with conventions of practice
SOCIAL
Learned as part of membership
Becomes visible upon Embeddedness breakdown
http://deepblue.lib.umich.edu/handle/2027.42/49353
LOCAL
UK e-infrastructure for Science and Innovation
sets out the requirements for a national e-infrastructure to help ensure the UK maintains and indeed enhances its global standing in science and innovation in an increasingly competitive world.
Executive Summary The growth of the UK’s knowledge-based economy depends significantly upon the continued support of the research community and in particular its activities to engage with industry and to apply its world-leading innovations to commercial use. A national e-infrastructure for research provides a vital foundation for the UK’s science base, supporting not only rapidly advancing technological developments, but also the increasing possibilities for knowledge transfer and the creation of wealth. http://www.nesc.ac.uk/documents/OSI/index.html
Six Working Groups: Data & information creation • Preservation & curation • Search & navigation • Virtual research communities • Networks, compute and data storage • Authentication, authorisation, accounting, middleware, and digital rights management
Background on Report and Process of Its Creation
Terms of Reference: Role of Review Panel Assess the impact of the programme on research areas nationally and internationally; on broader wealth creation and quality of life; and on e-Science itself; Assess and compare the quality of the UK research base in e-Science with the rest of the world via triangulation of data, panel and community perception; Comment on the added value of this programme; Present findings and recommendations about the strength, weakness and opportunities for the future to the research community and Councils.
Evidence Framework
200 Page Evidence Documentation Provided by RCUK
Review Week in Oxford
Documentation Requested by Panel Presentations, Conversations, Observation Panel’s collective expert judgement
Context,Vision, Opportunity Space
Findings
+ Distributed group writing and discussions
Recommendations
Draft Panel Public Report + Town Hall Meeting
Feedback
Final Report
Next Steps
e-Infrastructure Report
Panel’s Concept of the Process and Expectations
e-Science Evidence Framework (FOGIES) F - What are the future opportunities for UK e-Science? O - Other observations not included in the above. G - How does UK e-Science activity compare globally? I - What has been the impact (accomplished and potential) of the UK e- Science Programme? E - Did the UK e-Science Programme build a Platform which enables e- Science tools, infrastructure and practises to become incorporated into mainstream research in the UK?
S - How did the Programme Strategy (having a Core and individual Research Council
Programmes, developing tools and applications in parallel) affect the outputs from UK e-Science?
Panel Explore and Integrate Matrix E Feldman Foster Wensink
G Milanesi Ellisman Bindoff
I Borgman Ynnerman Heermann
F Heck Szalay Tackley
S Lane Paraki von R端den
O Atkins
Project Presentations Field Trips Evidence Documents Conversations Panel Knowledge Other Sources
At every opportunity we have in our group private sessions (including after some meals), we will report-out findings of the day and the designate teams will mine these reports for findings and recommendations relevant to their topic in the (E-GIFSO OR FOGIES) evidence framework. Please be proactive in getting your input to the appropriate teams.
Findings and Recommendations
The UK has created a â&#x20AC;&#x153;jewelâ&#x20AC;? -- a pioneering, vital activity of enormous strategic importance to the pursuit of scientific knowledge and the support of allied learning. The UK e-Science Programme is in a world-leading position.
Golden Jubilee Diamond
Investments are already empowering significant contributions in the UK and beyond. The UK must decide whether to create the necessary combination of financial, organisational, and policy commitments to capitalise on their prior investments,. e-Science is an organic, emergent process requiring ongoing, coordinated investment from multiple funders and coordinated action by multiple research and infrastructure communities. It is both an enabler of research and an object of research, The UK should continue to nurture a robust infrastructure that couples and balance research, application development, and training processes. None of this is easy, but done well could achieve enormous reward.
The UK has created a â&#x20AC;&#x153;jewelâ&#x20AC;? -- a pioneering, vital activity of enormous strategic importance to the pursuit of scientific knowledge and the support of allied learning.
Twinkling in the sky is a diamond star of 10 billion trillion trillion carats, astronomers have discovered. The diamond star completely outclasses the largest diamond on Earth, the 546-carat Golden Jubilee...
http://news.bbc.co.uk/2/hi/sci/tech/3492919.stm
SIGNIFICANT FINDINGS: STRENGTHS (1) Produced competent people for both academia and industry. Created and enriched interdisciplinary collaborations (faculty & students) that are increasingly important for progress at the frontiers of scientific discovery. Created interdisciplinary e-science doctoral training programs. Stimulated industry up-take of e-science. Situated the UK reputation in e-science among the top nations. Accelerated the penetration of e-science capability in UK and Europe. Contributed significantly to establishing standards and tools for national and european consortial networked science projects.
SIGNIFICANT FINDINGS: STRENGTHS (2) Stimulated university leaders to establish e-science buildings and organizations on campus. Promoted recognition of digital data as an asset and the need for greater attention to its stewardship. But still lacking adequate repository capacity and the trained human capacity that is needed.
Supported directly and indirectly scientific international collaborations. But very little (any?) participation by developing countries.
Enabled science not otherwise possible. Initiated a national framework for sharing large-scale resources that will be increasingly important to both large and small scale research and education.
SIGNIFICANT FINDINGS: STRENGTHS (3) Supported important work in the humanities and social sciences. Promoted increasing standardization for data interoperability and aggregation. Promoted interdisciplinary work and provided mechanisms to link projects to projects on an on going way. (All-hands Meetings; community building activities) Leveraged investments from other sources (regional, industrial, international) Stimulated local/regional economies. Accelerated the productivity of researchers and science processes. Accomplished some knowledge/technology transfer but there could be more.
SIGNIFICANT FINDINGS: WEAKNESS (1) Too early and rapid reduction of core funding and high level leadership, resulting in Sense of abandonment by some researchers and career shift away from escience Failure to reap the benefits of prior investments. The time constants for real transformative impact and significant competitive advantage is decades.
Reduced momentum of an important movement in which UK established a global leadership role Perception that RCs don't appreciate the strategic importance of e-science and the special handling that it still needs
SIGNIFICANT FINDINGS: WEAKNESS (2) Lack of models for sustaining/maintaining software, platform/infrastructure operations, and data resources e-infrastructure providers are being forced to compete for research funding (rather than targeted infrastructure/facilities funding) every two years
Missed opportunities to transfer successful software tools/systems and best practices to other fields. Lack of regularized processes and organizations to do so.
SIGNIFICANT FINDINGS: WEAKNESS (3) Lack of adequate structure, leadership, and resources to promote constructive interplay and achieving balance (1) between shared/generic and specific einfrastructure and (2) between e-science core and disciplinary research. This situation raises barriers to interdisciplinary work; to developing and exploiting common infrastructure, middleware, tools, systems; and to interoperability between disciplines, projects, platforms and shared use of resource
Overly focused on computational "grid" platforms Good fit to physics but not necessarily all other domains. But there are variations in what "grid" means. (computational, data, all types of resources)
Knowledge transfer (KT) potential higher than was actually achieved. Need more systematic and staffed KT processes.
SIGNIFICANT FINDINGS: WEAKNESS (4) Shortage of women participants (as judged by data in evidence document and gender balance during review) Gaps in the e-science program conceptualization. sensor networks usability, human-computer-interaction understanding of social/behaviors barriers to technology mediate science collaboration and ways to design systems and processes to reduce barriers
Crossing the Chasm â&#x20AC;&#x201C; Modified
e-Science Prog.
Recommendations for the future within a 5 year window, informed by a 10 year vision
Next 5 Years
From Research to Sustainability Maintain critical-size centers already established Partnership with academic institutions already committed to e-Science Dramatically expand (x10 or more) involvement Both researchers and users (industry, society) Provide mid-term career paths for current e-science personnel Use existing mechanisms like 5-year UKRC fellowships Build stronger ties/bridges to the HPC community (e-Science should include simulation, modelling, prediction, and data mining activities.) Durham cosmology simulations, Oxford effort Develop increasingly shared infrastructure that is reliable, mature and sustainable Software is a sustainable facility, and the capital investment Hardware is becoming the consumable
Next 5 Years
Sustain and Grow the Emerging Community
Strong national leadership, stable cross-council coordination with real authority. Community building and training National and regional e-Science Centers, All Hands Meetings Summer schools, Doctoral Training Centers Systematic dissemination of best practice Knowledge transfer organization Explicitly reward â&#x20AC;&#x153;re-useâ&#x20AC;? of existing components Emphasise packaged and hosted service-based e-Science Keep up with emerging/evolving new technologies Shared support center, explore clouds, GPUs, etc
Next 10 Years Evolutionary Challenges Transformations in different disciplines will not happen all at the same time HEP … astro … genomics … environment … health … (most disciplines) Continuous evolution in underlying technologies Grid … SOA.. cloud … ??? Innovative “sensors” tied to computational tools (sequencing, gene chips, remote sensing, medical imaging, sensing data for social sciences) Stable hierarchical distribution of resources, with large national or international scale facilities at the top Group … University … Regional … National … International Sanger, EBI, IVOA, LHC Tiers (within and across disciplines)
Next 10 Years Data Challenges Data sets: “new kinds of instruments” LHC, Sanger, Oceanography, AstroGrid, Medical records, 4th paradigm Self-amplification of data The easier to collect and analyze large data, the more people collect… Data doubling times go from 1 year to 3-4 months Simulations larger and in more disciplines Heart, brain, cell, astro, LHC, social More pressure on the infrastructure Data growth beyond any current imagination Many 100s of PB in 10 years Capacity issues hard even on national scale, impossible locally Not only technical but a socio-political issue
Next 10 Years Sociological Challenges Cultural changes cause e-Science to become “socially” accepted in more and more disciplines (to stay competitive) Many authors, data sharing, novel kinds of contributions e-Science buildings and departments are first signs of wider acceptance, but still small fraction of papers impacted e-Science (“computational”) thinking becomes an integral part of the everyday curriculum across all disciplines 7 Doctoral Training Centers already E-Science will become mainstream when integrated into the education framework as a whole Substantial fraction of the research community exposed to e-Science Biggest changes will happen through demographics (“progress one grave at a time”)
A Dozen Recommendations
1. Structure and Leadership Continue to treat e-Science as a designated strategic initiative spanning all Research Councils and having ongoing designated funding. Provide high-quality dedicated leadership for a strategic e-Science Programme, and provide the leader with adequate authority at a high enough level and with resources to catalyse real synergy and co-investment. Establish more systematic, ongoing, coordinated investments in the infrastructure, development, and adoption of e-Science at even a higher level than across Research Councils. This higher level coordination could include several components of BIS: the Research Councils, JISC, the Technology Strategy Board, and the funders of higher education and facilities. e-Science Programme leadership should also seek coordination with e-Science-related funding from outside of government including the Wellcome Trust, the EU, the US NSF, and others.
Balance of Funding Regions Specific e-infrastructure Assets Intellectual Assets 1. Domain 2. Domain Specifc Specific Research e-Infrastructure Programs e-science Programs Infrastructure management Research structure 3. Collaborative, 4. Shared (multi(interdisciplinary) domain) eResearch Infrastructure Programs Programs Shared/Generic Based on work by Suzi Iacono & Diana Rhoten at NSF
2. Industry-academic collaborations Establish more systematic and better supported mechanisms, including targeted funding, to nurture collaboration and bi-directional knowledge transfer between academia and industry in the creation, provisioning, and application of e-Science. There are multiple goals here: (1) accelerate transfer of research outputs to beneficial innovation; (2) enlist industry in the creation and provisioning of the e-infrastructure platform for e-Science; and (3) to help industry adopt and tailor best practices and services from eScience to enhance their own productivity.
Recent novel examples of government, industry, academia partnerships on e-Science research http://www.networkworld.com/community/ node/27219
http://www.nsf.gov/news/news_summ.jsp? cntn_id=116336&org=NSF&from=news
http://www.nytimes.com/2010/02/05/science/ 05cloud.html
3. RCUK e-Science Centre Network Sustain and strengthen the RCUK network of e-Science Centres. Challenge and support these Centres to both serve regional constituencies and be members of a network for the common good. Establish the remit of various centres in a way that stresses complementary expertise and sharing. (give and take) Emphasise and assess expectations that the Centres be proactive in engaging with each other, with UK industry, and with other countries. Establish polices for sustaining this network but in a way that periodically (e.g. every 5 years) requires re-competition to enable new entries into the field and to retire less effective activities.
4. Sustaining advanced e-infrastructure Sustain the operational e-infrastructure for e-Science created to the present. Informed by an ongoing review of future needs, evolve it to: (1) higher capacity; (2) more complete function; and (3) leading-edge, distributed system architecture. In particular the UK needs to invest in e-infrastructure in ways that (1) anticipates the continuing exponential growth in scientific data and the increasing ability to extract knowledge from it; (2) provides the UK research community access to petascale-level computing and anticipates the future needs for access to exascale; (3) continues to build on and strengthen the grid model of distributed computing, but also explores the adoption of emerging models of cloud computing for research.
5. Supporting complementary personnel roles Recognise in programme calls and funding policies that there are people in several complementary roles that need to be funded and rewarded appropriately. There are people (1) seeking to innovate in the application of e-Science method to their field; (2) seeking to innovate better e-Science methods, practises, and services; (3) who design and build reliable production-grade systems; and (4) who administer and operate the supporting e-infrastructure. Need to better define and reward new professional identities and job types within academia that span role 2 and 3 above.
How do we enhance a culture of mutually-beneficial balanced participation and synergy between e-infrastructure provisioning, research application, and e-science/e-infrastructure innovation ? Transformative Application to enhance research, learning, and societal engagement.
Provisioning - to create, deploy and operate advanced e-infrastructure Borromean Ring: The three rings taken together are inseparable, but remove any one ring and the other two fall apart. See www.liv.ac.uk/ ~spmr02/rings/
R&D to provide technical and social enhancements in future e-science environments
6. Sharing for cost- and scienceeffectiveness Continue funding policies that strongly encourage or require the creation and adoption of shared e-infrastructure. Important not only from a cost-effective, efficient-energy use, and environmental-impact perspective, but also for facilitating intellectual interoperability between disciplines, institutions, facilities, and data resources essential for grand-challenge research. Since scientific research is intrinsically global, place great emphasis on creating UK e-infrastructure that harmonises with the e-infrastructure in other countries.
7. Role for arts and humanities Encourage and support even more participation of the arts and humanities research communities in the e-Science program. (We saw some excellent beginnings in our review.) Arts and humanities are poised to achieve large benefit from e-science methods and infrastructure as the human record becomes increasingly digitised and multimedia.
8. Role for social sciences Encourage and support even greater leadership by the social science research community in the adoption of e-Science methods particularly, for example, given capabilities to explore enormous data sets, analyse social networks, and explore very complex systems through simulation and modelling. The social science community should also be encouraged to contribute more to deeper understanding of more principled ways to design effective virtual research environments, collaboratories, (four-quadrant organisations).
9. Crossing the chasm; refreshing innovation Develop a dual strategy that both (1) accelerates the adoption of eScience methods in the “mainstream market” of researchers and (2) refreshes the investments in the “early market” to produce the next wave of innovation in e-Science services and application. Goal (1) involves training and tailoring current services to more specific needs of disciplinary and interdisciplinary communities. This process needs an integrated formative assessment activity that includes continuous monitoring and that helps ground and inform the activities of “early market” communities and supports participatory design methods.
10. Data stewardship at enormous scale Continue the strong focus on creating practices and services for appraisal, curation, federation, and long-term access to scientific data. Complement or broaden the activities of the Digital Curation Centre with the creation of coordinated and sustained production services for curation and stewardship of scientific data. Consider a highly centralised, large data centre model for storing the information and preserving the bits, together with a distributed model for curation by disciplinary specialists. Seek and promote international cooperation.
11. Openness as a general policy Establish policies for openness: open-source code, open data and meta-data, and open courseware. Encourage reuse. "Open" Resources for Research and Learning
Dimensions
Intellectual access
Technical access
Monetary payment or not
Attribution
Anonymous or not
IP terms and conditions for use
Extent and method of credentialling/ warranting
Default copyright
Creative Commons Licenses
Software (open source)
Commercial or not
Derivative works or not
Share Alike
Organizational form for collaborative creation & use/ remix
Courseware
Type of objects/ collection
Online laboratories
See http:// creativecommons.org/
Digital capture of lectures
Venues/tools for participatory learning
Journal Publications
Data
Raw data
Meta data
Analysis tools
12. Towards functionally complete, fourquadrant, research environments Pursue capacity for collaborative, international, interdisciplinary team science to occur routinely in “functionally complete, four-quadrant environments” built upon einfrastructure. “A four-quadrant environment” refers to a blended virtual-physical environment in which the activities of a group can flow easily between all four quadrants in a 2-by-2 matrix with same versus different for the two dimensions of both time and place. It subsumes the concept of virtual research environment. “Functionally complete” means that the environment supports access to all the people, the information and data services, the observatories and facilities, the computational services, and the collaboration and communication services necessary for a scientific team (or more generally, a community of practice) to carry out its work.
Four Quadrant Organizations (virtual organizations) offer additional modes of interaction between People, Information, and Facilities Same
Time
University of Michigan
Same Different
Geographic Place
(synchronous)
Different
(asynchronous)
P: Physical mtgs I: Print-on-paper books, journals F: Wet labs, studios, shops
P: Shared physical artifact I: Library reserve F: Time-shared physical labs, ...
P: AV conference I: Web search F: Online instruments
P: Email I: Knowbots F: Autonomous observatories
Physical + Virtual, Not Physical vs. Virtual
P: people, I: information, F: facilities, instruments
Daniel E. Atkins atkins@umich.edu
Need to discover how to best map collaborative workflows onto various paths through these collaboration states.
Same Different
Geographic Place
Same
University of Michigan
Time
Different
(synchronous)
(asynchronous)
P: Physical mtgs I: Print-on-paper books, journals F: Physical labs, studios, shops
P: Shared physical artifact I: Digital libraries F: Time-shared physical labs, ...
P: AV conference I: Web search F: Online instruments
P: Email I: Knowbots F: Autonomous observatories
P: people, I: information, F: facilities, instruments
Daniel E. Atkins atkins@umich.edu
Beyond Being There: A Blueprint for Advancing the Design, Development, and Evaluation of Virtual Organizations Available at: www.ci.uchicago.edu/ events/VirtOrg2008/
Use e-Science as a Pathway to New Forms of High Performance Collaboration for Discovery and Learning
Creating a Transformative e-Science Programme is a Complex Balancing Act also
Creating a Transformative e-Science Programme is a Complex Balancing Act
e-Science
Discussion & Questions