Future Profiles of e-Research


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E-Scienceand e-research: how can we understand their development and forecast their futures? Paper given to major e-Science conference in 2008.

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Future Profiles of e-Research

  1. 1. <ul><li>Future Profiles of e-Research </li></ul>Ian Miles Manchester Institute of Innovation Research Manchester Business School University of Manchester Ian.Miles@mbs.ac.uk &quot;Crossing Boundaries&quot; ALL HANDS MEETING 2008 e-Science UK 8-11 September, Edinburgh, UK JISC
  2. 2. WHAT SORT OF BEAST IS e-RESEARCH? Using e-infrastructure Diffusion: No of users (or: intensity of use; Range of applications…) Product cycle: “ maturity” of product Pioneers Laggards Take-off into mass acceptance: less “expert” users Changing Communities: types of user, of network Product/service designs in flux: Growing focus on functionality, supply efficiency, commoditisation Differentiation, bottlenecks, next big thing Changing Services and Impacts: types and modes of application Time What timescale: years? Decades?
  3. 3. WHERE ARE WE WITH e-RESEARCH? Using e-infrastructure Time Diffusion: No of users (or: intensity of use; Range of applications…) Product cycle: “ maturity” of product 1) Are we just at the beginning? How far will diffusion go? Is this something really new? Can we extrapolate from pioneers? 2) Is take-off underway, has it happened? Are communities established and expanding? Have usage patterns stabilised? What timescale: years? Decades? 3) Are things really pretty mature – no prospect of radical change, because requisite facilities well-diffused?
  4. 4. WHERE ARE WE WITH e-RESEARCH has… Using e-infrastructure Implications for the ways in which we can think about sorts of community and practice, sorts of application and effect, whether we expect change to be incremental or (potentially) revolutionary, how problems and opportunities may be identified and addressed What timescale: years? Decades? Time Diffusion: No of users (or: intensity of use; Range of applications…) Product cycle: “ maturity” of product
  5. 5. Two other thoughts about these trajectories - 1 Envelope Curves What timescale: years? Decades? Time Diffusion: No of users (or: intensity of use; Range of applications…) Product cycle: “ maturity” of product We can expect many specific technological trajectories Uptake data for a specific application will not tell whole story – nor will evidence on use, problems, etc.
  6. 6. The other thought about these trajectories Trajectory of Hype Technology Trigger Peak of . Inflated .. Expectations Trough of Disillusionment Plateau of Productivity Slope of Enlightenment Time Optimism/ excitement about the service or technology Political &/or business support? Source: Gartner Group , who place various Technologies on this; according to Wolfgang Gentsch, in 2006 they put Grid Computing here and tera-architectures here What timescale: years? Decades?
  7. 7. In Forsociety, we explored scenarios for e-Infrastructure <ul><li>ForSociety; http://www.eranet-forsociety.net/ForSociety/index.html </li></ul>What is ForSociety ForSociety ERA-Net is a sustainable and dynamic network, where national foresight programme managers co-ordinate their activities and - on the basis of shared knowledge on relevant issues, methodologies, legal and financial frameworks - regularly develop and implement efficient trans-national foresight programmes that significantly enrich both the national and the European research and innovation systems. Future dialogues : develop understanding of areas where Foresight may be used to assist transnational cooperation: e.g. * The Future of Nutrition – Production, Consumption, Innovation; * European Energy Future; * Electronic Infrastructures : from ICT to collaborative science and innovation networks; * Towards a transnational foresight analysis task force for Agronomic Knowledge in S&T; * The dynamics of the national and regional research & innovation systems (RIS) and the emergence of the European Research Area (ERA); * The future of multinational innovation clusters in Biotechnology and Life Sciences; * Future dialogue on European infrastructures - Assess tasks for an integrated Europe-wide foresight network on infrastructures
  8. 8. ForSociety future dialogue <ul><li>Small group met and explored alternative scenarios for e-infrastructure </li></ul><ul><li>Identified drivers and issues </li></ul><ul><li>Explored 4 scenarios using “archetype” method – rather than 2*2 driver method </li></ul><ul><li>Avoiding Business as usual, asked participants to work on identifying PLAUSIBLE paths of development that would be better then, worse than, or different from expectations </li></ul><ul><li>Uncertainty about the field demonstrated by the results that (a) ALL paths of development were seen as possible outcomes (we did not take this out to wider rating of “likelihood” or “extent of realisation”); (b) Most interest was generated by the futures “out there, where the bus doesn’t run”, which were felt to be particularly challenging – and liable to be realised in one or other way! </li></ul>
  9. 9. Future Dialogue on e-Infrastructures (FORSOCIETY 2006-7) <ul><li>Scenarios </li></ul><ul><li>“ Elephant” - Positive development, rapid (faster than expected) uptake: Research-dedicated e-I </li></ul><ul><li>“ Tiger”  “Utopia” - Positive development, rapid uptake: multipurpose, public-private e-infrastructures </li></ul><ul><li>“ Panther”/”Snake”  “Interesting times” - Substantially different path of development </li></ul><ul><li>Donkey - Disastrous (much slower than expected) development </li></ul>OSI TCP/IP Linux Internet bubble
  10. 10. Scenario 1 – Elephant - The main theme <ul><li>Seamless access to the e-Infrastructure i.e. integrated resources (networking, computing, data, etc.) and services offered to the scientific users </li></ul><ul><ul><li>Users should be satisfied (easy access) </li></ul></ul><ul><ul><li>Without the providers’ frustration </li></ul></ul>Drivers <ul><li>Grand challenge applications drive the need for seamless integration </li></ul><ul><li>EC has a clear integrating role </li></ul><ul><li>Seamless integration provides equal opportunities in using the e-Infrastructures </li></ul>
  11. 11. Scenario 1 – Elephant - Issues arising, problems <ul><li>Positive features (Strengthening Science and Education in Europe) need to be offset by Risks: </li></ul><ul><ul><li>Risk to privacy: Scientists’ ambitions vs. users/beneficiary privacy (e.g. Medical patient records) </li></ul></ul><ul><ul><li>Risk of over-satisfaction / sustainability </li></ul></ul><ul><ul><ul><li>Victims of our own success; Who pays at the end? </li></ul></ul></ul><ul><ul><li>Change of social behavior, need for new norms: </li></ul></ul><ul><ul><ul><li>Now: Reading e-mails when someone presents, getting mobile phone calls during the meetings.. Future: Submit job through the mobile phone and get results while being … </li></ul></ul></ul><ul><ul><li>Health hazards? </li></ul></ul><ul><ul><li>Increasing digital divide? Incl specific Countries or applications being left behind. </li></ul></ul>Open Questions <ul><li>Single, general purpose eInfrastructure or several interconnected application/discipline-specific eIs? </li></ul><ul><li>User empowered or not? </li></ul><ul><li>Virtualisation everywhere? </li></ul>
  12. 12. Scenario 2 – Tiger - The main theme <ul><li>For eI providers’: safe investments (equipment will have long-term users). </li></ul><ul><li>Focus on core research, industry collaboration very easy (same standards, both academia and industry have healthy market for computing services). </li></ul><ul><li>Larger array of services available, easier to launch and access services through common standards. New value added services. </li></ul><ul><li>PC will disappear? </li></ul><ul><li>Globalisation </li></ul><ul><li>Grand challenge applications drive the need for seamless integration which provides equal opportunities in using the e-Infrastructures </li></ul><ul><li>EC has a clear integrating role </li></ul><ul><li>• Shared commercial interests (incl. research community) and understanding. Immediacy, low cost IT services. Driven by profit motive where both large and small companies see advantages for business efficiency, etc. </li></ul><ul><li>• Commodification of services as academics see benefits; Big firms are prepared to go beyond traditional data centres (outsourcing these data centres to the grid); SMEs have access to IT power on “pay per use basis” </li></ul><ul><li>• Economies of scale important: issues of security and quality solved in widely acceptable ways. Trust in and desire for advanced technology </li></ul><ul><li>• Low cost specialisation of services - “Agent-auction mechanism”. </li></ul>Drivers
  13. 13. Scenario 2 – Tiger – More info <ul><li>Storylines: </li></ul><ul><li>• Bootstrap as we did with Internet and web, from R&D community to wider use </li></ul><ul><li>• The first limited applications will be public/private initiatives </li></ul><ul><li>• Self-propelling development: others want to emulate; network externalities. </li></ul><ul><li>• Commodification and de facto standards for a second layer of services; control of usage, payments and micropayments </li></ul><ul><li>Virtues – Problems: </li></ul><ul><li>• Scenario seen as having mostly virtues, but:. </li></ul><ul><li>• Privacy? </li></ul><ul><li>• Legal problems? </li></ul><ul><li>Critical factors: </li></ul><ul><li>Open de facto standards for metering and secure billing for services. </li></ul><ul><li>International resolution of legal problems like IPR, patents, licensing </li></ul><ul><li>Avoidance of national hegemony: control of underlying infrastructure; protectionism as important parameters </li></ul><ul><li>Barriers like protectionism, security and trust… </li></ul>
  14. 14. Scenario 3 – Panther - The main theme <ul><li>Traditional infrastructure providers become irrelevant. </li></ul><ul><li>Research might be stuck with “obsolete technologies” </li></ul><ul><li>From society perspective: opportunity, crisis. </li></ul>Drivers <ul><li>Open and difficult scenario with several possible routes to it </li></ul><ul><li>Much in common with Tiger, but stress on new factors influencing economies of scale (technical innovation, large emerging countries) </li></ul><ul><li>Mixed model with public & private sector participation - but i ndustry has superior momentum that forces public sector to apply it. New classes of research(er)? </li></ul><ul><li>Storylines: </li></ul><ul><ul><li>Market discontinuity – some player offers the world very low cost data centre/computer facility – could be Sony thin client server or Google sales platform… In “Plan 9 from Outer Playstation”, the idea is that of using a powerful processor like Playstation with some open source software as a cheap and accessible platform for all sorts of applications. Another model is BOINC. Another is P2P and Planetlab – the model here is that all Playstations are left on and used as elements in a distributed computing system (like the SETI project) – a “data swarm” which would be user driven, and perhaps be difficult due to problems of authentification and control </li></ul></ul>
  15. 15. Scenario 3 – Panther - Varieties <ul><li>Storylines 2: </li></ul><ul><ul><li>Changed technological paradigm , e.g. quantum computing or similar major architecture change, massive data storage (“exabytes for a few euros”) meaning that we only need data grids (unless local storage prices are also radically reduced): much individual P2P multilateral activity. </li></ul></ul><ul><ul><li>Going East: E and SE Asia (China, Japan, Korea) driven market driven mechanism – outgrowing from manufacturing to a new trading tool, new IPR from Asia-centred computing science; quasi Grid-based computing sold to all suppliers in China; market spreads worldwide, driven by economies of scale and low costs, together with the market strength of C21st major growth centre (?). </li></ul></ul><ul><ul><li>Virtues – Problems : </li></ul></ul><ul><ul><li>New opportunities for new types of businesses </li></ul></ul><ul><ul><li>Handling investments on technologies that become obsolete overnight – danger of triggering a recession. </li></ul></ul><ul><ul><li>Europe might have difficulties in adapting to technology that has been developed in different environment (e.g. facing the “copper limit” in interconnecting systems). </li></ul></ul><ul><ul><li>Policies Ensure contact between cutting-edge research and infrastructure providers. </li></ul></ul><ul><ul><li>Uncertainties: incl Barriers in, e.g., power consumption. (resistance to leaving processors turned on all the time). </li></ul></ul>
  16. 16. Scenario 4 – Donkey - The main theme <ul><li>Total inability of e-Infrastructure to fulfill user requirements </li></ul>Drivers <ul><li>Grand challenge applications fail to drive the need for seamless integration </li></ul><ul><li>No grand challenges left or no funding for these </li></ul><ul><li>EC stops funding for research infrastructures </li></ul><ul><li>Nations gradually discourage collaborative research </li></ul><ul><li>Nations gradually discourage research funding </li></ul><ul><li>Electronic war </li></ul><ul><ul><li>Immense spam, virus, denial of service attacks, electronic pollution in the air, etc. ) </li></ul></ul><ul><li>Technical failures in computer science to provide integrations (e.g. scalability issues) </li></ul><ul><li>Legal issues work as a barrier (privacy, IPR, etc.) </li></ul><ul><li>Risk of massive Single Point of Failures </li></ul><ul><ul><li>Destruction of a major memory chip factory led to a major memory price increase and corresponding computer configurations </li></ul></ul>Implications <ul><li>Stall research development; need to: Keep openness and co-operativeness; Awareness and rapid actions on behalf of governments in case of undesired events; Maintain a democratic basis of governance on the political, social, market, and regulatory aspects </li></ul>
  17. 17. Implications <ul><li>Where are we? This will have a major impact on what sorts of mapping and assessment, forecasting and planning, we undertake. Can evaluation and research into e-research elucidate? What methods for planning follow? </li></ul><ul><li>How distinguishable is e-research from a whole range of other factors shaping research? </li></ul><ul><li>If the range of alternative futures really is so wide, how best to develop strategy and monitor progress? </li></ul><ul><li>How far are there liable to be different futures for different fields? </li></ul><ul><li>What are the new paradigms that may elude established categorisation and measurement, and how can these be identified and shaped (for what goals?)? </li></ul>
  18. 18. End of presentation