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Research and Data Networks: A global perspective.

Research and Data Networks: A global perspective. Deborah Mitchell Australian National University. Overview. Research networks From local to global Diffusion of e-Research Breakthroughs and constraints Enabling technologies Data storage, analysis and conventions Next steps

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Research and Data Networks: A global perspective.

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  1. Research and Data Networks:A global perspective. Deborah Mitchell Australian National University

  2. Overview • Research networks • From local to global • Diffusion of e-Research • Breakthroughs and constraints • Enabling technologies • Data storage, analysis and conventions • Next steps • What do researchers want? • Multi-lateral agreements

  3. Research networks • From local to global • The social sciences have been at the forefront of the development of global research networks, dating from 1980s. Examples include ISSP; WVS; and LIS. • “Front-end” approach: creating comparative data. • Diffusion of the ‘idea’ of e-Research • e-Research only possible in the context of powerful desk top computing; the WWW; and software tools. • “Back-end” technologies: taking diverse data forms, post-creation to create new research horizons. Examples include visual mapping of observations to customary spatial divisions, eg Census locations.

  4. Breakthroughs and … constraints • Enabling technologies • Concerted funding by research councils has led to a dazzling array of e-research tools; cyber-infrastructure investment. • Data visualisation tools especially strong and developed by humanities, arts and geographers. • Are the social sciences now lagging? Are there constraints? • Data storage, analysis and conventions • Early ‘research efficiency’ gains in the social sciences may be being penalised in current research council funding rounds. Front-end approaches to data creation and widespread adoption of conventions such as the DDI, make the task of claiming funding difficult for the social sciences. • The ‘gee-whizz’ factor and the ‘terabyte’ effect. Tool development is lagging in the social sciences, especially for quantitative data. Tolerance of inefficient data forms.

  5. Next Steps (1)… What do researchers want? • The short answer • Everything, now, on the desk-top … and with minimal effort. • The long answer • Current [Google, Wiki] generation of researchers lack an appreciation of ‘front-end’ efficiencies. This is also true of funding bodies. Should we now focus on ‘back-end’ technologies in archives? ie, using improved tools to achieve the same ends (data quality or comparability) post-collection? • Ability to combine diverse data forms, within and between national data sources; ie, assembling the quantitative, qualitative, admin and visual data on a particular topic. • Minimising barriers to data access, cross-nationally. For example, adopting common ‘Shibboleth-type’ conventions.

  6. Next Steps (2)… Multi-lateral agreements • A starting point • The 40th anniversary of UKDA, the existence of the ICPSR archive at Michigan and the CESSDA group, all provide a strong basis for considering the possibility of a multi-lateral project for data distribution. This would address the global access barriers for researchers. • Building on existing strengths • A natural progression from the above and again, building on existing common platforms such as Nesstar, the DDI conventions: would be the development and the capacity to develop [and transfer!] a bank of e-Research tools. • For those in the ‘Nesstar club’ this would mean placing greater demands on the Nesstar group to develop and make available innovations to all subscribers. Development of a ‘tool bank’ alongside of existing data sources.

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