PARSE-insight conclusions on European science data infrastructure published
14 July, 2010 | in Community
By: Mr Graham Pryor
After two years of research, the European project PARSE.Insight held its final symposium on 25th June 2010 to present results and recommendations for the science data infrastructure in Europe.
Ten major insights into research and researcher behaviours were presented. These included the identification of major differences between European countries in their methods for dealing with research data and an exposition of researchers' attitudes to data sharing. These findings were enforced by the outcomes of three case studies - in High-Energy Physics, Earth Observation and Social Sciences and Humanities.
In conjunction with these insights the final roadmap for a science data infrastructure in Europe has been published. Aside from technical aspects this also addresses organisational as well as social aspects, such as incentives for researchers to increase their willingness to share their data.
Mr Graham Pryor
As Associate Director Graham has responsibility for the Edinburgh team’s contribution to the DCC partnership, with a particular interest in the identification of new directions and new business. Prior to joining the DCC he was project manager for JISC's Source to Output Repositories project (StORe), which explored the creation of bidirectional links between electronic publications and the data from which they are derived. Before StORe, Graham spent nine years as Director of Information Systems and Services at the University of Aberdeen, following ten years in a number of senior information management posts within the oil and gas sector. His second novel, Preferred Lies, was published in 2007.
- Institution:
- Edinburgh
- Contact:
- graham.pryor@ed.ac.uk
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The aim of the Infrastructure for Integration in Structural Sciences (I2S2) project is to uncover what’s needed to implement a data-driven research infrastructure in the structural sciences – chemistry in particular. Issues of scale, complexity and inter-disciplinary research throughout the data lifecycle will be explored over 18 months.
