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- Research & Development
- Geographic Simulation
- Semantic Web
- Social Shaping
- Understanding New Forms of Digital Records (Digital Records)
- Video Annotation
- Quantitative Research
- Data Management
- Obesity e-Lab
- LifeGuide
- GENeSIS
- Hub Research
- Use and Relevance of web2.0 for researchers
- Adoption of e-Research Technologies: from prototype to commodity
- Adaptive Visualisation Tools for e-Science Collaboration (ADVISES)
- ID Cards
- Accelerating Transition to Virtual Research Organisation in Social Science (AVROSS)
- Collaborative Research Events on the Web (CREW)
- Uptake of e-Research in Taiwan and the UK
- e-Uptake: Enabling Uptake of e-Infrastructure Services
- eIUS: e-Infrastructure Use Cases and Service Usage Models
- International Collaboration to Extend and Advance Grid Education (ICEAGE)
- StORe (Source-to-Output Repositories)
- Social and Ethical Issues in e-Health Technologies
- NeuroGrid
- Text Mining
- EUAsiaGrid
- Meeting Memory Technology Informing Collaboration (MEMETIC)
- Use and Relevance of web2.0 for researchers
- Small Grant Projects
- Pilot Demonstrator Projects
- e-infrastructure
NeuroGrid
Principal Investigator -
Co-Principal Investigators -
Prof. John Geddes, Dr Andrew Simpson, University of
Dr. Nick Fox, Prof Martin Rossor, Prof. Derek Hill, University College London
Prof. Joseph Hajnal, Imperial College London
Prof. Rob Procter, National Centre for e-Social Science
Dr. Stephen Lawrie, Dr Joannna Wardlaw, University of Edinburgh
Prof. Philip Bath, University of Nottingham
Prof. Ian McKeith, Prof John O'Brien, University of Newcastle
Prof. Ed Bulmore, Dr John Suckling, Prof. John Hodges, Adenbrookes Hosptial, Cambridge
Contact - Please see website
Start date - March 2005
Duration - 3 years
Website - http://www.neurogrid.ac.uk
The aim of the NeuroGrid consortium is to enhance collaboration between clinical, imaging and e-scientists to create a Grid-based network of neuroimaging centres and a neuroimaging tool-kit. Sharing data, experience and expertise will facilitate the archiving, curation, retrieval and analysis of imaging data from multiple sites and enable large-scale clinical studies.
A critical strategy of the NeuroGrid project is to provide enabling capabilities for the neuroimaging community by using Grid technology to allow current algorithms and existing data management procedures to be more accessible and interoperable, so that there are low barriers to entry and time is not wasted re-engineering well established algorithms or forcing alien practices on established research groups. Although the primary aim is not to produce new research data, NeuroGrid will produce valuable new scientific findings from the application of cutting edge analytic methods to combined existing datasets.