Meeting Curation Challenges in a Neuroimaging Group
Author(s) -
Angus Whyte,
Dominic Job,
Stephen Giles,
Stephen M. Lawrie
Publication year - 2008
Publication title -
international journal of digital curation
Language(s) - English
Resource type - Journals
ISSN - 1746-8256
DOI - 10.2218/ijdc.v3i1.53
Subject(s) - data curation , context (archaeology) , data sharing , documentation , metadata , neuroimaging , computer science , data science , knowledge management , reuse , neuroinformatics , world wide web , psychology , engineering , medicine , paleontology , alternative medicine , pathology , psychiatry , biology , programming language , waste management
The SCARP project is a series of short studies with two aims; firstly to discover more about disciplinary approaches and attitudes to digital curation through ‘immersion’ in selected cases; secondly to apply known good practice, and where possible, identify new lessons from practice in the selected discipline areas. The study summarised here is of the Neuroimaging Group in the University of Edinburgh’s Division of Psychiatry, which plays a leading role in eScience collaborations to improve the infrastructure for neuroimaging data integration and reuse. The Group also aims to address growing data storage and curation needs, given the capabilities afforded by new infrastructure. The study briefly reviews the policy context and current challenges to data integration and sharing in the neuroimaging field. It then describes how curation and preservation risks and opportunities for change were identified throughout the curation lifecycle; and their context appreciated through field study in the research site. The results are consistent with studies of neuroimaging eInfrastructure that emphasise the role of local data sharing and reuse practices. These sustain mutual awareness of datasets and experimental protocols through sharing peer to peer, and among senior researchers and students, enabling continuity in research and flexibility in project work. This “human infrastructure” is taken into account in considering next steps for curation and preservation of the Group’s datasets and a phased approach to supporting data documentation
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