The paper reviewed here is ‘The Neuroscience Information Framework: A Data and Knowledge Environment for Neuroscience’ and freely available here. The authors describe the establishment of the Neuroscience Information Framework (The Neuroscience Information Framework is located here). The authors begin by describing the purpose of the NIF in
‘the NIF is a new initiative for integrating access to – and thereby promoting use of – Web based neuroscience resources‘
In order to do this a complex logistical exercise was undertaken which is described in overview and involved the delivery to the American National Institute for Health. What is particularly interesting is that this has been delivered with an open source license and it would not be unreasonable to suggest that this is a Web 2.0 project. A number of aims are described including building links with wider communities and thus drawing on diverse areas of expertise. There are also specific aims – to ‘advance the mission and goals of the NIH Blueprint for Neuroscience Research’. There is then discussion of the Neuroinformatic Ecosystem
‘Neuroscience is among the most complex scientific activities the world has known. No other area uses more different techniques, develops more different models, explores across more scales: from Angstrom units to populations‘
Psychiatry also crosses many such domains and is immensely complex. The relationship between psychiatry and neuroscience is similarly complex and some of the issues faced by each may be shared although taking manifesting differently. The authors then talk about the appropriate labelling of neuroscience data by the neuroscience community and that the usefulness of such data is dependent on the ‘density’ of data and raise a very important point
‘If a resource is only sparsely populated with respect to the potentially available data, it loses both utility and credibility. If a researcher looks for data in an archive, fails to find it, and then discovers text partially describing the same data available through other means (e.g. Google, supplementary materials of papers, personal web pages of individual investigators), the archive is failing at a central task‘
They go on to clarify other aspects of the infrastructure – it should allow reusability of the information and integration of the data from different areas of research. The authors describe how the infrastructure emerges from those already in existence including several databases and some of the other properties it must have including extendability. They go into detail about how it differs from the Google search engine by describing it as neuroscience specific. The data has another quality referred to as ‘dynamic’ and as I read this the term semantic web sprang to mind as did the approach being used by Wolfram Alpha. These are certainly interesting times and this infrastructure may have significant benefits not just for neuroscience but for closely related areas including psychiatry. This will be an area to keep a close eye on for those with an interest in neuroscience.
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