Working in the clouds: creating an e-science collaborative environment for neurophysiology

Abstract

Event Abstract Back to Event Working in the clouds: creating an e-science collaborative environment for neurophysiology Colin Ingram1* 1 University of Newcastle, Institute of Neuroscience, United Kingdom Understanding the way that neural networks function can only be achieved through detailed analysis of the spatio-temporal relationships between activity patterns of neurones within the network. The increasing sophistication of multielectrode and optical recording techniques has provided the means for us to explore the control and organisation of neural networks in ever greater detail. However, whilst developments in neuroinformatics offer new ways in which the large volumes of data generated from such techniques may be manipulated and analysed, there is a growing need to develop an infrastructure to support sharing and collaborative exploitation of these data. Cloud computing provides exciting opportunities for this exploitation with rapidly increasing availability of data storage and compute resource accessed through the web. However, any practical solution to supporting analysis and sharing of time-series neurophysiological data needs to address a number of major challenges, including interoperability of file formats, data visualisation, and effective metadata descriptions. These challenges are being addressed through a number of international research projects, including CARMEN (Code Analysis, Repository and Modelling for e-Neuroscience; www.carmen.org.uk), an open access web platform developed for handling time-series data using distributed computing technology. CARMEN has created a secure collaborative environment in which data can be shared, either between private groups or publicly, and new analysis algorithms can be deployed without restrictions of issues of software and file compatibility. The on-going implementation of an enactment engine is enabling service applications to be linked into more complex and user-defined workflows. The cloud architecture allows the co-location of data and computation and enabling users to conduct their science through a web browser. Furthermore the growing data repository enables maximum exploitation of data that are often difficult and expensive to produce. CARMEN is one example of the shift from small scale science to large scale data integration which will underpin the next major steps in understanding the brain. Infrastructure built on cloud computing will make this integration feasible and will offer new opportunities to build a global community for neuroscience. Conference: Neuroinformatics 2010 , Kobe, Japan, 30 Aug - 1 Sep, 2010. Presentation Type: Oral Presentation Topic: Keynote speakers Citation: Ingram C (2010). Working in the clouds: creating an e-science collaborative environment for neurophysiology. Front. Neurosci. Conference Abstract: Neuroinformatics 2010 . doi: 10.3389/conf.fnins.2010.13.00019 Copyright: The abstracts in this collection have not been subject to any Frontiers peer review or checks, and are not endorsed by Frontiers. They are made available through the Frontiers publishing platform as a service to conference organizers and presenters. The copyright in the individual abstracts is owned by the author of each abstract or his/her employer unless otherwise stated. Each abstract, as well as the collection of abstracts, are published under a Creative Commons CC-BY 4.0 (attribution) licence (https://creativecommons.org/licenses/by/4.0/) and may thus be reproduced, translated, adapted and be the subject of derivative works provided the authors and Frontiers are attributed. For Frontiers’ terms and conditions please see https://www.frontiersin.org/legal/terms-and-conditions. Received: 09 Jun 2010; Published Online: 09 Jun 2010. * Correspondence: Colin Ingram, University of Newcastle, Institute of Neuroscience, Newcastle, United Kingdom, c.d.ingram@ncl.ac.uk Login Required This action requires you to be registered with Frontiers and logged in. To register or login click here. Abstract Info Abstract The Authors in Frontiers Colin Ingram Google Colin Ingram Google Scholar Colin Ingram PubMed Colin Ingram Related Article in Frontiers Google Scholar PubMed Abstract Close Back to top Javascript is disabled. Please enable Javascript in your browser settings in order to see all the content on this page.