TY - GEN
T1 - A multimodal platform for cloud-based collaborative research
AU - Wagenaar, Joost B.
AU - Brinkmann, Benjamin H.
AU - Ives, Zachary
AU - Worrell, Gregory A.
AU - Litt, Brian
PY - 2013
Y1 - 2013
N2 - The need for sharing and analyzing large-scale data sets in scientific research has increased significantly over the last decade. Despite multiple efforts, there is currently no single platform that is widely used to search for, share, and perform custom data analysis over large numbers of TB-scale datasets using cloud technologies. We present a cloud-based portal and data integration/access platform to fulfill this need. The IEEG-Portal is being developed as a means to share and collaborate on projects containing large EEG datasets. It currently contains over 75 de-identified intracranial EEG datasets as well as imaging and associated meta-information, and a variety of datasets from animals. The IEEG-Portal is modular by design, which results in a highly extensible platform for neural data analysis on the cloud. In this paper, we highlight the current state of the portal infrastructure; its capabilities for fostering collaborative research and data-validation, and the challenges that are inherent to sharing and analyzing datasets using a global collaborative cloud-based platform.
AB - The need for sharing and analyzing large-scale data sets in scientific research has increased significantly over the last decade. Despite multiple efforts, there is currently no single platform that is widely used to search for, share, and perform custom data analysis over large numbers of TB-scale datasets using cloud technologies. We present a cloud-based portal and data integration/access platform to fulfill this need. The IEEG-Portal is being developed as a means to share and collaborate on projects containing large EEG datasets. It currently contains over 75 de-identified intracranial EEG datasets as well as imaging and associated meta-information, and a variety of datasets from animals. The IEEG-Portal is modular by design, which results in a highly extensible platform for neural data analysis on the cloud. In this paper, we highlight the current state of the portal infrastructure; its capabilities for fostering collaborative research and data-validation, and the challenges that are inherent to sharing and analyzing datasets using a global collaborative cloud-based platform.
UR - http://www.scopus.com/inward/record.url?scp=84897734583&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84897734583&partnerID=8YFLogxK
U2 - 10.1109/NER.2013.6696201
DO - 10.1109/NER.2013.6696201
M3 - Conference contribution
AN - SCOPUS:84897734583
SN - 9781467319690
T3 - International IEEE/EMBS Conference on Neural Engineering, NER
SP - 1386
EP - 1389
BT - 2013 6th International IEEE EMBS Conference on Neural Engineering, NER 2013
T2 - 2013 6th International IEEE EMBS Conference on Neural Engineering, NER 2013
Y2 - 6 November 2013 through 8 November 2013
ER -