Pennsieve: Impactful Multimodal Data Sharing for Epilepsy Research - Summary Epilepsy affects over 70 million people globally and more than 3.6 million Americans, 1/3 of who are not controlled by medication. While new technologies like laser ablation, implantable devices, high bandwidth intracranial EEG (iEEG), and multimodal imaging have improved therapies, meaningful data sharing is lacking which limits clinical progress and translational research. There is a tremendous need to aggregate, share and collaborate on increasingly large and complex multimodal data from patients with medication-resistant epilepsy to advance these efforts, but a lack of novel mechanisms to share and explore these data in a meaningful way. Our central hypothesis is that a scalable, self-sustaining Epilepsy Data Ecosystem (EDE), which integrates multi-modal datasets and is responsive to the changing needs of the epilepsy community, will dramatically accelerate translational research and impact clinical care. The EDE will also accelerate the fields of Machine Learning, Neuroscience and Computer Science, communities that depend upon large, multimodal data from these patients for their research. Over the past 14 years our group has focused on building tools and community to accelerate translational epilepsy and neuroscience research through two major efforts: (1) through our open- source platform iEEG.org, for sharing data and computational tools in epilepsy. Seeded by a grant from NINDS from 2009-2013 and supported by a group of over 200 scientists focused on Engineering and Epilepsy Research (the ICTALS group), the platform now has almost 6,000 users and is self-sustaining, paid for by groups who use it for their research needs. It shares over 1,000 published data sets free of charge, and it has generated scores of publications. Advances to care, data standards and platform technologies as well as the significant increase in data volume require that iEEG.org be updated. (2) Led by Dr. Joost Wagenaar, The Pennsieve Platform was independently developed over the last 7 years as an open-source, cloud-based data management and sharing platform for large volume, multi-modal data in the Neurosciences, with a focus on standards, scalability, and sustainability. It is currently used as the data core for several NIH programs (e.g. SPARC and REJOIN) and is ideally suited to replace iEEG.org as the next generation repository for multimodal data in Epilepsy research. Our goals for this proposal are: (1) To migrate all data, tools, and users from iEEG.org to Pennsieve, to ensure continued impact of iEEG.org public datasets by updating the data to adhere to current standards, (2) To tailor Pennsieve to the Epilepsy Community's needs, to develop seamless mechanisms for submitting, finding, sharing, accessing, and publishing high impact Epilepsy Datasets in line with all FAIR requirements and standards in the age of big integrated data, (3) To build community and prospective data contributions to the EDE through educational workshops, seminars and web content, and (4) to leverage Pennsieve's workflows and existing model to ensure sustainability. This project leverages an established collaboration between investigators across Medicine and Engineering at Penn, and the International Epilepsy Community.
