Proposed Training to Meet Challenges of Large-Scale Data in Neuroscience.

William Grisham,Barbara Lom,Raddy L Ramos,Linda Lanyon

doi:10.3389/fninf.2016.00028

Abstract

The scale of data being produced in neuroscience at present and in the future creates new and unheralded challenges, outstripping conventional ways of handling, considering, and analyzing data. As neuroinformatics enters into this big data era, a need for a highly trained and perhaps unique workforce is emerging. To determine the staffing needs created by the impending era of big data, a workshop (iNeuro Project) was convened November 13–14, 2014. Participants included data resource providers, bioinformatics/analytics trainers, computer scientists, library scientists, and neuroscience educators. These individuals provided perspectives on the challenges of big data, the preparation of a workforce to meet these challenges, and the present state of training programs. Participants discussed whether suitable training programs will need to be constructed from scratch or if existing programs can serve as models. Currently, most programs at the undergraduate and graduate levels are located in Europe—participants knew of none in the United States. The skill sets that training programs would need to provide as well as the curriculum necessary to teach them were also discussed. Consistent with Vision and Change in Undergraduate Biology Education: A Call to Action1, proposed curricula included authentic, hands-on research experiences. Further discussions revolved around the logistics and barriers to creating such programs. The full white paper, iNeuro Project Workshop Report, is available from iNeuro Project2.

Highlights

Large-scale brain genomics has already made a significant impact on neuroscience (Insel et al, 2004), and big data have the potential to change the process of discovery in neuroscience as it has in mathematics, astronomy, and genetics (Nielsen, 2011)
This workshop brought together purveyors of large-scale data resources, individuals involved with bioinformatics training, library and information scientists, computer scientists, neuroscience educators, International Neuroinformatics Coordinating Facility (INCF) and National Science Foundation (NSF) officers, and other scientific collaborators focused on dealing with the human capital needs posed by large-scale data in neuroscience
There are several reasons to initiate big data neuroinformatics programs at this point in time: the public is interested in such efforts, there are expanding global online resources including those provided by the INCF7, and job opportunities for such a workforce are already emerging

Summary

INTRODUCTION

Large-scale brain genomics has already made a significant impact on neuroscience (Insel et al, 2004), and big data have the potential to change the process of discovery in neuroscience as it has in mathematics, astronomy, and genetics (Nielsen, 2011). Inspired by the efforts and priorities of the European Commission Human Brain Project and the White House BRAIN Initiative, an NSF-sponsored workshop, called iNeuro Project, with more than 35 participants was convened in Arlington, VA, USA, November 13–14, 2014 to address the need for training in this aspect of neuroinformatics. This workshop brought together purveyors of large-scale data resources, individuals involved with bioinformatics training, library and information scientists, computer scientists, neuroscience educators, INCF and NSF officers, and other scientific collaborators focused on dealing with the human capital needs posed by large-scale data in neuroscience.

A STATEMENT OF THE PROBLEM

CONCLUSIONS