Maryann Martone

Maryann Martone received her BA from Wellesley College in biological psychology and her Ph. D. in neuroscience in 1990 from the University of California, San Diego, where she is currently a Professor in the Department of Neuroscience. Her background is in neuroanatomy, particularly light and electron microscopy, but she spends most of her time now in the field of neuroinformatics.  Maryann is the principal investigator of the Neuroinformatics Framework project, a national project to establish a uniform resource description framework for neuroscience.  Her recent work has focused on building ontologies for neuroscience for data integration.

University of California, San Diego, USA

Talk title
Making neuroscience FAIR

Talk abstract
The launch of several international large brain projects indicates that we are still far from understanding the brain at even a basic level, let alone being able to intervene meaningfully in most degenerative, psychiatric and traumatic brain disorders.  Such projects reflect the idea that neuroscience needs to be placed on a more data-rich, computational footing to address the inherent complexity of the nervous system.  But should we just be looking towards big science to produce comprehensive and integrated data and tools?  What about the thousands of studies conducted by individual investigators and small teams?  How does the regular practice of neuroscience need to change to address grand challenges in brain science?

Across the breadth of academia, researchers are defining new modes of scholarship designed to take advantage of 21st century technology for linking and distributing information.  Principles, best practices and tools for networked scholarship are emerging. Chief among these is the move towards open science, making the products of research as open as possible to ensure their broadest use.  Second, that research outputs should not only include journal articles and books, but data, tools and workflows.  Third, that research outputs should be FAIR: Findable, Accessible, Interoperable and Reusable-the characteristics required for making digital objects maximally useful for both humans and machines.  Finally, that citation and credit systems be redesigned to reflect the broadening of scholarly output.

In this presentation, I will discuss how neuroscience can become an open and FAIR discipline, highlighting both approaches and capabilities enabled by open and FAIR data.  Furthermore, with significant concerns about the reproducibility of neuroscience experiments and the frustrating lack of progress on developing effective treatments for neurodegenerative, neurotraumatic and neuropsychiatric diseases, I will argue that we have a moral imperative to ensure that the outputs of both large scale brain initiatives and individual researchers alike are open, FAIR and citable.