The rise of “big data” research has offered researchers unprecedented methods of working with enormous amounts of data to address complex questions in many fields. Working with information at this scale presents challenges with data management, sharing and processing, as many researchers must juggle the use of multiple standalone tools to carry out their work.
To simplify the research workflow, Healthy Brains, Healthy Lives (HBHL) has supported a team at McGill to create NeuroHub, a free, open platform that offers tools for efficient, collaborative and reproducible science in neuroinformatics, genomics, social sciences, biology and more. Through an online portal, NeuroHub gives access to a streamlined system for storing and sharing data with connectivity to standard computational tools for data processing. “As a unique platform integrating multimodal data with advanced analysis algorithms, NeuroHub is at the heart of the HBHL vision of big data neuroscience,” says HBHL Scientific Director Alan Evans. “Through NeuroHub, McGill has become a world leader in the expanding field of neuroinformatics."
To make data management and sharing easy, NeuroHub features a rich searchable data repository and offers dedicated storage for users whose research leverages the platform. In addition to being able to upload their own data, researchers can access standardized, searchable datasets, including datasets from neuroimaging and genomics, as well as cohort and longitudinal data from behavioural, population and social science studies. All data across NeuroHub are linked with metadata to enable easier searches and have varying levels of access control to keep sensitive information private.
“NeuroHub’s data space manages access to both publicly available datasets and data with restricted access, and these different levels of access will help researchers collaborate by offering straightforward options for private versus public data sets,” explains Jean-Baptiste Poline, co-principal investigator on NeuroHub. “The platform also gives approved users access to key resources in neuroscience, such as raw and processed data from the UK Biobank, including data relevant to the COVID-19 pandemic.”
Once users have uploaded their data into NeuroHub, the platform’s connectivity to existing computational infrastructure simplifies the number of steps usually required to perform big data calculations. Small- and large-scale computational workflows can be launched directly from within the platform on different services—for example, a researcher can upload data, send it to a high-performance computing centre for processing and have the results sent directly back into NeuroHub for further exploration. “Unlike some solutions, users do not have to use command line prompts as NeuroHub allows users to interact with external tools through one simple graphical user interface,” says Bryan Caron, NeuroHub director. “This greatly simplifies the user experience to accomplish their data processing, analysis and sharing objectives.”
Already, researchers are exploring ways to take advantage of NeuroHub’s infrastructure in different fields, including ways to bring artificial intelligence and brain research closer together. “Research groups around the world are using artificial neural networks, the workhorse of modern artificial intelligence, to compare different forms of models to real brains,” explains Blake Richards, researcher at McGill University and the Quebec Artificial Intelligence Institute. “At the same time, many machine learning researchers are interested in developing better techniques for analyzing complex, high-dimensional neural data. Both these streams of work require computational researchers to have access to large amounts of data from real brains. NeuroHub is establishing a key open data resource for the growing community of people working at the intersection of neuroscience and AI.” Existing projects can also take advantage of NeuroHub’s features right away—the Quebec Parkinson Network (QPN) has already begun using the platform to help manage their imaging and genetics data.
Looking ahead, NeuroHub will continue to evolve, working with users to determine their greatest needs, and adding new features to address them. New functionalities are already planned, some of which were identified in collaboration with alpha and beta users prior to the launch, such as accessibility of datasets from the Canadian Open Neuroscience Platform (CONP) and Open Science Framework (OSF). Through this community approach focused on interoperability between platforms, NeuroHub promises to be a powerful platform for the scientific community to use.
Visit the NeuroHub website to learn more about the platform and register for access.
