Big Data
In November, we look at finding, accessing, and (re)using large open datasets.
About
Now that we’ve learned about Data Management and the Brain Imaging Data Structure, it’s time to talk about using large datasets. This can require some different skills compared to using smaller datasets. We’re going to discuss how to find, access, and (re)use large open datasets.
For this topic, we’re thrilled to bring on a new expert, Justine Hansen. Justine, an expert in working with open datasets, has never collected her own data, and all of her analyses depend on data that is either already open or is shared directly with her lab and later made open. This makes her well versed in finding and accessing datasets, as well as integrating multiple datasets and data modalities (e.g. MRI, fMRI, PET, MEG, autoradiography, transcriptomic data) into a single project.
Expert of the month
PhD candidate, McGill University
Justine Hansen is a PhD candidate at the Montreal Neurological Institute with Dr Bratislav Misic, working in the Network Neuroscience lab. She works with multimodal neuroimaging data from large and small open-source datasets to bridge the gap between the brain’s microscale and macroscale.
Seminar/Workshop
November 8 2023, 4pm
The Neuro, De Grandpre auditorium
During this introductory lecture, Justine Hansen will walk through her path to open science and how she found, accessed, and used open (and previously closed) datasets and tools in her work. These datasets include the Human Connectome Project, Neurosynth, the Allen Brain Atlas (and an accompanying tool, abagen), the Brainstem Navigator dataset, as well as others that she has been part of collating and disseminating, e.g. the PEscienceT receptor atlas of the human brain and the neuromaps data repository and toolbox.
The workshop will include specific pointers on how to find, access, and use such open datasets and how to integrate multiple datasets into a single project. She will also share her experience collaborating with research groups whose (previously closed) data she uses, including how to reach out to these groups, how to encourage open data sharing, and how to appropriately give credit to those whose datasets they use.