Neuroinformatics Assembly 2021 - Program
|11:00 - 12:50 EDT||Session 1: Introduction to INCF & perspectives of FAIR
Chair: Maryann Martone, University of California, San Diego
Since their introduction in 2016, the FAIR data principles have gained increasing recognition and adoption in global neuroscience. FAIR defines a set of high level principles and practices for making digital objects, including data, software and workflows, Findable, Accessible, Interoperable and Reusable. But FAIR is not a specification; it leaves many of the specifics up to individual scientific disciplines to define. INCF has been leading the way in promoting, defining and implementing FAIR data practices for neuroscience. We have been bringing together researchers, infrastructure providers, industry and publishers through our programs and networks.
In this session, we will hear some perspectives on FAIR neuroscience from some of these stakeholders who have been working to develop and use FAIR tools for neuroscience. We will engage in a discussion on questions such as: how is neuroscience doing with respect to FAIR? What have been successes? What is currently very difficult? Where does neuroscience need to go? Audience participation will be encouraged.
|12:50 - 13:00 EDT||BREAK|
|13:00 - 14:30 EDT||Session 2: Practical use cases for FAIR
Chair: Anita Bandrowski, SciCrunch
We will explore some practical use cases and see whether these affect your repository, your tool, or your research. This will be a highly interactive session with online polling to engage the audience with the content.Panelists
|11:00 - 12:30 EDT||Session 3: FAIR approaches for computational neuroscience
Chair: Sharon Crook, Arizona State University
As models in neuroscience have become increasingly complex, it has become more difficult to share all aspects of models and model analysis, hindering model accessibility and reproducibility. In this session, we will discuss existing resources for promoting FAIR data and models in computational neuroscience, their impact on the field, and remaining barriers.
|12:30 - 12:40 EDT||BREAK|
|12:40 - 13:00 EDT||DataJoint Elements: Implementing standardized workflows in neurophysiology - Dimitri Yatsenko|
|13:00 - 14:30 EDT||Session 4: FAIR approaches for neuroimaging research
Chair: Satra Ghosh, MIT
Over the last three decades, neuroimaging research has seen large strides in the scale, diversity, and complexity of studies, the open availability of data and methodological resources, the quality of instrumentation and multimodal studies, and the number of researchers and consortia. The awareness of rigor and reproducibility has increased with the advent of funding mandates, and with the work done by national and international brain initiatives. This session will focus on the question of FAIRness in neuroimaging research touching on each of the FAIR elements through brief vignettes of ongoing research and challenges faced by the community to enact these principles.
|14:30 - 15:30 EDT||Poster slot 1 (1 hour)
14:30 EDT/ 20:30 CET
|03:00 - 04:00 EST||Poster slot 2 (1 hour)
09:00 CET /16:00 JST /17:00 AET
|11:00 - 12:30 EDT||Session 5: FAIR approaches for electrophysiology
Chair: Thomas Wachtler, Ludwig-Maximilians University
|12:30 - 13:00 EDT||BREAK|
|13:00 - 14:30 EDT||Session 6: Tools and infrastructure showcase
Chair: Helena Ledmyr, INCF
This session will include presentations of infrastructure that embrace the FAIR principles developed by members of the INCF Community.
|20:00 - 21:00 EDT||Poster slot 3 (1 hour)
20:00 CET /08:00 JST /09:00 AET
|11:30 - 12:30 EDT||Session 7: INCF councils and committees showcase
Chair: Mathew Abrams, INCF
The objective of this session is to present the current and future activities of the INCF councils and committees and provide a forum in which the community can provide feedback and recommend new directions for the INCF network.
|12:30 - 13:00 EDT||BREAK|
|13:00 - 14:00 EDT||Session 8: Data science and neuroinformatics
Chair: Ariel Rokem, University of Washington
Much like neuroinformatics, data science uses techniques from computational science to derive meaningful results from large complex datasets. In this session, we will explore the relationship between neuroinformatics and data science, by emphasizing a range of data science approaches and activities, ranging from the development and application of statistical methods, through the establishment of communities and platforms, and through the implementation of open-source software tools. Rather than rigid distinctions, in the data science of neuroinformatics, these activities and approaches intersect and interact in dynamic ways. Together with a panel of cutting-edge neuro-data-scientist speakers, we will explore these dynamics.
|10:30 - 12:30 EDT||Session 09: International Brain Initiative
Chairs: Kenji Doya, Okinawa Institute of Science and technology & Maryann Martone, University of California, San Diego
The International Brain Initiative (IBI) is a consortium of the world’s major large-scale brain initiatives and other organizations with a vested interest in catalyzing and advancing neuroscience research through international collaboration and knowledge sharing. This session will introduce the IBI and the current efforts of the Data Standards and Sharing Working Group with a view to gain input from a wider neuroscience and neuroinformatics community.
|12:30 - 12:40 EDT||BREAK|
|12:40 - 13:00 EDT||Harnessing (FAIR) Neuroscience Data with MATLAB|
|13:00 - 14:00 EDT||Session 10: Open Innovation & Intellectual property
Chairs: Vijay Iyer, MathWorks, and Randy McIntosh, Baycrest
Participants: Joe Artuso (OpenBCI), Sue Tappan (MBF Bioscience), Markus
In recent years, leading academic institutes have begun to embrace and define Open Science. Some puzzles have emerged, including the role of intellectual property protection for innovations emerging in academia. Meanwhile, industry has been grappling with these puzzles for years. A notable milestone was the publication of Open Innovation in the 2000s, which highlighted limitations of closed innovation and benefits of more open innovation for companies to consider.This session will cover questions such as
- What does open innovation mean for commercial entities? How does it help and challenge operations?
- How do we balance intellectual property protection and open innovation? What is the relationship between intellectual property and open innovation?
- How do we incentivize open innovation for industry and academics?
- What are the risks and benefits of open innovation? For companies and for academics.
- Academia and industry often misunderstand each other. From an industry perspective, what’s one thing about open innovation that might surprise academic researchers?
- Innovation is generally situated within a “supply chain” with the promise of benefits for both the innovators and the downstream consumers. Where do companies fit into a supply chain and how does that affect open innovation?
- How can academia & industry collaborate in an open innovation context?
|14:00 - 15:00 EDT||Posters & networking|