12 research outputs found

    Centering inclusivity in the design of online conferences: An OHBM-Open Science perspective

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    As the global health crisis unfolded, many academic conferences moved online in 2020. This move has been hailed as a positive step towards inclusivity in its attenuation of economic, physical, and legal barriers and effectively enabled many individuals from groups that have traditionally been underrepresented to join and participate. A number of studies have outlined how moving online made it possible to gather a more global community and has increased opportunities for individuals with various constraints, e.g., caregiving responsibilities. Yet, the mere existence of online conferences is no guarantee that everyone can attend and participate meaningfully. In fact, many elements of an online conference are still significant barriers to truly diverse participation: the tools used can be inaccessible for some individuals; the scheduling choices can favour some geographical locations; the set-up of the conference can provide more visibility to well-established researchers and reduce opportunities for early-career researchers. While acknowledging the benefits of an online setting, especially for individuals who have traditionally been underrepresented or excluded, we recognize that fostering social justice requires inclusivity to actively be centered in every aspect of online conference design. Here, we draw from the literature and from our own experiences to identify practices that purposefully encourage a diverse community to attend, participate in, and lead online conferences. Reflecting on how to design more inclusive online events is especially important as multiple scientific organizations have announced that they will continue offering an online version of their event when in-person conferences can resume

    The past, present, and future of the Brain Imaging Data Structure (BIDS)

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    The Brain Imaging Data Structure (BIDS) is a community-driven standard for the organization of data and metadata from a growing range of neuroscience modalities. This paper is meant as a history of how the standard has developed and grown over time. We outline the principles behind the project, the mechanisms by which it has been extended, and some of the challenges being addressed as it evolves. We also discuss the lessons learned through the project, with the aim of enabling researchers in other domains to learn from the success of BIDS

    maximtrp/scikit-posthocs: scikit-posthocs: v0.8.0

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    <p>This release includes a number of features, enhancements and fixes:</p> <ul> <li>critical difference diagrams (see <a href="https://scikit-posthocs.readthedocs.io/en/latest/generated/scikit_posthocs.critical_difference_diagram.html"><code>critical_difference_diagram</code></a>) are implemented (thanks to @pedroilidio and @chengmingbo)</li> <li><code>outliers_gesd</code> code improved (thanks to @ysBach)</li> <li>increased abs tolerance for wilcoxon test (<code>test_posthoc_wilcoxon</code>)</li> <li>minor updates and fixes</li> </ul&gt

    BIDS apps: Improving ease of use, accessibility, and reproducibility of neuroimaging data analysis methods.

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    The rate of progress in human neurosciences is limited by the inability to easily apply a wide range of analysis methods to the plethora of different datasets acquired in labs around the world. In this work, we introduce a framework for creating, testing, versioning and archiving portable applications for analyzing neuroimaging data organized and described in compliance with the Brain Imaging Data Structure (BIDS). The portability of these applications (BIDS Apps) is achieved by using container technologies that encapsulate all binary and other dependencies in one convenient package. BIDS Apps run on all three major operating systems with no need for complex setup and configuration and thanks to the comprehensiveness of the BIDS standard they require little manual user input. Previous containerized data processing solutions were limited to single user environments and not compatible with most multi-tenant High Performance Computing systems. BIDS Apps overcome this limitation by taking advantage of the Singularity container technology. As a proof of concept, this work is accompanied by 22 ready to use BIDS Apps, packaging a diverse set of commonly used neuroimaging algorithms

    Proceedings of the OHBM Brainhack 2021

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    The global pandemic presented new challenges and op-portunities for organizing conferences, and OHBM 2021was no exception. The OHBM Brainhack is an event thatoccurs just prior to the OHBM meeting, typically in-per-son, where scientists of all levels of expertise and interestgather to work and learn together for a few days in a col-laborative hacking-style environment on projects of com-mon interest (1). Building off the success of the OHBM2020 Hackathon (2), the 2021 Open Science SpecialInterest Group came together online to organize a largecoordinated Brainhack event that would take place overthe course of 4 days. The OHBM 2021 Brainhack eventwas organized along two guiding principles, providinga highly inclusive collaborative environment for inter-action between scientists across disciplines and levelsof expertise to push forward important projects thatneed support, also known as the “Hack-Track” of theBrainhack. The second aim of the OHBM Brainhack is toempower scientists to improve the quality of their sci-entific endeavors by providing high-quality hands-ontraining on best practices in open-science approaches.This is best exemplified by the training events providedby the “Train-Track” at the OHBM 2021 Brainhack. Here,we briefly explain both of these elements of the OHBM2021 Brainhack, before continuing on to the Brainhackproceedings

    The Past, Present, and Future of the Brain Imaging Data Structure (BIDS)

    No full text
    The Brain Imaging Data Structure (BIDS) is a community-driven standard for the organization of data and metadata from a growing range of neuroscience modalities. This paper is meant as a history of how the standard has developed and grown over time. We outline the principles behind the project, the mechanisms by which it has been extended, and some of the challenges being addressed as it evolves. We also discuss the lessons learned through the project, with the aim of enabling researchers in other domains to learn from the success of BIDS
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