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Presentation . 2021
License: CC BY
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Other literature type . Presentation . 2021
License: CC BY
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Can we reimagine FAIR for building communities in open science?

Authors: Sharan, Malvika;

Can we reimagine FAIR for building communities in open science?

Abstract

This keynotes talk was given by Malvika Sharan at OPEN SCIENCE FAIR 2021 on 21 September 2021. Video is available online on YouTube. Different stakeholders in research contribute to open science communities with a shared mission of making scientific knowledge freely available for public access. However, most of these communities operate independently of other initiatives, either lacking the capacity to build meaningful collaboration or competing for limited resources. This often results in scientific outputs that most users can find, but not access, build upon or reuse in their local contexts. In this talk, I invite you to reimagine if FAIR [1] guiding principles can be applied for building and supporting open science communities. Can this practice be extended for cross-community collaboration, knowledge exchange and sharing resources? I will discuss how intentional connections between community-led efforts benefit the larger open science ecosystem by enabling sustainable development, maintenance and reuse of community resources. Bringing examples from my work in The Turing Way, Open Life Science and other initiatives, I will further highlight the irreplaceable importance of ���people in open infrastructure��� ��� those who facilitate FAIRness through inclusive approaches in open science communities. [1] FAIR principles provide guidelines to improve the Findability, Accessibility, Interoperability, and Reuse of digital assets. See FAIR Principles - GO FAIR: https://www.go-fair.org/fair-principles.

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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