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Hauptverfasser: Sharan, Malvika, Karoune, Emma, Hellon, Vicky, van Praag, Cassandra Gould, Kayumbi, Gabin, Bennett, Arielle, Alvarez, Alexandra Araujo, Steele, Anne Lee, Batchelor, Sophia, Lacey, Arron, Whitaker, Kirstie
Format: Preprint
Veröffentlicht: 2024
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Online-Zugang:https://arxiv.org/abs/2409.00108
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author Sharan, Malvika
Karoune, Emma
Hellon, Vicky
van Praag, Cassandra Gould
Kayumbi, Gabin
Bennett, Arielle
Alvarez, Alexandra Araujo
Steele, Anne Lee
Batchelor, Sophia
Lacey, Arron
Whitaker, Kirstie
author_facet Sharan, Malvika
Karoune, Emma
Hellon, Vicky
van Praag, Cassandra Gould
Kayumbi, Gabin
Bennett, Arielle
Alvarez, Alexandra Araujo
Steele, Anne Lee
Batchelor, Sophia
Lacey, Arron
Whitaker, Kirstie
contents In this article we discuss community management in interdisciplinary research teams, focusing on recognising and professionalising roles referred to here as the Research Community Managers (RCM). Drawing insights and examples from research and data science projects, we discuss how RCM roles address some of the research’s most pressing challenges, from promoting best practices for open research and reproducibility to engaging diverse stakeholders in community-led research and ensuring fair recognition for their contributions. We offer a Community Maturation Indicator and share examples of projects from The Alan Turing Institute, the UK's national institute for data science and Artificial Intelligence (AI), where institutionally supported RCM roles were established. With the aim to integrate RCM expertise in teams involved in data science and AI research, we provide an RCM Skills and Competencies Framework. We also propose a roadmap for professionalising RCM roles by improving recognition and rewards, potential career paths and organisational support structures. To systematically sustain and progress these roles, we recommend institutional investment in establishing RCM teams that are empowered to prioritise collaboration, transparency and community-based approaches in interdisciplinary projects, such as in data science and AI. As a team, RCMs are well placed to connect disparate teams, initiatives and resources across the organisation, building more resilient research communities that can achieve greater innovation, improved project outcomes and a strongly connected ecosystem, with impacts extending beyond their narrow contexts.
format Preprint
id arxiv_https___arxiv_org_abs_2409_00108
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Professionalising Community Management Roles in Interdisciplinary Research Projects
Sharan, Malvika
Karoune, Emma
Hellon, Vicky
van Praag, Cassandra Gould
Kayumbi, Gabin
Bennett, Arielle
Alvarez, Alexandra Araujo
Steele, Anne Lee
Batchelor, Sophia
Lacey, Arron
Whitaker, Kirstie
Physics and Society
In this article we discuss community management in interdisciplinary research teams, focusing on recognising and professionalising roles referred to here as the Research Community Managers (RCM). Drawing insights and examples from research and data science projects, we discuss how RCM roles address some of the research’s most pressing challenges, from promoting best practices for open research and reproducibility to engaging diverse stakeholders in community-led research and ensuring fair recognition for their contributions. We offer a Community Maturation Indicator and share examples of projects from The Alan Turing Institute, the UK's national institute for data science and Artificial Intelligence (AI), where institutionally supported RCM roles were established. With the aim to integrate RCM expertise in teams involved in data science and AI research, we provide an RCM Skills and Competencies Framework. We also propose a roadmap for professionalising RCM roles by improving recognition and rewards, potential career paths and organisational support structures. To systematically sustain and progress these roles, we recommend institutional investment in establishing RCM teams that are empowered to prioritise collaboration, transparency and community-based approaches in interdisciplinary projects, such as in data science and AI. As a team, RCMs are well placed to connect disparate teams, initiatives and resources across the organisation, building more resilient research communities that can achieve greater innovation, improved project outcomes and a strongly connected ecosystem, with impacts extending beyond their narrow contexts.
title Professionalising Community Management Roles in Interdisciplinary Research Projects
topic Physics and Society
url https://arxiv.org/abs/2409.00108