The Turing Way: Aligning Professional Roles and Incentives with Open, Reproducible, and Ethical Research
Creators: name: Bennett, Arielle
name: Sharan, Malvika
Publisher: name: Zenodo
Year: 2024

description: Abstract

In an era marked by rapid technological progress and the evolving landscape of data science and AI, the need for transparent, reproducible, and ethically sound research practices is more pressing than ever. The Turing Way, hosted at The Alan Turing Institute, is an open science, open collaboration, and community-driven initiative that works towards addressing these imperatives. It fosters collaboration among a diverse international community of contributors from various backgrounds and expertise. They are collaboratively developing and promoting best practices in data science, and sharing via an online handbook covering reproducibility, project design, collaboration, communication, ethics, and community building (https://the-turing-way.netlify.app/index.html). 

Over the past five years, The Turing Way has significantly shaped the field of data science by professionalising diverse roles and aligning them with open, reproducible, and ethical research practices. This session’s panel discussion will feature experts from The Turing Way community, exploring diverse initiatives aimed at enhancing and transforming contemporary research practices related to incentives and rewards. The panel will provide insights into core principles, and challenges and opportunities in the professional landscape that foster open collaboration, promote reproducibility, and uphold ethical standards. Participants will leave with an understanding of the intricate relationship between professional responsibilities and recognition that combines open, reproducible, and ethical research.

Agenda








Timing



Description



Who?



Questions





0:00 - 0:08



Welcome and Introduction to The Turing Way



Arielle Bennett



What is The Turing Way?

How are we pushing the conversation on professionalising diverse roles in data science?Use the presentation shared on this page to define the scope and roles.





0:08 - 0:20



Panel introductions



All panellists - 2 mins each


Sandra

Joseph

Neil

Esther



Panellists introduce themselves and respond to how they and their organisations have advocated diversifying roles in research and data science.





0:20 - 0:28



Panel question 1



Posed to two panellists - 3 mins each


RSE: Neil


Data Stewardship: Esther


Other speakers can respond in follow-up (1 min max)



Q1: Can you share how these professions play an important role in adopting and integrating open, reproducible, and ethical research practices into technology and data science projects?

Follow-up: How do these roles affect systems-level change and setting shared standards and practices?





0:28 - 0:36



Panel question 2



Posed to two panellists - 3-4 mins each


Data Stewardship: Joseph


RSE: Sandra


Other speakers can respond in follow-up (1 min max)



Q2: How is the relationship between professional responsibilities and traditional incentive systems evolving? What are some challenges you have faced, and how is your organisation addressing them?

Follow up: Do these relatively newer roles get supported within traditional academic institutions and recognised for promoting best practices?





0:36 - 0:40



Questions from the audience



Openly posed for speakers to respond to

 




0:40 - 0:44



Final words by two speakers



Posed to two panellists - 2 mins each


Sandra, Neil



Q3: Closing question: Who else can we learn from in this area? Are there organisations and individuals outside of the field of open science that we should be looking towards?





0:44 - 0:48



Final words by two speakers



Posed to two panellists - 2 mins each


Esther, Joseph



Q4: Closing question: What is your vision for advancing open collaboration, reproducibility, and ethical standards in research and data science, and how can we leverage The Turing Way in supporting that?





0:48 - 0:50



Wrap up and closing



Arielle and Alexandra