Digits: Two Reports on New Units of Scholarly Publication

Burton, Matt; Lavin, Matthew J.; Otis, Jessica; Weingart, Scott

doi:10.3998/3336451.0022.105

Cited by 3 publications

(2 citation statements)

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“…, Perkel, 2017 ; Samota & Davey, 2021 ) that researchers regard the ability to interact with code published in its complete software environment as beneficial. Using containerisation tools, such as Docker, have been recommended for increasing the reproducibility of research ( Burton et al, 2020 ) but it has also been acknowledged that this requires skills that not many researchers in this field have ( Kim, Poline & Dumas, 2018 ). Platforms that utilise this technology have been adopted or trialled by several publishers, for example Code Ocean has been deployed by some Springer Nature journals, and some Taylor & Francis journals.…”

Section: Discussionmentioning

confidence: 99%

A survey of researchers’ code sharing and code reuse practices, and assessment of interactive notebook prototypes

Cadwallader

Hrynaszkiewicz

2022

PeerJ

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This research aimed to understand the needs and habits of researchers in relation to code sharing and reuse; gather feedback on prototype code notebooks created by NeuroLibre; and help determine strategies that publishers could use to increase code sharing. We surveyed 188 researchers in computational biology. Respondents were asked about how often and why they look at code, which methods of accessing code they find useful and why, what aspects of code sharing are important to them, and how satisfied they are with their ability to complete these tasks. Respondents were asked to look at a prototype code notebook and give feedback on its features. Respondents were also asked how much time they spent preparing code and if they would be willing to increase this to use a code sharing tool, such as a notebook. As a reader of research articles the most common reason (70%) for looking at code was to gain a better understanding of the article. The most commonly encountered method for code sharing–linking articles to a code repository–was also the most useful method of accessing code from the reader’s perspective. As authors, the respondents were largely satisfied with their ability to carry out tasks related to code sharing. The most important of these tasks were ensuring that the code was running in the correct environment, and sharing code with good documentation. The average researcher, according to our results, is unwilling to incur additional costs (in time, effort or expenditure) that are currently needed to use code sharing tools alongside a publication. We infer this means we need different models for funding and producing interactive or executable research outputs if they are to reach a large number of researchers. For the purpose of increasing the amount of code shared by authors, PLOS Computational Biology is, as a result, focusing on policy rather than tools.

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Section: Discussionmentioning

confidence: 99%

A survey of researchers’ code sharing and code reuse practices, and assessment of interactive notebook prototypes

Cadwallader

Hrynaszkiewicz

2022

PeerJ

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“…The escalating prevalence of academic transgressions facilitated by AI within education prompts a reevaluation of academic integrity policies. Institutions are urged to recalibrate policies, circumscribing acceptable collaborative practices and instating robust mechanisms for plagiarism detection specific to higher education (Weingart et al, 2020). The recalibration of academic integrity policies represents a crucial step toward safeguarding the educational landscape from the potential erosive effects of AI on traditional notions of academic honesty.…”

Section: Academic Integrity Policies and Ethical Considerationsmentioning

confidence: 99%

AI in Higher Education

Fowler

2023

J. ethics high. educ.

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This scholarly inquiry examines the interplay between artificial intelligence (AI) and academic integrity within higher education. Through a comprehensive synthesis of academic literature, the study delves into the multifaceted implications of AI tools on academic practices, pedagogical approaches, and the evolving landscape of academic integrity within higher education. The findings, derived from an extensive analysis of scholarly works, offer profound insights into the challenges posed by the integration of AI in higher education. The impact on academic dishonesty, the nuances of pedagogical shifts, and the dynamic relationship between students and AI are scrutinized, contributing to a nuanced comprehension of the intricate dynamics within the academy.

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A survey of researchers’ code sharing and code reuse practices, and assessment of interactive notebook prototypes

Cadwallader¹,

Hrynaszkiewicz²

2022

Preprint

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This research aimed to understand the needs and habits of researchers in relation to code sharing and reuse; gather feedback on prototype code notebooks created by Neurolibre; and help determine strategies that publishers could use to increase code sharing.We surveyed 188 researchers in computational biology. Respondents were asked about how often and why they look at code, which methods of accessing code they find useful and why and what aspects of code sharing are important to them, and how satisfied they are with their ability to complete these. Respondents were asked to look at a prototype code notebook and give feedback on its features. Respondents were also asked how much time they spent preparing code and if they would be willing to increase this to use a code sharing tool, such as a notebook.As a reader of research articles the most common reason (70%) for looking at code was to gain a better understanding of the article. The most commonly encountered method for code sharing – linking articles to a code repository -- was also the most useful method of accessing code from the reader’s perspective. As authors, the respondents were largely satisfied with their ability to carry out tasks related to code sharing. The most important of these tasks were ensuring that the code was running in the correct environment, and sharing code with good documentation.The average researcher, according to our results, is unwilling to incur additional costs (in time, effort or expenditure) that are currently needed to use code sharing tools alongside a publication. We infer this means we need different models for funding and producing interactive or executable research outputs if they are to reach a large number of researchers. For the purpose of increasing the amount of code shared by authors, PLOS Computational Biology is, as a result, focusing on policy rather than tools.

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Digits: Two Reports on New Units of Scholarly Publication

Cited by 3 publications

References 0 publications

A survey of researchers’ code sharing and code reuse practices, and assessment of interactive notebook prototypes

A survey of researchers’ code sharing and code reuse practices, and assessment of interactive notebook prototypes

AI in Higher Education

A survey of researchers’ code sharing and code reuse practices, and assessment of interactive notebook prototypes

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