AGILE Reproducible Paper Guidelines

Nüst, Daniel; Ostermann, Frank O.; Šileryté, Rusné; Hofer, Barbara; Granell, Carlos; Teperek, Marta; Gräser, Axel; Broman, Karl W.; Hettne, Kristina; Clare, Connie

doi:10.17605/osf.io/cb7z8

Cited by 6 publications

(1 citation statement)

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“…Fortunately, funding bodies, e.g., Horizon 2020 (https://ec.europa.eu/research/participants/ docs/h2020-funding-guide/cross-cutting-issues/open-access-dissemination_en.htm, last access for this and the following URLs: 20th Dec 19), increasingly consider data and software management plans as part of grant proposals. Accordingly, more editors add a section on code and data availability into their author guidelines (see, e.g., Nüst, Ostermann, et al (2019); Hrynaszkiewicz (2019)), and reviewers consider reproducibility in their decision process (Stark 2018). Nevertheless, these cultural and systematic developments (Munafò et al 2017) alone do not solve the plethora of reproducibility issues.…”

Section: Introductionmentioning

confidence: 99%

Publishing computational research – A review of infrastructures for reproducible and transparent scholarly communication

Konkol¹,

Nüst²,

Goulier³

2020

Preprint

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Funding agencies increasingly ask applicants to include data and software management plans into proposals. In addition, the author guidelines of scientific journals and conferences more often include a statement on data availability, and some reviewers reject unreproducible submissions. This trend towards open science increases the pressure on authors to provide access to the source code and data underlying the computational results in their scientific papers. Still, publishing reproducible articles is a demanding task and not achieved simply by providing access to code scripts and data files. Consequently, several projects develop solutions to support the publication of executable analyses alongside articles considering the needs of the aforementioned stakeholders. The key contribution of this paper is a review of applications addressing the issue of publishing executable computational research results. We compare the approaches across properties relevant for the involved stakeholders, e.g., provided features and deployment options, and also critically discuss trends and limitations. The review can support publishers to decide which system to integrate into their submission process, editors to recommend tools for researchers, and authors of scientific papers to adhere to reproducibility principles.

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Section: Introductionmentioning

confidence: 99%

Publishing computational research – A review of infrastructures for reproducible and transparent scholarly communication

Konkol¹,

Nüst²,

Goulier³

2020

Preprint

Self Cite

View full text Add to dashboard Cite

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Reproducibility and replicability: opportunities and challenges for geospatial research

Kedron

Fotheringham

et al. 2020

International Journal of Geographical Information Science

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Practical Reproducibility in Geography and Geosciences

Nüst

Pebesma

2020

Annals of the American Association of Geographers

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Reproducible research is often perceived as a technological challenge, but it is rooted in the challenge to improve scholarly communication in an age of digitisation. When computers become involved and researchers want to allow other scientists to inspect, understand, evaluate, and build upon their work, they need to create a research compendium that includes the code, data, computing environment, and script-based workflows used. Here, we present the state of the art for approaches to reach this degree of computational reproducibility, addressing literate programming and containerisation, while paying attention to working with geospatial data (digital maps, GIS). We argue that all researchers working with computers should understand these technologies to control their computing environment, and we present the benefits of reproducible workflows in practice. Example research compendia illustrate the presented concepts and are the basis for challenges specific to geography and geosciences. Based on existing surveys and best practices from different scientific domains, we conclude that researchers today can overcome many barriers and achieve a very high degree of reproducibility. If the geography and geosciences and communities adopt reproducibility and the underlying technologies in practice and in policies, they can transform the way researchers conduct and communicate their work towards increased transparency, understandability, openness, trust, productivity, and innovation.

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AGILE Reproducible Paper Guidelines

Cited by 6 publications

References 0 publications

Publishing computational research – A review of infrastructures for reproducible and transparent scholarly communication

Publishing computational research – A review of infrastructures for reproducible and transparent scholarly communication

Reproducibility and replicability: opportunities and challenges for geospatial research

Practical Reproducibility in Geography and Geosciences

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AGILE Reproducible Paper Guidelines

Cited by 6 publications

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Publishing computational research &#8211; A review of infrastructures for reproducible and transparent scholarly communication

Publishing computational research &#8211; A review of infrastructures for reproducible and transparent scholarly communication

Reproducibility and replicability: opportunities and challenges for geospatial research

Practical Reproducibility in Geography and Geosciences

Contact Info

Product

Resources

About

Publishing computational research – A review of infrastructures for reproducible and transparent scholarly communication

Publishing computational research – A review of infrastructures for reproducible and transparent scholarly communication