The role of metadata in reproducible computational research

Leipzig, Jeremy; Nüst, Daniel; Hoyt, Charles Tapley; Ram, Karthik; Greenberg, Jane

doi:10.1016/j.patter.2021.100322

Cited by 64 publications

(33 citation statements)

References 213 publications

(289 reference statements)

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“…We refer to [72] for a comprehensive overview and recommendations, in particular for data; notably that review highlights the wide variety of metadata and documentation that the literature prescribes for enabling data reuse. Likewise, we suggest [82] that covers the importance of metadata standards in reproducible computational research.…”

Section: Related Workmentioning

confidence: 99%

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Packaging research artefacts with RO-Crate

Soiland‐Reyes

Sefton

Crosas

et al. 2022

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An increasing number of researchers support reproducibility by including pointers to and descriptions of datasets, software and methods in their publications. However, scientific articles may be ambiguous, incomplete and difficult to process by automated systems. In this paper we introduce RO-Crate, an open, community-driven, and lightweight approach to packaging research artefacts along with their metadata in a machine readable manner. RO-Crate is based on Schema.org annotations in JSON-LD, aiming to establish best practices to formally describe metadata in an accessible and practical way for their use in a wide variety of situations. An RO-Crate is a structured archive of all the items that contributed to a research outcome, including their identifiers, provenance, relations and annotations. As a general purpose packaging approach for data and their metadata, RO-Crate is used across multiple areas, including bioinformatics, digital humanities and regulatory sciences. By applying “just enough” Linked Data standards, RO-Crate simplifies the process of making research outputs FAIR while also enhancing research reproducibility. An RO-Crate for this article11 https://w3id.org/ro/doi/10.5281/zenodo.5146227 is archived at https://doi.org/10.5281/zenodo.5146227.

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Section: Related Workmentioning

confidence: 99%

“…RO-Bundle evolved to Research Object BagIt archives, 82 a variant of RO Bundle as a BagIt archive [74], used by Big Data Bags [25], CWLProv [68] and WholeTale [26,76].…”

Section: Bundling and Packaging Digital Research Artefactsmentioning

confidence: 99%

Packaging research artefacts with RO-Crate

Soiland‐Reyes

Sefton

Crosas

et al. 2022

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“…), statistical reports and notebooks (e.g., session variables, parameters), pipelines (dependencies between tools, provenance), and the resulting scientific publication (research domain, keywords, attribution etc. ), see (Leipzig et al, 2021) for an overview.…”

Section: Metadatamentioning

confidence: 99%

Bagman – A Tool that Supports Researchers Archiving Their Data

Zinn¹

2022

Linköping Electronic Conference Proceedings

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“…More details are available elsewhere. 19,[29][30][31] Raw data versus analysis-ready data Make both raw and analysis-ready data available. Raw data are the first format of data provided before any cleaning has taken place (e.g., data in some binary or proprietary format).…”

Section: Metadatamentioning

confidence: 99%

Common-sense approaches to sharing tabular data alongside publication

Tierney

Ram

2021

Patterns

Self Cite

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Summary Numerous arguments strongly support the practice of open science, which offers several societal and individual benefits. For individual researchers, sharing research artifacts such as data can increase trust and transparency, improve the reproducibility of one's own work, and catalyze new collaborations. Despite a general appreciation of the benefits of data sharing, research data are often only available to the original investigators. For data that are shared, lack of useful metadata and documentation make them challenging to reuse. In this paper, we argue that a lack of incentives and infrastructure for making data useful is the biggest barrier to creating a culture of widespread data sharing. We compare data with code, examine computational environments in the context of their ability to facilitate the reproducibility of research, provide some practical guidance on how one can improve the chances of their data being reusable, and partially bridge the incentive gap. While previous papers have focused on describing ideal best practices for data and code, we focus on common-sense ideas for sharing tabular data for a target audience of academics working in data science adjacent fields who are about to submit for publication.

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The role of metadata in reproducible computational research

Cited by 64 publications

References 213 publications

Packaging research artefacts with RO-Crate

Packaging research artefacts with RO-Crate

Bagman – A Tool that Supports Researchers Archiving Their Data

Common-sense approaches to sharing tabular data alongside publication

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