KEY TAKEAWAYS

• Most open access repositories have evolved without sufficient means to communicate corrections or retractions.
• Metadata, such as DOIs, could be used to link all article versions and ensure corrections/retractions are clearly indicated to readers.

Open access repositories have an important role in disseminating scientific research. But what happens when a journal corrects or retracts a publication? A recent LSE Impact Blog article describes Frédérique Bordignon’s alarming discovery around how well this is captured by repositories.

Open repositories’ ‘blind spot’ to corrections and retractions

As Bordignon explains, most journals display up-to-date editorial notices alongside publications, although clarity can vary. On the other hand, open repositories do not necessarily pull through information on correction/retraction from published counterparts, and guidance from the Confederation of Open Access Repositories is lacking.

To examine the topic further, Bordignon’s team conducted a manually verified analysis of the world’s second largest institutional repository, HAL, by cross-checking its records against 24,430 corrected or retracted publications extracted from the Crossref x Retraction Watch database. Shockingly, they found that 91% of corrections/retractions were not indicated in the repository. Bordignon emphasises that this situation is not unique to HAL, but reflective of repositories across the world.

“91% of corrections/retractions were not indicated in the repository…this situation is…reflective of repositories across the world.”

How to ‘fill the gap’ in effective reporting of corrections

The solution? Bordignon points out that open repositories have a powerful opportunity to ‘fill the gap’ in effective reporting of corrections. However, rather than expecting repository managers to make individual version control decisions for every publication, Bordignon suggests that open repositories:

• create their own archives
• clearly display the editorial status of each article
• include a permanent, bidirectional link to the corrected published version
• enable automated updates through partnerships with Crossref x Retraction Watch, making use of metadata such as digital object identifiers
• incorporate platforms that detect and report retractions, such as PubMed, PubPeer, and Scite.

Bordignon provides a stark reminder that omission of corrections/retractions notices from open repositories risks that users may be learning, citing, or even propagating, flawed science; this can ultimately “erode public trust in science”. She urges open repositories to galvanise their position in the fight for research integrity, paving the way for a more streamlined archiving system that leaves readers in no doubt as to the reliability of the information they are accessing.

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KEY TAKEAWAYS

• Current mandates for responsible data sharing aim to make data findable, accessible, interoperable, and reusable (FAIR), but are not always effective.
• More action may be needed to develop metadata standards that ensure research data are truly FAIR.

Data-sharing mandates aim to make research outputs more accessible to allow verification of results and further analyses.

Horizon Europe, the European Union’s programme for research and innovation funding, mandates that almost all data must be FAIR:

• Findable
• Accessible
• Interoperable
• Reusable.

Further, in August 2022, the US government announced a policy that federal-funded research articles and most underlying data should be made freely available, to be implemented by 2025.

Despite these efforts, Professor Mark A. Musen has shared concerns about the ad hoc nature of metadata and the difficulties in finding online data sets, arguing that few data sets are actually FAIR. He describes how current metadata often contain only administrative and organisational information without any useful experiment-specific descriptors, forcing researchers to search records manually, a time-consuming and often futile task.

“The research community must commit to creating discipline-specific standards for metadata and to applying them throughout the scientific enterprise.” – Professor Mark A. Musen, Professor of Medicine (Biomedical Informatics) and Biomedical Data Science, Stanford University, California

Prof. Musen highlights potential solutions to optimise data sharing but acknowledges that these come with certain difficulties. For example:

• Referencing data sets in published manuscripts: allows inclusion of experimental details, although data may not be deposited in a form that is easy to understand; additionally, not all manuscripts are accepted for publication.
• Technology: the CEDAR Workbench is a tool that automatically generates metadata forms to help describe particular types of biomedical experiments in a standardised way; however, the tool is only useful in scientific fields with at least basic metadata standards – something Prof. Musen believes is lacking.
• Dedicated workshops: ZonMw, a funding agency in the Netherlands, hosts workshops to develop FAIR metadata standards for its grant recipients to use; however, these workshops are costly (approximately €40,000 for the development of a single standard).

Prof. Musen concludes that FAIR data will need a huge investment and development of standards that go much further than simple mandates.

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Some examples of metadata, or data that provide information about other data, are familiar in medical publishing. Digital object identifiers (DOI), for example, allow easy location of digital content, and are linked to other metadata embedded within an article. This may include tags identifying the title, author, journal and International Standard Serial Number (ISSN). Such metadata are used by programs like Altmetric to track online activity surrounding a unique publication. However, current processes are not allowing the full potential of metadata to be realised in the evolving scholarly communications landscape.

Metadata 2020 is an international collaboration involving stakeholders from across scholarly communications.

Metadata 2020’s mission involves “advocating for richer, connected, and reusable, open metadata for all research outputs in order to advance scholarly pursuits for the benefit of society”.

This work builds on that of Crossref, which facilitates the finding, citing, linking and reuse of research outputs by tagging such content with metadata. In an article in the Journal of Research Ideas and Outcomes, Kathryn Kaiser et al lay out the Metadata 2020 Principles for the use of metadata in scholarly communications.

The Metadata 2020 Principles

For metadata to support the community, it should be:

Compatible: provide a guide to content for machines and people.

• Metadata must be as open, interoperable (allowing information exchange), parsable (containing characters that can be broken down into recognisable components analysable by a computer), machine actionable (structured for recognition by computer programmes), and human readable as possible.
• Persistent identifiers (PIDs), such as ORCID ID, should be used to support interoperability. In contrast, a URL link is not a PID: it can break and so does not reliably refer to a digital entity.

Complete: reflect the content, components and relationships as published.

• To achieve this, metadata must be as complete and comprehensive as possible.

Credible: enable content discoverability and longevity.

• To meet this principle, metadata must be of clear provenance, trustworthy and accurate.

Curated: reflect updates and new elements.

• The authors note that metadata will always be evolving, so metadata must be maintained and updated over time.

These principles aim to shape a common understanding around the metadata needed to support scholarly communications. The authors note that the language of metadata may be specific to a particular discipline, so best practice approaches must allow flexibility in metadata use across communities. In addition, existing metadata standards should be considered and re-used as much as possible to improve the interoperability of different metadata schema, while minimising redundancy.

Applying these principles may also help stimulate further development of ideas and workflows in the scholarly ecosystem. The future work of the Metadata 2020 group will focus on demonstrating the potential benefits of better metadata for stakeholders including researchers, through a set of Metadata Practices.

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Summary by Julianna Solomons PhD, CMPP from Aspire Scientific

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With thanks to our sponsors, Aspire Scientific Ltd and NetworkPharma Ltd