IOP Publishing (IOPP) is advancing open science and research impact by assigning Digital Object Identifiers (DOIs) to supplementary data files submitted alongside research papers. This initiative will make supplementary materials more Findable, Accessible, Interoperable, and Reproducible (FAIR), ensuring that authors receive greater recognition for their contributions beyond the primary research article.

A 2020 study demonstrated that articles with linked data receive a citation advantage, showing the value of this initiative. Supplementary files are often not easily discoverable or citable, which limits their impact.  

Benefits for authors and researchers:

• Increased recognition and credit: Supplementary files will become formally citable, allowing authors to gain recognition for a broader range of research outputs.

• Enhanced discoverability: Data will be prominently linked on article pages, have its own dedicated ‘article’ pages on IOPscience, and be easily found through search engines.

• Support for funder open science policies: Authors will be better supported to meet some funders’ requirements to publicly share data associated with publicly funded research.

“Assigning DOIs to supplementary data is another step for IOPP toward making research more transparent and interconnected. It will help authors get the credit they deserve for more aspects of their work while making it easier for them to find and access relevant data. This initiative advances our journey toward a more FAIR research ecosystem and strengthens our commitment to open science, aligning with the global shift toward open data and scientific reproducibility,” says Daniel Keirs, Head of Journal Strategy and Performance at IOP Publishing.

IOPP’s decision to assign DOIs to supplementary research data was taken in response to feedback from the research community. A survey of researchers publishing with IOPP found that they see improving links between articles and relevant data as one of their highest priorities for publishers. Researchers also expressed their support for assigning persistent identifiers to supplementary data after it was trialled on selected journals.

An opportunity not to be missed! MDPI Books warmly invites all Social Sciences, Arts, and Humanities (SSAH) researchers to submit a proposal to its inaugural book competition. The winning entries will be published free of charge on the MDPI Books platform. The selected authors will be able to showcase their expertise to a global audience, contributing to broader conversations on the role of SSAH in addressing key global challenges.

Entries will be judged by subject experts from MDPI Books. The judges are looking for entries that make an important contribution to knowledge and demonstrate the following:

• An original contribution to the field;
• A clear, well-structured argument;
• Methodological soundness;
• Relevance to current societal or academic debates and clear engagement with the state of the art;
• Interdisciplinary potential.

Selected proposals will be invited to proceed to the next stage, which includes peer review in accordance with MDPI Books’ editorial standards.

Submissions are now open, closing on 31 August 2025.

“Researchers in the Social Sciences, Arts, and Humanities (SSAH) make substantial contributions to public discourse and explore topics of broad public interest,” says Laura Wagner, head of books division at MDPI. “However, they often work within formats such as books and may have limited financial resources for open access publishing. At MDPI, we recognize both the value of their work and the challenges they face and we are committed to supporting greater accessibility and impact in these fields. The competition will broaden accessibility and impact in these fields of research by providing the opportunity to publish in open access at no cost to the authors, helping their work reach wider audiences.”

Eligibility

• The competition is open to researchers working within the Social Sciences, Arts, and Humanities.
• Proposals can be submitted by an individual or predefined team of authors.
• Both monographs and edited volumes with a clear, coherent concept are eligible. 
• Proposed books should aim for a length of between 30,000 and 90,000 words.
• All proposals must be original, unpublished, and intended for open access publication under a CC BY license with MDPI Books.
• There are no restrictions based on career stage, geographic location, or institutional affiliation.

Submitting a Proposal

Entries can be made by completing an online application form, following the Guidelines for Manuscript Submission. All proposals must clearly indicate they are being submitted for the ‘Social Sciences, Arts and Humanities Book Competition’. Book publication is contingent on successful peer review and final approval processes. Authors of non-selected proposals will be contacted to explore alternative funding options or publication pathways with MDPI Books.

Are All Papers Created Equal?

And Why Are We Insisting on Treating Them as Such?

For an industry that prides itself on progress, scientific publishing has a strange habit of rewarding conformity.

Every year, over three million scientific papers are published—a figure that doubles roughly every nine years. This massive output rests on the assumption that each publication adds a measurable contribution to the world’s knowledge base. But in practice, the academic system treats nearly all papers the same, relying on blunt proxies like citation counts, journal prestige, and impact factors to infer value.

These metrics reward safe, incremental research. Paradigm-challenging work, which by nature resists easy categorization or immediate validation, often lingers in obscurity. Many of the most important ideas in science were first ignored, misunderstood, or marginalized—and the current system does little to surface such work earlier.

That gap is what a new platform called Preprint Watch is trying to address. Instead of using citations as a proxy for importance, Preprint Watch classifies scientific papers based on their epistemic role—where they fall in the broader arc of scientific development. The tool doesn’t care how many people are reading a paper. It’s looking for signs that a preprint may indicate the early stages of a conceptual shift.

At the heart of the platform is a deep-reasoning agent called iKuhn, named after philosopher Thomas Kuhn, whose 1962 book The Structure of Scientific Revolutions outlined how science progresses through periodic upheavals rather than smooth accumulation. Preprint Watch applies this model on a set of semantic ontologies that classify preprints according to where they contribute to the so-called Kuhnian cycle:

• Normal Science (refinement within a dominant model)
• Model Drift (early signs of theoretical stress)
• Model Crisis (systematic contradictions)
• Model Revolution (emergence of alternative frameworks)
• Paradigm Shift (replacement of the reigning model)

These classifications are assigned algorithmically by analysing the full text of preprints from sources like arXiv, bioRxiv, and medRxiv. The result is a signal that is fundamentally distinct from bibliometric signals like citation count, views, or downloads. This signal tracks the progress of science across disciplines, something that researchers never thought possible.

For now, the platform delivers these signals via a public reporting feed and monthly digest. But the broader goal is to offer decision-makers—funders, publishers, R&D managers—an early detection and reconnaissance system for scientific research and discovery. “Even a 0.1% failure to detect disruptive research equates to billions of dollars in misallocated funding,” says co-founder Dr. Khalid Saqr. “This isn’t just about science—it’s about capital efficiency.”

This May, Saqr, engineering simulation expert and founder of KNOWDYN, launched Preprint Watch with Dr. Gareth Dyke, a renowned palaeontologist and former publishing executive with over 300 academic papers to his name. Together, they built the platform as a response to the limitations they saw in both academic gatekeeping and automated research tools. Their aim is to offer a new layer of epistemic inquiry to evaluate scholarly communication focused on epistemic contribution and position in the progress of science.

One of the most compelling aspects of the project is how little it asks of the user. It doesn’t require researchers to change how they write, publish, or tag their work. Instead, it reinterprets the research using a well-established philosophical model, translated into a computational framework.

In 2026, the team plans to introduce the Thomas Kuhn Prize, an annual award for the most disruptive preprint surfaced by the system. Unlike traditional prizes, this won’t be based on votes or nominations: The goal is to reward papers that challenge the foundations of their field—particularly those coming from outside elite institutions.

Though still early in its lifecycle, Preprint Watch is attracting interest among researchers sceptical of current incentives. It accepts preprint submissions freely from the scientific community, while the system is continuously monitored for signal anomalies. But the broader idea—that epistemic contribution deserves its own measurement standard—is gaining traction. After the pandemic, preprints are increasingly becoming vital social contracts that researchers, funders, and policymakers rely on to act without having to wait the peer review stamp from slow journals and inefficient society committees.

Critics may question whether a machine can accurately apply Thomas Kuhn reasoning and classify scholarly communications, or whether any system can reliably detect innovation in real time. But the platform’s creators are quick to clarify that they’re not claiming to predict Nobel prizes. “We’re not scoring papers,” Dyke explains. “We’re contextualizing them—mapping their relationship to the conceptual structures they affirm, extend, confront, or destabilize.”

The reality is: What emerges from Preprint Watch is not a ranking rubric as it may seem, but an entirely new type of content. The classification reports are well structured, explainable, and inspects preprints with a critical lens that provide immediate call to action for the stakeholders of science. It may also offer a supplementary decision-support feed to improve editorial judgment, reduce funding waste, and to make discovery pipelines more responsive to underlying shifts in scientific knowledge.

Of course, this kind of signal intelligence isn’t infallible. But that’s beside the point. What matters is that Preprint Watch is trying to measure something most platforms ignore: the trajectory of ideas, not just their afterglow.

If it works, it could help fix one of the most persisting inefficiencies in science. If it doesn’t, it still asks a question worth repeating: Are all papers created equal? Because the future of scientific progress may depend on how we choose to answer it.