Knowledge Sharing with Tim Vines: How DataSeer is Revolutionizing Editorial Checks and Research Integrity

by Mike Groth

I sat down with Tim Vines, Founder and CEO of DataSeer, a KGL Smart Review integration partner, to discuss how AI is transforming editorial workflows and research integrity. DataSeer’s technology automates checks for data sharing, reporting, and reproducibility, ensuring manuscripts run through Smart Review meet rigorous standards.

Tim is a recognized leader in scholarly publishing, with a deep background in peer review, data sharing, and reproducibility. Beyond his leadership roles, Tim contributes to The Scholarly Kitchen and has published extensively on peer review and open science—his work has even been featured in Vanity Fair. With a PhD in evolutionary ecology from the University of Edinburgh, he brings a researcher’s perspective to the challenges publishers face today.

In this Q&A, Tim shares insights on DataSeer’s latest innovation, SnapShot—an AI-powered tool that streamlines editorial checks, enhances research integrity, and helps journals enforce policies efficiently.

MG: Can you tell us a bit about DataSeer’s SnapShot product and how it works?

TV: DataSeer SnapShot is an AI-powered editorial tool that streamlines journal checks and sendbacks, increases consistency, and helps to reinforce journal policies and research integrity best practices. In doing so it both improves published output quality and frees editors to focus on things that really require their expertise.

In terms of user experience, SnapShot works within an editorial publishing platform to scan each submitted manuscript. It returns a top-level research integrity score backed by an itemized list of checks, and author-ready revision instructions for each issue identified. Manuscripts that meet the journal’s threshold requirements for research integrity can advance automatically to peer review, which cuts down on key metrics like time-to-first-decision. The system can send customized feedback to the authors of manuscripts with moderate issues, coaching authors to success, and checking revisions to make sure changes are implemented correctly. Very serious issues can be routed to journal staff for further review or desk rejection. The tool is incredibly flexible, capable of applying the same criteria across a portfolio, or tailoring it based on specific journal or article-type requirements.

SnapShot works by ingesting the full text of each submitted manuscript and using a mixture of Language Models and traditional Natural Language Processing tools to determine whether the manuscript text meets the journal’s criteria. We can answer very nuanced questions. For example, DataSeer checks not just whether a data availability statement is present but also: Is data available? Is it in an approved repository? Does it include the files we would expect given the type of paper? Do the links work? If data isn’t shared, have the authors provided a valid reason why not? That’s true for a variety of metrics including code sharing, protocols, preprints, and others.

MG: With SnapShot embedded into KGL’s Smart Review, how will KGL customers (editors/reviewers/authors) benefit from this integration?

TV: I had the idea for DataSeer while manually checking manuscripts for data policy compliance at the journal Molecular Ecology. Instead of going through each article line-by-line for 30 minutes or more, I wondered, why not have AI do the same job in seconds? Five years on, SnapShot is a natural evolution of that first concept — faster, with checks that go beyond data alone, with a customizable in-built triage hierarchy, and flexible and intelligent author support mechanisms.

DataSeer SnapShot saves on editorial time and operational budget and keeps article standards consistently high, adhering to journal policy, and contributing to a reputation for quality and reliability. Because SnapShot integrates with publishing platforms, it’s much easier for journals to test, implement and scale across a portfolio with minimal transition cost.

Editors and journal staff benefit from reduced administrative burden, more efficient use of their time and expertise, and an overall higher-quality published output. Authors benefit from faster review times, clear and rapid just-in-time instructions and support, and a finished article with all the signals of quality and integrity likely to increase discovery and usage.

MG: How does DataSeer help solve some of the challenges publishers are facing around data sharing and research integrity, particularly around peer review?

TV: There are several factors at play. Publishers are under enormous pressure to address research integrity issues, such as articles that can’t be validated or reproduced, rising papermill output, increased fraud. At the same time, funders are strengthening their open science policies to maximize the impact of their grants. And the overall volume of published literature continues to increase year-on-year.

To address research integrity concerns and support funder requirements, many publishers have adopted open science and research integrity policies of their own — policies they now have to enforce through editorial checks. At a certain point it just isn’t feasible to handle all that screening manually.

AI and LLM technologies are game changers in this regard. These solutions are capable of much more sophisticated, granular, and accurate screening that has previously been possible, at a fraction of the cost of manual checks. This isn’t simply another report that editorial staff must then review and action; depending on journal submissions, a certain percent of articles can move through the SnapShot with no need for direct human intervention.

MG: One of SnapShot’s USPs is that it helps publishers save time on editorial checks – can you provide any real world examples of these efficiency savings in action?

TV: As tested by the KGL team and the DataSeer publishing clients, often manual data-related checks can take up to 20-30 minutes per article to confirm authors have adhered to journal policy. DataSeer Snapshot delivers results in seconds, and flags problematic articles for deeper human analysis. Snapshot will also give suggested text which editors can use, or send automatically, and has strong reasoning traces (why decisions were made). We are only just touching the surface of the potential to both save editorial time, and significantly improve the quality, transparency, and consistency of published works.

MG: DataSeer has forged collaborations with a range of publishers and service providers – how would you describe the company’s role in shaping the future of Open Science and scholarly publishing?

TV: Forward-looking publishers, funders, and researchers have embraced a shared vision for how open science practices like data sharing, code sharing, preprints, and preregistration can shape a new scholarly communications ecosystem that is more efficient, reproducible, trusted, and fair. But how we as an industry can realize those goals is less clear. One of our partners, Rebecca Taylor-Grant, Head of Open Data Initiatives at Taylor & Francis, has spoken about their approach and working with DataSeer and authors: “Taylor & Francis is committed to encouraging and supporting authors to adopt open research practices, which have a key role in promoting the integrity, reproducibility and reusability of research,” “We’re excited by the potential of DataSeer’s tools to help authors follow open research requirements more consistently and to give us valuable insights into open research practices across our portfolio.”

DataSeer’s technologies bridge the gap between vision and action, policy and practice. Our affordable AI editorial support solutions make manuscript checks, open science monitoring, researcher support, and policy enforcement practical and affordable for organizations of all sizes. We are a partner. Our aim is to empower publishers, funders, and other stakeholders to implement their vision in a consistent, scalable way.

KnowledgeWorks Global Ltd. (KGL) is the industry leader in editorial, production, online hosting, and transformative services for every stage of the content lifecycle. We are your source for society services, market analysis, intelligent automation, digital delivery, and more. Email us at info@kwglobal.com.