Imagetwin Partners with Aries Systems to Enable Image Integrity Screening in the Editorial Workflow
Aries Systems Corporation, a leading provider of workflow management technologies for the scholarly publishing community, and Imagetwin, a trusted AI-powered image integrity software for research, are pleased to announce their partnership to strengthen trust in publishing through streamlined research image screening.
Research integrity is an increasingly complex and critical challenge within scholarly publishing. Ensuring research figures are credible within each article is typically a highly manual and time-consuming bottleneck for journals, and visual review by the human eye often fails to catch problematic cases. Without advanced support and additional resources, inconsistent image integrity investigations can result in frustrating delays and expensive post-publication corrections. To automate this process and minimize downstream risk, Aries Systems and Imagetwin have partnered to integrate their AI-powered image analysis software with Editorial Manager® (EM), the leading manuscript submission and peer review tracking system.
Upon submission and revision, articles in EM are automatically scanned by Imagetwin within seconds against their database of 160+ million published figures to identify potential instances of manipulation, duplication, plagiarism, or AI-generated content. From their existing workflow in EM, Editors can seamlessly access Imagetwin’s generated confidence score and sophisticated forensic toolbox for detailed examination of flagged images. Publishers also have the option to create a private repository of their own past papers to screen submissions against that archive alongside the full Imagetwin database – further promoting transparency and legitimacy in scholarship.
Pierre Montagano, Aries’ Director of Business Development says:
“Supporting trust in publishing remains a strategic priority for Aries, and we are thrilled to bolster this commitment as Imagetwin joins our suite of research integrity solutions within the Aries ecosystem. This powerful integration enables the detection of image issues early, consistently, and efficiently at scale – relieving editorial pressure and driving confidence in manuscript screening.”
Patrick Starke, Imagetwin’s Co-Founder and CEO adds to that:
“Editorial Manager is where the majority of manuscript decisions happen, so bringing image integrity screening directly into that workflow is a natural fit. This partnership means editors get flagged issues before publication, not after, which is exactly where the industry needs to be heading.”
About Aries Systems | www.ariessys.com
Aries Systems transforms and revolutionizes the delivery of high-value content to the world. We are committed to providing highly customizable, flexible, and innovative workflow solutions designed to help enhance the discovery and dissemination of human knowledge. Publish faster, publisher smarter, with Aries Systems.
Frequently asked questions
How does Imagetwin detect image integrity issues in Editorial Manager?
Within seconds of submission, Imagetwin checks manuscript figures against a database of 160+ million published images to flag potential manipulation, duplication, plagiarism, or AI-generated content. Editors then get a confidence score and access to Imagetwin’s forensic toolbox directly from their EM dashboard for closer review of any flagged figures.
What is the Imagetwin and Aries Systems partnership?
Imagetwin has integrated its AI-powered image integrity screening directly into Editorial Manager® (EM), the manuscript submission and peer review platform from Aries Systems. Manuscripts submitted or revised in EM are automatically scanned by Imagetwin, so editors can review flagged image issues without leaving their existing workflow.
Can publishers screen against their own archive, not just Imagetwin's database?
Yes. Publishers can build a private repository of their own previously published papers and screen new submissions against that archive in addition to the full Imagetwin database, useful for catching duplication or self-plagiarism within a publisher’s own journals.
