A global framework that identifies hidden risks in university research systems, reveals integrity vulnerabilities overlooked by traditional rankings, and enables better institutional and policy decisions.
International Research Integrity Conference | NEXT CONFERENCE 2027
Research Integrity and Peer Review
Research Integrity and Peer Review is an open access journal led by a renowned Editorial Board and occupying a unique niche in the field as the only journal ...
The History Crisis Is a National Security Problem
As universities shed scholars, key learning disappears.
When the Scoreboard Becomes the Game, It’s Time to Recalibrate Research Metrics - The Scholarly Kitchen
Today's guest post discusses research metrics and their relationship to research integrity, inclusivity, and long-term impact.
Position paper: persistent identifiers in research infrastructure policy - Crossref
PIDs have become central to national and international open research strategies, but identifiers alone cannot deliver the connected, open record that researchers, institutions, funders, publishers, and policymakers depend on. Effective research infrastructure rests on three interdependent elements: open, persistent identifiers; rich, open, and linked metadata; and the sustainable governance and resilient operation of the organisations involved. Crossref urges policymakers to evaluate all three together.
Reformation of science publishing: the Stockholm Declaration
Science relies on integrity and trustworthiness. But scientists under career pressure are lured to purchase fake publications from ‘paper mills’ that use AI-generated data, text and image fabrication. The number of low-quality or fraudulent publications is rising to hundreds of thousands per year, which—if unchecked—will damage the scientific and economic progress of our societies. The result is editor and reviewer fatigue, irreproducible experiments, misguided experiments, disinformation and escalating costs that devour funding from taxpayers intended for research. It is high time to reevaluate current publishing models and outline a global plan to stop this unhealthy development. A conference was therefore organized by the Royal Swedish Academy of Sciences to draft an action plan with specific recommendations, as follows. (i) Academia should resume control of publishing using non-profit publishing models (e.g. diamond open-access). (ii) Adjust incentive systems to merit quality, not quantity, in a reputation economy where the gaming of publication numbers and citation metrics distorts the perception of academic excellence. (iii) Implement mechanisms to prevent and detect fake publications and fraud which are independent of publishers. (iv) Draft and implement legislations, regulations and policies to increase publishing quality and integrity. This is a call to action for universities, academies, science organizations and funders to unite and join this effort.
Community for Rigor
Reliable research can be complicated to create. So we made a network of essential resources to help you better understand the principles and practices of scientific rigor.Why trust us? Because we’re a team of students, post-grads, professors, and professionals who know what it’s like to be right where you are.
Clear Skies – Your partner in research integrity
Ten quick tips to SNIFF out sustainable and secure scientific software
Modern computational biology depends heavily on open-source software tools, analysis pipelines, and containerized workflows developed and shared by the research community. While there is extensive guidance (including Quick Tips and Simple Rules articles) on how to build robust and sustainable scientific software, far less has been written for researchers in the role of software users evaluating whether an existing tool is reliable, secure, and sustainable enough for their work. Here we present ten quick tips to help researchers critically assess the tools they adopt. Our tips are organized around a framework that centers on key evaluation features: source, network, interaction, fit, and fragility (SNIFF). These dimensions prompt researchers to consider who maintains a tool and why, whether it is embedded in a broader ecosystem, how actively its developers and users engage, whether it matches the intended use case and licensing requirements, and how robust its dependencies and security practices are. By applying these tips, researchers can make more informed decisions, reduce the risk of relying on abandoned or insecure software, and contribute to a more sustainable scientific software ecosystem.
Scientific sleuths come in from the cold
Research integrity investigators are starting to organize, but the field, and the people, remain idiosyncratic
Distributed Denial of Science: How Indirect Data Poisoning of AI Systems Can Industrialize Scientific Fraud
Scientific fraud is the instrument of doubt that malicious entities can use to establish controversy in science. Historically, it required the resources of a company: deep pockets, ghostwritten articles, and corrupt academics. Today, Artificial Intelligence (AI) is increasingly automating scientific research, so we ask: Can a remote adversary weaponize the honest use of AI in science to compromise scientific integrity? We envision and empirically evaluate a new attack, indirect data poisoning, in which an adversary corrupts an open dataset and uploads the poisoned variant to a public repository. Autonomous research agents may independently retrieve and process this data, turning honest scientists into the unpaid and unwitting distributors of fraud at scale. Across five socially-salient topics, from hiring discrimination to the safety of autonomous vehicles, three widely used frontier AI systems (Claude Code with Claude Opus 4.7, Codex with GPT-5.5, Gemini CLI with Gemini 3.1 Pro), and 450 ethically contained experimental runs, we find that poisoning succeeds in 49.56% of runs, while the rate of poisoning detection is only 6.0%. The attack requires no topic-specific trigger-words, agent access, indirect prompt injection, or fabricated papers, only the open data ecosystem and misleading metadata. To mitigate the attacks, we propose and evaluate two measures: a scientist persona and a data provenance audit with five checks (referencing papers, social markers, statistical anomalies, related datasets, poisoning caution). We find that the persona still leaves 16.67% of runs with a poisoned conclusion, but provenance auditing reduces attack success rate to zero. Our results suggest that indirect data poisoning may enable scientific fraud at unprecedented scale, but these attacks can be mitigated with suitable auditing by agents during data retrieval.
A Data Utopia for Science-of-Science
Here I want to briefly sketch out a vision for how to solve a key set of problems facing science-of-science researchers, using the relatively new idea of a ‘data trust.’ In my ideal wor…
Science Integrity Digest
A blog about science integrity, by Elisabeth Bik, for Harbers-Bik LLC. Support my work at Patreon.com/elisabethbik
