Millions of researchers could be affected by a “dramatic distortion of citation counts” likely caused by flaws in how the academic publishing giant Springer Nature handles article metadata, accordi…

Här samlas den viktigaste information om de aktörer, resurser och styrdokument som är centrala för en svensk övergång till ett öppet vetenskapssystem. Portalens mål är att vara en levande webbplats so...

Falska, massproducerade och AI-genererade forskningsartiklar skapar en vetenskaplig kris, menar forskare. En ny plan i fyra punkter ska komma åt problemet.

DOKUMENT<br />Fastigheten Norra Djurgården 1:1, Tekniska Högskolan Hus 3, Norra Djurgården, Byggnadsinventering, 1992<br />Stockholms stadsmuseum, Sweden

Scientific discovery relies on innovative software as much as experimental methods, especially in proteomics, where computational tools are essential for mass spectrometer setup, data analysis, and interpretation. Since the introduction of SEQUEST, proteomics software has grown into a complex ecosystem of algorithms, predictive models, and workflows, but the field faces challenges, including the increasing complexity of mass spectrometry data, limited reproducibility due to proprietary software, and difficulties integrating with other omics disciplines. Closed-source, platform-specific tools exacerbate these issues by restricting innovation, creating inefficiencies, and imposing hidden costs on the community. Open-source software (OSS), aligned with the FAIR Principles (Findable, Accessible, Interoperable, Reusable), offers a solution by promoting transparency, reproducibility, and community-driven development, which fosters collaboration and continuous improvement. In this manuscript, we explore the role of OSS in computational proteomics, its alignment with FAIR principles, and its potential to address challenges related to licensing, distribution, and standardization. Drawing on lessons from other omics fields, we present a vision for a future where OSS and FAIR principles underpin a transparent, accessible, and innovative proteomics community.

For years, we’ve been working under the name OurResearch. That name sat at the top of our org chart, with three child projects under it: OpenAlex, Unpaywall, and Unsub. Starting today, things are simp...

AI web harvesting bots are different from traditional web crawlers and violate many of the established rules and practices in place. Their rapidly expanding use is emerging as a significant IT managem...

Open data sources such as Crossref, DataCite, ORCID, OpenAlex, OpenCitations, and many others offer important opportunities to perform scientometric analyses in more transparent, inclusive, and reprod...

As part of the American Statistical Association project assessing and monitoring the health of the federal statistical agencies, the project team is launching a “Citizen Science” project. This project...

Elicit.com, Consensus, and Undermind.ai are among the new leading comprehensive cross-disciplinary “AI-powered academic search engines” today.