Understanding Open Access Publishing

Three more of the UK’s universities have just walked away from the Elsevier deal. (And honestly, I think more institutions will follow) We’ve normalised an unsustainable system where: - Taxpayers fund the research - Academics write the papers - Peers review them for free - Editors manage journals for free - Then universities pay AGAIN so staff can read the work And if we want to make our research open access so that the community doesn't have to pay to read it, we’re hit with £2,000–£4,000+ APCs per article That isn’t an “open access model”. It's a "pay-to-play model". The JISC national deal with the big 5 publishers was supposed to “solve” this and offer more affordable open-access publishing and reading for universities across the UK. Over the past few years, we spent £112m on these deals. Let this number sink in. I wonder, why won't we redirect this budget into shared and open infrastructure, building for example on Octopus[ac], that will support: - diamond open access - community-run outlets - pre-prints + repositories used as default Thoughts? #science #scientist #research #researcher #phd #postdoc #postdoctoral #professor #publishing #openaccess

⚠️💰 134 500 000 € for €lsevier from France 💸 France has just signed a "transformative agreement" with Elsevier https://lnkd.in/eaSr2PRh, and I believe this deserves our collective attention. As an Open Science enthusiast and co-founder of JTCAM: Journal of Theoretical, Computational and Applied Mechanics, I'd like to share some critical insights: 📊 The Agreement: Cost: 😮 €134.5 million over 4 years Covers 241 French institutions (44 of which are free of charge) Approximately €690,000 per paying institution 💰 To put this in perspective, compare it to annual public funding for various French institutions and organizations: + CCSD (HAL, ...): 0.4 M€ + Génopole - 7.3 M€ + ENSTA ParisTech - 20 M€ + Ecole des ponts - 32 M€ + ISAE - 44 M€ + Ecole polytechnique - 110 M€ + INRIA: 216 M€ CCSD with its HAL, Episciences and ScienceConf projects is a leading Open Science actor in France and Europe and its annual budget is only about 1% about 1% of the annual cost of Elsevier! 🤔 Critical Questions: + Why are we paying this exorbitant price for Open Access (OA) publishing with Elsevier while we have all the necessary infrastructure (HAL) and a will to share them without extra cost and an embargo period? + How will this agreement impact the future of scientific publishing and its costs? 🔍 Key Points: + France already has the necessary infrastructure for OA through HAL, without additional costs or embargoes thanks to the rights retention strategy adopted by France. + Despite opposition from some institutions (e.g., University of Lorraine), Elsevier has succeeded in selling its Gold OA under the guise of a "transformative agreement". + This is disappointing for Open Science, as France could have made all publications open without this agreement and its additional costs. + We could find a better use of this extra OA fee integrated in this contract, e.g. spend it on research funding and personnel. ⚠️ Hidden Costs: While we won't see direct OA publication fees as labs or researchers, these costs still exist. Be cautious when publishing OA articles, as the volume of these will likely influence negotiations in 4 years. 🌟 My Stance: I will not publish OA with Elsevier under this agreement. Instead, I encourage utilizing existing national infrastructures like HAL for true open access and publishing in Diamond Open Access journals like, for example, CR Mécanique and JTCAM: Journal of Theoretical, Computational and Applied Mechanics. 👩🔬 👨🔬 👩🏫 👨🏫 👩💻 👨💻 What are your thoughts? How will this agreement impact your publishing practices? Let's discuss the implications for the global scientific community. 🔗 For more information: Systematic analysis of these transforming agreements https://lnkd.in/eEeEGfB4 #OpenScience #ScientificPublishing #Research #TransformativeAgreements #AcademicPublishing #JTCAM

💡 Has science been helpful in providing measurement tools, especially indicators and metrics, to assess urban climate adaptation? Not yet. 🚀 While in Oslo for the Lead Authors Meeting of the IPCC Special Report on Climate Change and Cities, I’m pleased to share our latest article, now published in npj Urban Sustainability https://lnkd.in/eG2WT9J4 🪅 “Conventional approaches to indicators and metrics undermine urban climate adaptation” systematically examines how current measurement practices fall short of capturing real progress on adaptation in cities worldwide. Through a review of nearly 140 studies and more than 900 indicators and metrics, we uncover a highly fragmented measurement landscape that often fails to meet the needs of adaptation decision-making. Key findings include: 🧱 The dominance of input- and output-focused metrics that track effort and immediate results rather than long-term impact. 🏚️ A strong bias toward city-scale indicators, with far less attention to neighbourhood and household scales. 📜 Limited integration of governance, social, and economic dimensions in measurement frameworks. 🧠 A lack of theoretical grounding and practical guidance amid a sea of highly technical, uncontextualised proposals. 🫵 Insufficient attention to units of measurement, intended users, and real-world applications. This research is essential reading for scientist, practitioners, policymakers, and climate (adaptation) professionals seeking more meaningful urban adaptation, and more meaningful ways to measure it, for learning, accountability, and impact. Let's discuss. 💡 Indicators matter. In every field. But it’s not only about the indicator itself, it’s about the ecosystem of actors, applications, and interpretations around it. Global efforts such as the Global Goal on Adaptation (GGA) can help clarify measurement needs, but urban adaptation challenges are complex, cross-sectoral, and deeply interconnected. Much more work is needed to support practitioners, policymakers, and researchers in applying and learning from ongoing urban adaptations. 👉 https://lnkd.in/eG2WT9J4 #openaccess 🙏 This work has been a long time in the making, from early ideas, through a lengthy review process, to finally seeing it out. Huge thanks to all the co-authors (Andressa V. Mansur, Samraj Sahay, Ph.D, Laura Helmke-Long, Massimiliano Granceri Bradaschia, Ane Villaverde García, Leire Garmendia Arrieta, Prince Dacosta Aboagye, PhD, PISEP, Patricia Mwangi (PhD, MISK), William Lewis, Obed Asamoah, Patricia Mwangi (PhD, MISK), borja izaola, Dr Ellie Murtagh and Ira Feldman ) for their dedication, patience, and collaboration, and to International Platform on Adaptation Metrics for planting the seed that made this work possible. IMAGINE adaptation European Research Council (ERC) BC3 - Basque Centre for Climate Change 💭 Dr. Diana Reckien Dr Stacy-ann Robinson A/Prof Johanna Nalau Emilie Beauchamp Sean Goodwin

📣 𝐇𝐨𝐰 𝐢𝐬 𝐭𝐡𝐞 𝐞𝐱𝐩𝐞𝐫𝐢𝐞𝐧𝐜𝐞 𝐨𝐟 𝐜𝐥𝐢𝐦𝐚𝐭𝐞 𝐡𝐚𝐳𝐚𝐫𝐝𝐬 𝐥𝐢𝐧𝐤𝐞𝐝 𝐭𝐨 𝐜𝐥𝐢𝐦𝐚𝐭𝐞 𝐫𝐢𝐬𝐤 𝐩𝐞𝐫𝐜𝐞𝐩𝐭𝐢𝐨𝐧𝐬 𝐰𝐨𝐫𝐥𝐝𝐰𝐢𝐝𝐞? 🔥🌎 👉 Find out in my open access article published today in 𝘌𝘯𝘷𝘪𝘳𝘰𝘯𝘮𝘦𝘯𝘵𝘢𝘭 𝘙𝘦𝘴𝘦𝘢𝘳𝘤𝘩 𝘓𝘦𝘵𝘵𝘦𝘳𝘴: https://lnkd.in/daqEKJAM 🔧 𝐖𝐡𝐚𝐭’𝐬 𝐢𝐧 𝐭𝐡𝐞 𝐬𝐭𝐮𝐝𝐲? I analysed nationally representative survey data from 142 countries (N = 128,093) collected as part of World Risk Poll. The dataset includes information on whether (a) respondents experienced a climate-related hazard in the last five years, whether (b) they see climate change as a threat to their country in the next 20 years, and (c) a multidimensional resilience index combining individual, household, community, and societal resilience factors. 💡 𝐖𝐡𝐚𝐭 𝐝𝐢𝐝 𝐈 𝐟𝐢𝐧𝐝? 1️⃣ People who have experienced a climate-related hazard are more likely to consider climate change a 𝘷𝘦𝘳𝘺 𝘴𝘦𝘳𝘪𝘰𝘶𝘴 𝘵𝘩𝘳𝘦𝘢𝘵 compared to those who didn't within the same country. These effects are consistent across eleven hazard types and, for heatwaves, comparable in magnitude to the effect of having a university education. 2️⃣ At the same time, it is not the case that countries with widespread exposure to climate-related hazards show higher overall levels of climate risk perception. The data set allowed me to disentangle country-level patterns from the strong individual-effects described in 1️⃣ — in contrast to another recent large-scale study that did not measure individual-level exposure (but measured subjective attribution): https://lnkd.in/dk4rGVEt 3️⃣ Resilience does not clearly amplify or dampen the link between experience and perception. For some hazards, there seems to be a positive trend, for others a negative one. 4️⃣ There is marked variation between countries, and this appears to differ across hazards. For example, hurricanes, mudslides, and wildfires show similar effects across countries, while the effects of earthquakes, sandstorms, and droughts vary strongly across countries. 📄 The paper discusses these results, limitations, and avenues for future research: https://lnkd.in/daqEKJAM 🔥🌎 𝐖𝐡𝐚𝐭 𝐝𝐨𝐞𝐬 𝐭𝐡𝐢𝐬 𝐦𝐞𝐚𝐧 𝐟𝐨𝐫 𝐜𝐥𝐢𝐦𝐚𝐭𝐞 𝐚𝐜𝐭𝐢𝐨𝐧? Billions of people are already living with the impacts of climate change. As these experiences accumulate, we may see rising demand for climate action. But without political leadership and media that connect the dots, those experiences alone will not drive the transformation we need.

Flood science has historically been trapped between two extremes: hydrodynamic models that are highly accurate but computationally expensive, or global models that are too coarse (>1 km) to capture critical local vulnerabilities. Bridging this divide requires a fundamental shift from physics-based deduction to data-driven induction, a challenge that has defined my research over the last four years. This week, I am very happy to share that I have formalized this solution by submitting my Ph.D. thesis at Hong Kong Baptist University: "Towards GeoAI-based Data-driven Flood Management Solutions: A Synergistic Machine Learning and Earth Observation Framework" As illustrated, the thesis establishes a scalable GeoAI framework built on three synergistic pillars: 1. High-Dimensional Earth Observation (The Data) Leveraging multi-temporal global data streams (Landsat, Sentinel) to transition the field from data scarcity to data abundance. 2. Planetary-Scale Geo-Computation (The Platform) Utilizing cloud clusters (Google Earth Engine) and HPC (Shaheen-III) to democratize processing power, enabling the analysis of petabyte-scale geospatial data without traditional hardware constraints. 3. Machine Learning Analytics (The Engine) We systematically benchmarked 14 ML architectures to resolve the "accuracy-efficiency" trade-off, establishing a robust modeling engine. This framework was first operationalized across Pakistan's diverse landscapes to reveal that 95 million people reside in high-risk zones, before being scaled globally to produce the first harmonized 30 m flood susceptibility baseline. The Output: Global Flood Susceptibility Map (GFSM v1) By applying a climate modeling scheme (across 192 climate zones), we produced the first globally harmonized, 30 m resolution flood susceptibility baseline derived entirely from open-access data. This research addresses the "data equity deficit" in the Global South, where 89% of flood-exposed populations reside, often without high-resolution risk data. Next Steps: I will be releasing the open-source code, the GFSM v1 dataset, and the GEE web applications in the coming weeks. If you are interested in the work, feel free to drop a message to dicsuss further possibilities! For more info, feel free to check my updated portfolio: www.waleedgeo.com #geoai #earthengine #floodrisk #remotesensing #hkbu #datascience #gfsm #flood

The transition to open access appears to have stalled. Why? Yesterday I posted an essay that explores the link between the rapid growth of research articles from China and the proportion of papers published open access globally. The attached document summarises the key takeaways. To get the full story (and the caveats) you can read the essay here: https://lnkd.in/evvVtDUV The scholarly publishing industry is going through a significant transition. We've never experienced article growth like this before, driven by a country that owns relatively few journals that its researchers publish in. Historically, Chinese institutions have paid less under 'read' subscription models than institutions in the USA, Japan and Europe. This makes transformative agreements hard to negotiate, as Chinese institutions would need to pay a lot more than they do now. (And no one wants to pay more.) There are many questions with unknown answers: ➡️ Will western publishers push back on publishing Chinese research if they can't monetise those papers adequately? ➡️ Will China be willing to pay more than it does currently to support scholarly publishing infrastructure? ➡️ Will Chinese funders mandate their researchers to publish more content in new, local journals? Or will they prefer to publish in established journals for free under a subscription reader-pays model? ➡️ What can be done to increase the peer reviewer pool in China? These are big, difficult questions for a Saturday morning. Thoughts welcome!

The Congo Basin and the Amazon together form the living green heart of our planet. Yet the Congo Basin remains far less studied, far less resourced and far less understood. Today, there are just over 100 publishing environmental scientists across Congo Basin countries, compared to more than 6,000 working in the Amazon. We undertook the work of the Science Panel for the Congo Basin: to bring together the scientific knowledge necessary to inform global climate policy and strengthen regional scientific capacity, to identify key knowledge gaps and to call for increased funding to train a generation of scientists. Last year at COP30 in Belém, we launched the Executive Summary of our report, Resilience and Sustainability in the Congo Basin: Retracing the Past, Looking to the Future. The full report is now being released as an open-access digital volume published by Springer, with chapters becoming available as they are finalised. This 40-chapter, 800-page work represents one of the most comprehensive scientific assessments ever undertaken on the Congo Basin. During the coming weeks, in my capacity as Special Envoy of the Science Panel for the Congo Basin and one of the editors-in-chief of the report, I will share some of these chapters with you as they become public, along with some thoughts from me on each of them, explaining and why the findings matter. I hope that will be of some interest to you. Today, to kick things off, here is the Executive Summary – which makes clear exactly why these rainforests, which for many years were my and my family’s home, matter. It can be found here: https://lnkd.in/e46FY36f It has truly been a privilege to serve as an editor-in-chief on this project, alongside Bila-Isia Inogwabini, Bonaventure Sonké and Lydie Stella Koutika, working closely with section editors Jean-Jacques Braun, Raphael Tshimanga, Kate Abernethy, Averti Suspense IFO and Denis Jean Sonwa, and with the support of the UN Sustainable Development Solutions Network, Springer Nature and our partners and sponsors. A central objective of this effort was to ensure the report would be fully open access. By doing so, we aim to strengthen scientific capacity across the region and ensure that researchers, students and institutions in Congo Basin countries have unrestricted access to the knowledge needed to understand and protect these globally critical forests. It is our hope that this work will help bring greater global attention, scientific investment and policy focus to the Congo Basin in the years ahead. I look forward to your thoughts on what we publish. Executive Summary: https://lnkd.in/eYwTDPNK Full volume (in progress): https://lnkd.in/exCxG-_Y

📢 New publication and a meaningful milestone I’m very happy to share our new paper in University of Oxford Open Climate Change. This study explores how Kenyan health workers perceive their role in building a climate-resilient, net-zero healthcare system, drawing on a national questionnaire and an in-depth focus group discussion across professions. Key takeaways: • Health workers in Kenya are highly aware of the health impacts of climate change and strongly support action within the healthcare system. • The main barriers to action are not motivation, but limited resources, financing, and, critically, insufficient, non-contextualised training. • Education emerged as a cornerstone for transformation: not just technical knowledge, but practical, locally relevant skills, emotional resilience, ethical leadership, and community-embedded approaches. • Health workers see themselves not only as clinicians, but as advocates, educators, and trusted actors bridging national policy and local realities. The paper argues that co-created, context-specific climate-health education can empower health workers to lead both mitigation and adaptation efforts and should be treated as a core strategy for sustainable, resilient healthcare systems. On a personal note, this is the final publication from my PhD thesis, which I successfully defended in earlier this year. Bringing this work to completion feels both grounding and deeply meaningful. I’m incredibly grateful to all my co-authors and collaborators: Marie-Claire Wangari M. MBChB, MSc(Ongoing), Leonard Agan, Winslet Mwende, Naomi Gitau, Iain Cross, and Anita Berlin, with a special shout-out to Melvine Otieno, whose role as in-country coordinator was central throughout, and my supervisors Andy Haines and Sarah Whitmee for their guidance, trust, and steady support over the years. Thank you as well to all Kenyan health workers who shared their time, insights, and experiences. 📄 Open-access article: https://lnkd.in/eRz52J6U 📘 PhD thesis: https://lnkd.in/eUAHvpKc #ClimateAndHealth #SustainableHealthcare #HealthWorkforce #NetZeroHealthcare #PlanetaryHealth #Kenya #PhDResearch #OpenAccess

Why Crucial Climate Science Remains Hidden Behind Paywalls and Why That’s a Planetary Risk: the ‘𝐃𝐞𝐬𝐭𝐚𝐛𝐢𝐥𝐢𝐳𝐚𝐭𝐢𝐨𝐧 𝐨𝐟 𝐄𝐚𝐫𝐭𝐡 𝐬𝐲𝐬𝐭𝐞𝐦 𝐭𝐢𝐩𝐩𝐢𝐧𝐠 𝐞𝐥𝐞𝐦𝐞𝐧𝐭𝐬’ study* is an outstanding and deeply consequential piece of research empirically demonstrating that multiple Earth system tipping elements -  the Greenland ice sheet, AMOC, the Amazon rainforest, and the South American monsoon system -  are simultaneously losing resilience. This study moves the conversation far beyond abstract modelling or distant scenarios. It tells us, with measurable evidence, that the Earth’s stabilising mechanisms are weakening now. This is precisely the kind of science-based insight that should inform every policy and strategic plan, climate risk assessment, and political negotiation taking place in 2025 and beyond. Equally important is the methodological innovation: translating long-term observational data into quantitative indicators of system resilience and recovery rates. This offers a practical early-warning framework, a potential foundation for real-time planetary monitoring, and a science–policy interface tool with immense value for climate policy, diplomacy, adaptation, and financial risk management alike. But here’s the scandal: 𝐒𝐮𝐜𝐡 𝐯𝐢𝐭𝐚𝐥 𝐫𝐞𝐬𝐞𝐚𝐫𝐜𝐡 𝐢𝐬 𝐨𝐟𝐭𝐞𝐧 𝐥𝐨𝐜𝐤𝐞𝐝 𝐛𝐞𝐡𝐢𝐧𝐝 𝐩𝐚𝐲𝐰𝐚𝐥𝐥𝐬. When the fate of planetary systems  and the well-being of billions  depends on shared knowledge, restricting access through commercial publishers is indefensible. How can we expect policymakers, businesses, journalists, or civil society actors to act on findings they cannot even read? If we are serious about closing the knowledge–action gap that still paralyses global climate policy, studies like this must not only be produced but shared openly, translated into decisions, and acted upon! With sincere thanks to the authors - Niklas Boers, Teng Liu, Sebastian Bathiany, Maya Ben-Yami, Lana L. Blaschke, Nils Bochow, Chris A. Boulton, Timothy Lenton, Andreas Morr, Da Nian, Martin Rypdal, and Taylor Smith. -  for this crucial contribution to our planetary understanding. * [a] Publisher (paywalled): https://lnkd.in/eFaecVHr [b] View-only, open-access Springer Nature Shared It content-sharing version: https://lnkd.in/eehSuv3i [c] PIK summary: https://lnkd.in/e3P2-ddr  Johan Rockström, Guido Palazzo, Andreas Rasche, Hans Stegeman, Niklas Höhne, Alison Taylor, Glen Peters, Joeri Rogelj, Michael Mann, Katharine Hayhoe , Nick Robinsm Diana Urge-Vorsatz, Robert Vautard

I edit manuscripts for Springer Nature. Read posts from Jonas Heller and Alex Zhavoronkov about the topic: The future of the publishing system. Last month, an AI-generated paper passed peer review at an ICLR workshop. Cost to produce: $15. Time: a few hours. The reviewers couldn't tell. Neither can I, sometimes. Here's what most people miss about the "crisis" in scientific publishing: It's not a crisis. It's a phase transition. NeurIPS submissions: 3,297 in 2017. 27,000 in 2025. Reviewer acceptance rate: collapsing. Papers with paper mill signatures: 1 in 50. LLM fingerprints in peer reviews: up to 17%. The system isn't stressed. It's breaking. I send reviewer invitations every week. Decline. Decline. No response. Decline. Scientists contribute 130 million hours annually to peer review. Zero compensation. Zero training. Zero recognition. Why would they keep doing it? Meanwhile, in laboratories: Pacific Northwest National Lab just deployed autonomous research platforms. Robots run experiments 24/7. AI agents design protocols, analyze data, adjust parameters. Lawrence Berkeley's A-Lab synthesized 41 novel materials autonomously. Sakana's AI Scientist writes complete research papers for $15. The endpoint is obvious: AI generates hypotheses. Robots run experiments. AI writes papers. AI reviews papers. Where exactly do humans fit? My prediction: the current system survives five years. Maximum. Not ten. Five. The economic logic is unforgiving. What changes: Phase 1 (now): Detection arms race. Tortured phrase databases. Prompt injection attacks. Fraud detection theater. Phase 2 (2027+): The literature bifurcates. High-trust venues become invitation-only. AI-generated content floods open-access mega-journals. Phase 3 (2029+): Validation becomes the product. Reproducing findings matters more than publishing them. Autonomous labs become arbiters of truth. If your value is "I write papers," you're competing with $15 software. If your value is "I interpret what matters and make ethical judgments about risk," you're still ahead. The uncomfortable truth: academic incentive structures still reward publication volume. The metric is becoming meaningless. The careers built on it are not. I don't have a clean solution. But I know what doesn't work: Pretending the system is fine. Defending what's already failing. Optimizing for metrics that AI can generate at infinite scale. The question isn't AI versus humans in science. The question is: What do we want the scientific literature to actually do? Archive everything? AI wins. Curate what matters? Different system required. Validate truth claims? Reproducibility infrastructure, not publication infrastructure. We can't have all three. Not anymore. I still review manuscripts. I still believe expertise matters. But I'm planning for what comes next. You should be too. Full analysis linked below ⬇️ What's your timeline? Am I too pessimistic? Or too optimistic?