OAI14

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Managing large open data platforms - developing cutting edge technology solutions through collaboration

Bioinformatics is the science of collecting and analysing complex biological data such as genetic codes. The European Bioinformatics Institute (EBI) is one of the six sites of The European Molecular Biology Laboratory (EMBL), an intergovernmental organisation with 20 member states. With over 40 open access data resources and cutting edge data analysis tools, EBI provides data, tools and training to advances scientific discovery that enable solutions for global challenges such as infectious diseases, food insecurity and loss of biodiversity. Running and managing this collection of open resources requires significant infrastructure investment, global collaboration with other infrastructure and industry partners, and investment to remain cutting edge and take advantage of technological advances such as AI. This talk will cover three case studies to demonstrate 1) global collaboration through the European Nucleotide Archive, member of the International Nucleotide Sequence Database Collaboration; 2) industry collaboration through AlphaFold, the protein structure database developed in collaboration with Google DeepMind and 3) how to meet user expectations in a resource constrained environment through Europe PMC’s product management strategy.

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How can researchers leverage Open Source AI with a data-centric approach

Open-source AI, particularly with open-weight models from Llama, Mistral, and DeepSeek, has shifted research focus from massive general-purpose systems toward compact, domain-specific solutions. This talk will overview the rapidly evolving open ecosystem of AI, emphasizing how researchers can adopt data-centric workflows to use AI responsibly and innovatively. By curating high-quality, rights-cleared datasets, and iteratively refining data quality, researchers can fine-tune open-weight models into transparent, reproducible, and sustainable tools. Adopting this approach democratizes AI, enhances methodological transparency, enabling labs of all sizes to build precise solutions tailored for embedded, privacy-sensitive, and energy-efficient AI applications.

Open Source AI: Propagation of Open Source Licenses in the Age of AI

Open source AI models have the potential to foster innovation and technological progress. Nevertheless, the definition of “open source” in the AI space is hotly discussed. A related – yet no less central – issue concerns the propagating effect of copyleft (or ShareAlike) clauses embedded in training data or upstream code. Do these clauses require downstream AI models, systems and their output to be released under the same open source terms, e.g. as copyright derivatives? This has major repercussions as such propagation would render entire AI projects fully open. The presentation will examine this question and find that this is presently unlikely to be the case, save for training data. Further to this finding, and in order to protect the effectiveness of ShareAlike clause, it will thus advocate for a new definition of copyright derivatives specific to the AI-context.

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Developing scalable learning opportunities about generative AI

ETH Library has identified digital information literacy as a key need in our academic community. In particular, with the advent of genAI, researchers at all levels have experienced considerable uncertainty regarding the ethical ways of incorporating these new tools in their scientific workflow. Therefore, we have developed multiple learning paths for staff and students to obtain the competences necessary for working effectively and responsibly with generative AI tools. This talk will provide an overview of our strategic decisions and insights gained from addressing this issue.

Feynbot: Unlocking conversational access to High Energy Physics literature

Imagine having a conversation with the entire INSPIRE-HEP database—asking complex questions about particle physics research and receiving precise, contextual answers instantly. The Feynbot project aims to make this vision reality through an advanced Retrieval Augmented Generation system that transforms how researchers interact with scientific literature. This presentation unveils Feynbot's innovative approach that combines cutting-edge AI with the comprehensive INSPIRE-HEP collection. Natural language queries will unlock insights buried across thousands of research papers. Whether you're exploring theoretical frameworks, investigating experimental results, or tracking research trends, Feynbot will deliver accurate, detailed responses tailored to your specific needs. We'll explore the technical architecture behind this system, reveal proven strategies for eliminating AI hallucinations, and demonstrate how Feynbot bridges the gap between researchers' needs and RAG implementation. With tools like this, we will be able to reshape research workflow, opening new pathways for scientific exploration in particle physics.

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Introduction

Open Science, Next Generation Metrics, and the World of Publishing

The starting point is the LERU Next Generation Metrics report aiming to maximising its utility for universities by compiling an extensive list of valuable resources on next-generation metrics. It places strong emphasis on the imperative of collaboration, both among universities and between universities and funding agencies. By leveraging international expertise in bibliometrics and informatics, universities will enhance their resilience, reduce dependence on a limited number of companies that provide (seemingly) pre-packaged research intelligence, and gain a greater capacity to shape their metric policies in alignment with their own missions, rather than relying solely on standard metrics and data availability.

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Panel Session

RoundUp

Introduction

Retractions: On The Rise, But Not Enough

In 2000, there were about 40 retractions from the scholarly literature. In 2023, there were more than 10,000. That is a dramatic increase, even accounting for the growing number of papers published per year. In this talk, I will explore the reasons for the increase, why it is good news, and why the real number should be even higher. Drawing on more than a decade and a half of experience at Retraction Watch, I will tell the stories of the sleuths who are finding problems in the literature. And I will talk about how everyone can avoid ending up in the Retraction Watch Database -- or end up there for a good reason.

The virus model of research fraud: integrity requires inoculation, testing, and quarantine

It's generally thought that fraud is rare, and science is self-correcting, but is that true? Sadly, there is increasingly evidence of widespread fraud in science, ranging from individual bad actors who build a glowing reputation on faked or manipulated data, to industrial scale fraud from so-called “paper mills”, who charge for authorship and/or citations. I’ll discuss why it is urgent to tackle these, with various measures comparable to testing for a virus, tracing contact, quarantine and vaccination. I list some red flags that aid paper mill detection, and show how open science practices are important to counteract fakery in science.

How the misuse of GenAI can spoil the publishing system

The recent explosion of generative AI has had a profound impact on society as a whole, particularly through the new possibilities enabled by text generation tools, with ChatGPT being the most well-known example. The research community has not been immune to this phenomenon. In this presentation, I will discuss how this technology has been used by researchers, with a particular focus on its role in questionable research practices related to scientific publishing, and the broader questions this raises about the research ecosystem as a whole.

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Placing Humans at the Centre of Open Research

Efforts to produce standards, guidelines, technologies and infrastructures that may boost sharing practices in science have resulted in great advances over the last few decades. However, they have also unintentionally boosted a technocratic, object-oriented vision of open research that is easy to appropriate for “open washing” and does not do justice to the very efforts of the humans at the heart of such work. The result is an open research landscape that fosters, rather than mitigate, existing inequities and divides in the production and use of scientific research. This talk reflects on the requirement of keeping social agency at the heart of open research practice, and what it means for the future development of policies, tools and services.

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A Latin American Perspective on Research Integrity and Open Science

In this presentation, I will succinctly go over why Open Science can help realize and sustain global research integrity, including fair scientific participation from the global south. I will underscore the importance of having the correct international incentives, prioritizing high quality over quantity, and the need to provide enough material resources to the historically postponed geographies to effectively include all talent and perspectives in the advancement of science. I will explain why volunteerism, often found in Open Source Science, is problematic and will draw from our experience co-creating and participating in international Open Science communities of practice that facilitate collaboration over competition as a way to durable scientific integrity.

Q&A session