• Mihai Pop

• Alex Bateman, EMBL-EBI, UK
• Cathy Wu, University of Delaware, USA
• Alan Bridge, SIB, Switzerland

This talk presents a comprehensive cost-benefit analysis of UniProt, the universal protein resource that serves as a crucial catalogue for protein data in the scientific community. The analysis was carried out by CSIL as part of the Pathos project funded by the European Union's Horizon Europe framework programme. Drawing from extensive quantitative and qualitative research, we examine UniProt's economic impact across multiple dimensions including transaction cost savings, access cost savings, and labor cost savings for its diverse global user base. The analysis establishes a counterfactual scenario to evaluate what the research landscape would look like without UniProt, revealing significant efficiency gains and economic benefits that substantially outweigh operational costs. Beyond direct economic impacts, we explore UniProt's broader influence through citation and patent analysis, demonstrating its critical role in enabling scientific advancements across multiple fields and supporting sustainable development goals. The assessment methodology combines survey data, bibliometric analysis, and stakeholder interviews to provide a holistic view of how this essential resource facilitates knowledge dissemination and scientific innovation. Our findings offer valuable insights for research infrastructure evaluation and underscore UniProt's position as a foundational element of the global bioinformatics ecosystem.

• Shoba Ranganathan

The Asia-Pacific (APAC) region covers countries and territories in Australasia, East Asia, and Southeast Asia are often included. In a wider context, Central Asia, North Asia, the Pacific Islands, South Asia, West Asia (including the Arabian Peninsula and the Levant). The region provides striking contrasts between high-income countries and low- and middle-income countries. Bioinformatics data and infrastructure stewardship in this region will need to address challenges in bridging the existing gaps.

APAC data challenges include data privacy, security, and the immense quantity of data generated by modern sequencing technologies. Linking quality data generation to bioinformatics analysis tools in clinical settings, comprehensive analysis of large datasets as well as data security and confidentiality are primary hurdles to be crossed.

Bioinformatics infrastructure stewardship covers challenges related to data accessibility, interoperability, and sustainability. Better data management practices, infrastructure investments, and global collaboration to make bioinformatics resources more readily available and usable for research and development are critical. However, the high cost of specialized tools and technologies, limited computing resources and network woes limit progress in e-science.

I will present the current state of APAC data and infrastructure and how to address these challenges.

• Deepak Nair

The Indian Biological Data Centre (IBDC) is the first digital repository mandated to archive and share all biological data generated in India. The IBDC project was initiated in 2020 and was formally launched in 2022. At present, the centre has seven portals for the archiving of nucleotide, crop phenome, metabolomics, proteomics and structural data. An overview of IBDC portals and other activities conducted at IBDC will be presented.

• Julio Collado Vides, National Autonomous University of Mexico UNAM, Mexico

The FAIR (Findable, Accessible, Interoperable, and Reusable ) principles define the current standard for data representation. However, there is still room to go beyond and improve the representation of knowledge itself through explicit criteria for Quality of Knowledge Representation (QKR).
The proposal is based on universal properties in the representation of knowledge, especially scientific knowledge. Certainly, any piece of knowledge - explicitly or implicitly- has one or more evidence and their corresponding sources, a confidence level, and one or multiple contexts. These four criteria define QKR-version 1.0. Additionally, any knowledge can be described at different levels of detail, which offers a way to organize it. I will focus on how confidence level is defined and used in RegulonDB, the biodata resource of transcriptional regulation in E.coli, and will show what could be achieved with different levels of detail. The vision is for QKR to become a natural extension of the FAIR principles. This is more relevant now given the impact of quality of knowledge in the output of AI systems. The societal impact is evident since representation and sharing are inseparable. The quality of representation determines the quality of communication of knowledge in broader contexts as well.

• Maria Martin

• Peter Maccallum , United Kingdom

• Christophe Dessimoz, Swiss Institute of Bioinformatics, Switzerland

Over the past decade, the FAIR principles which provide guidance in making data Findable, Accessible, Interoperable, and Reusable have transformed the way research is funded and evaluated. In a paradigm shift, funders now routinely require data management plans, which involves researcher training in FAIR practices and data deposition. The FAIR movement has also led to pronounced behavioural changes among researchers, while largely overlooking the essential role of infrastructure: the biodata resources — deposition databases and knowledgebases — that turn scattered data sets into readily-available coherent knowledge.

Without infrastructure, FAIR data policy risks becoming a compliance exercise where data might be shared, but remain fragmented, inconsistently annotated, or practically inaccessible. Achieving FAIR at a global scale and reaping its benefits for discovery, artificial intelligence (AI), and innovation depends on infrastructure designed to capture, curate, and connect research data systematically. In life sciences, such infrastructure is referred to as “biodata resources”.

In this talk, I will argue that investing in biodata resources provides some of the most effective and cost-efficient means of achieving the goal of the FAIR principles. I will call on funders and institutions to provide stable, competitive support for these vital resources such as at a level of at least 1% of research budgets to secure the foundations of FAIR data, accelerate AI-driven discovery, and maximise the impact of public investment in science.

• Guy Cochrane

Just as scientific data are essential for life science and biomedical research, the databases, services and tools that enable scientists to safeguard, share and access data provide a critical foundation for scientific advance. However, unlike many other scientific infrastructures, biodata resources exist as a globally distributed open ecosystem of independently managed activities that lack a coordinated holistic approach to sustained operation development. Individual resources are often at risk and many survive on short-term research grant funding, hampering long-range strategic planning.

The Global Biodata Coalition, an initiative that brings together funding organisations working towards greater sustainability in the biodata infrastructure, through consultation of stakeholders, has developed a set of nine principles to guide the development of models for greater biodata resource sustainability and is exploring models through which funders can cooperate to achieve this.

In the talk, I will present the principles and outline a number of models under exploration.

• Susan Gregurick

• Phil Bourne
• Francis Ouellette

What can you do as a graduate student, postdoc, professor, leader to address the scientific moment we find ourselves in? We will come with a few suggestions, but we are sure you will have others.