ICBO 2025 conference
About Program¶
- Conference Dates:
- Workshops/tutorials: (see Program page for more detail)
- Annotating Data with Ontologies: LinkML Can Help: (11/5/2025)
- 14th Vaccine and Drug Ontology Studies (VDOS) 2025 Workshop: (11/7/2025)
- Workshop for PhD Students & Early Career Researchers: (11/10/2025)
- Food, Waste, and Sustainability: Synergizing Ontology Efforts: (11/14/2025)
- Accelerating Ontology Curation with Agentic AI and GitHub: (11/18/2025)
- Main conference: November 7th to November 9th (11/7/2025-11/9/2025) November 9th to November 11th (11/9/2025-11/11/2025)
- ICBO-EAST (Joint with Semantic Web Ontology Study Group (SWO)): November 1st (11/1/2025)
- 13:0010:00 - 17:30 JST
Schedule¶
Note that the following schedule is subject to change. Additionally, more detail about presentations days/times will be added as it becomes available.
Saturday, November 1, 2025 (JST* Friday Oct. 30, 2025 in EST)
10:00 - 17:30 JST ICBO-EAST (Joint with Semantic Web Ontology Study Group (SWO))
Wednesday, November 5, 2025
11:00am ET (08:00am PT) Annotating Data with Ontologies: LinkML Can Help
Friday, November 7, 2025
tbd 14th Vaccine and Drug Ontology Studies (VDOS) 2025 Workshop
Sunday, November 9, 2025
ICBO 2025 Main Conference Day 1 (*presentation times tbd)
Monday, November 10, 2025
ICBO 2025 Main Conference Day 2 (*presentation times tbd)
09:00am - 11:00am ET Workshop for PhD Students & Early Career Researchers
Tuesday, November 11, 2025
ICBO 2025 Main Conference Day 3 (*presentation times tbd)
Friday, November 14, 2025
10:00am - 01:00pm ET (04:00pm - 07:00pm CET) Food, Waste, and Sustainability: Synergizing Ontology Efforts
Tuesday, November 18, 2025
10:00am - 01:00pm ET (07:00am - 10:00am PT / 03:00pm - 06:00pm UK / 04:00pm - 07:00pm CET) Accelerating Ontology Curation with Agentic AI and GitHub
Keynotes Speakers¶
-
tbd
Workshops Details¶
- Organizers
- Sabrina Toro (University of North Carolina at Chapel Hill)
- Justin Reese (Lawrence Berkeley National Laboratory)
- Nicolas Matentzoglu (Semanticly)
- Melissa Haendel (University of North Carolina at Chapel Hill)
- J Harry Caufield (Lawrence Berkeley National Laboratory)
- Chris Mungall (Lawrence Berkeley National Laboratory)
- Date of Workshop
- November 18
- Time and Timezone of Workshop
- 7am-10am PT
- 10am-1pm ET
- 3pm-6pm United Kingdom
- 4pm-7pm Central Europe
- Abstract
- Artificial Intelligence (AI) technology is having a tremendous impact on science and society. This can be readily observed in fields such as software engineering, where developers are increasingly using AI tools and even ‘vibe coding’ entire projects. However, much of this impact has yet to filter down to curation and ontology development. Many ontology developers report that they are either distrustful of AI, or they don’t know where to start. Additionally, ontology developers may think that parts of their workflow are too complex to use in AI.
In fact, AI is particularly well suited to many complex aspects of ontology development, and if used correctly, can be deployed with high reliability, while giving the human experts full control over tasks. Some ontologies, such as Mondo, Uberon, and the GO, have already successfully incorporated ontology agents into their GitHub-based workflows.
In this tutorial, we will give a practical hands-on guide to ontology developers, showing how to use the latest powerful agent-based AI to support and accelerate their work. At the end of the tutorial, participants will be able to use an AI coding agent as a part of their day-to-day workflow.
- Organizers
- Sierra Moxon (Lawrence Berkeley National Laboratory)
- Kevin Schaper (Translational and Integrative Sciences Lab, University of North Carolina)
- Matt Brush (Translational and Integrative Sciences Lab, University of North Carolina)
- Chris Mungall (Lawrence Berkeley National Laboratory)
- Melissa Haendel (Translational and Integrative Sciences Lab, University of North Carolina
- Date of Workshop
-
- November 5
- Time and Timezone of Workshop
- 8am PT
- Abstract
- This tutorial introduces LinkML (Linked Data Modeling Language), an open framework that simplifies the process of authoring, validating, and sharing data. LinkML offers an approachable syntax that is not tied to any one technical architecture, and can be integrated seamlessly with many existing frameworks. A low barrier to entry enables people from different backgrounds and varying levels of technical expertise to collaborate, forming a shared understanding of the underlying data semantics and contributing to data annotation and ontology integration.
- Organizers
- Sebastian Duesing (La Jolla Institute for Immunology)
- Bjoern Peters (La Jolla Institute for Immunology)
- James Overton (Knocean, Inc.)
- Randi Vita (La Jolla Institute for Immunology)
- Chris Mungall (Lawrence Berkeley National Laboratory)
- Abstract
- The Core Ontology for Biology and Biomedicine (COB) is a BFO-compatible upper-level ontology used by the Open Biomedical Ontologies (OBO) Foundry. COB provides a direct parent for the top-level classes in every OBO ontology, and so OBO ontologies that use COB are interoperable. Therefore, COB adoption makes interoperability measurable within the OBO Foundry, a critical step towards the Foundry's goal of ensuring the testability of all its principles. After a robust development push following the 2024 COB Workshop at the La Jolla Institute for Immunology, the COB development team is focused on making COB adoption faster, easier, and more rewarding. The purpose of this workshop is to engage and train others to adopt COB in their own ontologies and participate in future COB development.
- Organizers
- Olga Mashkova (King Abdullah University of Science and Technology)
- Anthony Huffman (University of Michigan)
- Date of Workshop
- November 10
- Time and Timezone of Workshop
- 9am-11am ET
- Abstract
- This interactive panel discussion brings together senior researchers to share insights and advice with early-career colleagues working in biomedical ontologies and knowledge representation. Panelists will reflect on key career decisions, essential skills beyond technical expertise, and strategies for resilience in research. The discussion will explore the evolving role of artificial intelligence and large language models (LLMs) in ontology development, addressing how these technologies can drive real-world impact, support industry, and tackle global challenges such as public health and climate change. The panel will also consider how to foster community governance, and uphold ethical responsibility in ontology-driven applications. The session aims to inspire the next generation of researchers while promoting dialogue on the future of ontologies for health, science, and sustainability.
- Organizers
- Giorgio Ubbiali (OTH Brixen College)
- Ludger Jansen (PTH Brixen College)
- Date of Workshop
- November 14
- Time and Timezone of Workshop
- 4pm-7pm CET
- Abstract
- To date, food and plastic waste deriving from human consumption and other supply chain activities pose serious challenges to human health and the resilience and sustainability of food systems. Ontologies play an essential role in enhancing interconnections among datasets, data sources, and people, proving to be critical means to deal with complex health and sustainability issues, such as food and plastic waste. If originally, ontology efforts mainly centered on developing resources addressing health and related features, recently, attention has also been dedicated to sustainability issues. It is imperative to enhance interconnectedness among these ontologies and related applications. In particular, it will be important to communicate across different ontology communities to adequately capture the intrinsic connections between health and sustainability. This workshop aims to promote discussions in this direction, focusing on waste as a starting use case. First, we will explore the current conceptualization of waste, especially food and plastic waste in food systems. Then, we will move to discuss the corresponding existing ontologies and models. Finally, we will engage with subject matter experts, conversating on how to synergize sustainability and health ontologies across ontology communities for food systems waste.
- Organizers
- Junguk Hur (University of North Dakota)
- Yongqun He (University of Michigan)
- Cui Tao (Mayo Clinic)
- Date of Workshop
- November 7
- Time and Timezone of Workshop
- tbd
- Abstract
- We propose the 14th Vaccine and Drug Ontology Studies (VDOS) workshop at the 16th International Conference on Biomedical Ontology (ICBO 2025). This year, we extend our focus to encompass artificial intelligence's transformative role in drug and vaccine ontology research. The workshop aims to explore innovative solutions and challenges in representing and analyzing drugs and vaccines, covering administration, immune responses, adverse events, and more. Key topics include the ontological representation of drugs and vaccines, real-world application challenges, drug components, administration, immune responses, drug interactions, and adverse events in clinical and research settings. A special emphasis will be placed on how AI can revolutionize ontology studies, enhancing literature mining, meta-analysis, and complex data interpretation. Despite progress, challenges remain in fully representing and utilizing ontologies for research and clinical issues, such as detailed representation of administration and adverse events, drug interactions, and analysis of immune responses. The workshop will bring together experts from clinical, research, and pharma-biotech sectors to discuss solutions to these challenges, aiming to foster advancements in drug development, administration, and the integration of AI in ontological research. Our goal is to contribute to public health improvement by enhancing the understanding and application of drug and vaccine ontologies.
- Organizers
- Alexander Diehl (University at Buffalo)
- Yongqun He (University of Michigan)
- David Osumi-Sutherland (Wellcome Trust Sanger Institute)
- Abstract
Large projects such as the Human Cell Atlas, the Human BioMolecular Atlas Program, the Single Cell Atlas, and the Allen Brain Map are generating and analyzing huge volumes of cell type-specific gene and protein expression data, and mapping their results to known cell types, often using the Cell Ontology. High throughput methods such as single cell RNA sequencing, special transcriptomics, and flow and mass cytometry produce large amounts of data regarding the role of cell types in health and disease. In many cases, the data point to the need for better ontological representation of existing and new cell types. At the same time, experimental approaches such as microscopy, genomics, and metabolomics are expanding our understanding of cellular functioning in relation to neighboring cells and the whole organism.
Ontologies are increasingly used for integrating and analyzing these diverse data types. The Cell Ontology and Cell Line Ontology have long served as reference ontologies for cell type information, and additional ontologies such as the Gene Ontology, Protein Ontology, and the Ontology for Biomedical Investigation are important for representing experimental data about cell types, the methods used to produce that data, and for performing data analyses on cell type data. There is a continuing need for improved automated analysis techniques to link data about cells with appropriate ontologies.
Contact Information¶
Please direct all further questions to Asiya Yu Lin (ontology.world@gmail.com)