10th-11th of February 2026, Swedish Museum of Natural History
Artificial Intelligence is no longer just a tool—it is becoming a vital partner in the quest to understand and protect biodiversity. SBDI Days 2026 will explore this transformative partnership under the theme: AI and Biodiversity: a Perfect Pair!
Registration is closed.
This forward-looking conference will bring together researchers working in the fields of ecology, biology, biodiversity, remote sensing, genetic monitoring, Earth system science, and data science, to examine how AI and machine learning are reshaping the study of Life on Earth. We’ll explore the power and promise of big data methods—including e-DNA, a-DNA, remote sensing, and image analysis—when coupled with advanced AI and ML techniques. From tracking species via drones and autonomous submarines to processing massive ecological datasets in real time, the road to full AI implementation in robotics is already under construction.
Our sessions will delve into emerging technologies such as Digital Twins of ecosystems—virtual replicas that allow simulation and prediction of biodiversity changes—and highlight how these depend on advanced infrastructure, robust metadata, and open data standards. Further, we will highlight real-world breakthroughs in biomonitoring, genetic monitoring, and AI-enhanced insights into extinctions through time.
Equally important, SBDI Days 2026 will address the ethics of generative AI: How can tools capable of creating synthetic data be applied responsibly in ecology and biodiversity research? What frameworks are needed to combat AI model-based hallucinations, including biased data, fake data, and algorithmic bias? And how do we ensure that the rapid adoption of AI aligns with principles of fairness, accountability, and scientific transparency?
If we are to unlock the full potential of AI in ecology and conservation, we must do so with care, collaboration, and a shared commitment to integrity in science. The Swedish Biodiversity Data Infrastructure (SBDI) invites you to be part of this essential conversation. Join us at SBDI Days 2026 to connect, challenge assumptions, and help shape the ethical, technical, and ecological future of artificial intelligence in ecology and biodiversity research!
Date: 10th-11th of February 2026
Place: Swedish Museum of Natural History, Frescativägen 40 Stockholm
Program: View full program
Do you want to submit a talk/poster or register for a workshop? Register for the conference using the “Sign up” button above to submit your abstract and chose workshops.
The deadline to submit an abstract is January 10 2026.
Do you want to pay by invoice? Send an email to info@biodiversitydata.se including your name, affiliation and billing information. You will receive a code to register.
SBDI Days 2026 Sponsorship information
The sponsor fee is 4 000 SEK and includes the following benefits:
Please note: There is space for just 10 exhibitors, and allocation is on a first come–first served basis.
Please contact us for more information and expression of interest: info@biodiversitydata.se
18:00 - 20:00
Kick off the conference with an icebreaker at the Swedish Museum of Natural History, where you can enjoy a drink and light snacks, while mingling with colleagues. The Icebreaker will take place in the museum’s newly refurbished hall, among exhibited specimens representing the Swedish fauna. What better way to get ready for SBDI Days 2026!?
Location: Swedish Museum of Natural History Welcome Hall, inside the main entrance.
09:00 - 10:00
Welcome to SBDI Days 2026
As you enjoy your coffee or tea, we invite you to register for SBDI Days 2026. SBDI Days 2026 offers a forum for collaboration, knowledge exchange, and discussion within Sweden’s biodiversity data community. We look forward to welcoming you to an engaging and inspiring event!
Location: Stora hörsalen (Large auditorium) – enter via museum main entrance and follow the signs.
10:00 - 10:15
Margret Steinthorsdottir (SBDI) and Anabella Aguilera (SciLifeLab Planetary Biology).
In this session we explore AI in biodiversity research: the power and promise of big data when coupled with advanved AI tecniques, present breakthroughs and discuss insights.
10:15 - 10:45
Dr. Tobias Andermann (SBDI, SciLifeLab, Uppsala University)
10:45 - 11:00
Wouter Koch (Norwegian Biodiversity Information Centre)
11:00 - 11:15
Josephine Sullivan (KTH)
11:15 - 11:30
Sven Adler (SLU)
11:30 - 11:45
Louis Fiorina (Gothenburg University)
11:45 - 12:00
Justine Pagnier (Gothenburg University)
12:00 - 13:30
In this session we explore emerging technologies in biodiversity research: from innovative methods to improve our understanding of the causes of biodiversity change and relationship with climate change, to advanced projects such as Digital Twins.
13:30 - 14:00
Prof. David Roy (UK Centre for Ecology & Hydrology)
14:00 - 14:15
Britt Andermann (Museum of Evolution, UU)
14:15 - 14:30
Lars Pettersson (SBDI, Lund University)
14:30 - 14:45
Bengt Karlson (SMHI)
14:45 - 15:00
Fredrik Ronquist (NRM)
15:00 - 16:00
16:00 - 17:30
Exploring eDNA in SBDI
Dr. Maria Prager - SBDI and University of Gothenburg
Dr. Daniel Lundin - SBDI and Linnaeus University
Prof. Anders Andersson - SBDI and KTH SciLifeLab
Description
This workshop will demonstrate how environmental DNA (eDNA) / metabarcoding data can be accessed, processed, and analyzed within the Swedish Biodiversity Data Infrastructure (SBDI). We will show how to download eDNA data, use our R package to unpack, merge, and aggregate datasets, and then explore biodiversity patterns across environments in R. The session will also introduce SBDI resources for data submission, processing, and integration with GBIF.
Expected outcomes
Participants will learn about tools and workflows for eDNA data management and analysis, and how these contribute to open biodiversity knowledge.
FAIR Data Principles
Dr. Angela Fuentes Pardo, SciLifeLab Data Centre
Dr. Stephan Nylinder, National Bioinformatics Infrastructure Sweden (NBIS)
Dr. Veronika A. Johansson, The Global Biodiversity Information Facility (GBIF) Sweden
Description
This workshop introduces the FAIR Data Principles—Findable, Accessible, Interoperable, and Reusable—and explores their practical implementation within life science research and data management. Participants will gain an understanding of how FAIR principles enhance data quality, transparency, and long-term usability, with hands-on examples and discussions on tools, standards, and best practices relevant to Swedish research centers and infrastructures, such as SciLifeLab and SBDI.
Expected outcomes
Participants will be able to apply FAIR principles in their own data management workflows and contribute to improving the FAIRness of data within their research communities.
All your base are belong to us: BioCollect as a versatile tool for cross-platform data integration
Mathieu Blanchet, SBDI and Lund University
Dr. Lars B. Pettersson, SBDI and Lund University
Description
This workshop will demonstrate how BioCollect can be used to integrate biodiversity monitoring data from different platforms via APIs. One example of a rapidly evolving platform is the range of mobile applications designed to assist with the monitoring of birds, butterflies and other species. Typically, such applications work together with dedicated data warehouse structures in the countries in which they were developed. This tends to create silo-like workflows with little cross-country integration of ongoing biodiversity monitoring. Here, we will demonstrate how API-to-API communication enables us to leverage data flows from external monitoring tools, integrate them with national monitoring data in BioCollect and EcoData, and then offer user-centred downstream publication in observation databases.
Expected outcomes
Participants will learn how BioCollect can enable cross-platform integration to help monitoring schemes mobilise quality data from external sources.
Building and sharing AI applications within ecology and biodiversity
Dr. Arnold Kochari, Project Lead, Data Centre, SciLifeLab
Description
As more researchers in ecology and biodiversity build machine learning models, it is important to find ways to make these models useful for the researcher community or general public. One way to do this is to share the models as web applications with an easy-to-use interface. Users of the models can then adjust parameters or submit their own input and see the result generated by the underlying model. This tutorial is aimed at PhDs and researchers working within ecology and biodiversity who work with machine learning models but do not have the skills to build applications for the web. During the tutorial we will start from a trained model and demonstrate step by step how you can create a graphical user interface for your application, prepare it for deployment, and make it available on the web with a URL. We will demonstrate the use of specific tools which make this process easy and doable in under an hour.
Expected outcomes
Participants will have an overview of various open-source tools for creating applications out of machine learning models. Furthermore, they will have practices creating an application using one such tool or perhaps already have a demo of an application with their own model. Participants will have knowledge about options for hosting their applications and making them available to the general public or to colleagues.
Public hosting of Shiny apps: hands-on workshop
Dr. Arnold Kochari, Project Lead, Data Centre, SciLifeLab
Description
Researchers often create R Shiny applications as part of their projects and want to publish them as research output – as analysis tools with a graphical interface, as supplementary materials for publications, in order to make annotation easier, etc. In order to make Shiny apps available to the collaborators or general public, they need to be hosted somewhere and have a URL. We will start this workshop by giving an overview of what it means to create and publish Shiny apps as researcher in terms of institutional and funder requirements. We will then take a look at different hosting options for Shiny apps. During the hands-on part, we will focus on packaging Shiny apps for hosting as Docker images. Together with the participants, we will step-by-step package and publish an example Shiny app or the participants’ own Shiny app. If you are a researcher with an existing Shiny app you’d like to host, or if you plan to build a Shiny app in the future, this workshop is for you. If you already have a Shiny app you would like to host, bring it, and we will help you with it.
Expected outcomes
After this workshop, the participants will both have an understanding of working with Shiny apps within research projects in a Swedish university context and have practical knowledge about public hosting of Shiny apps.
19:00 - 22:00
The conference dinner will be held at restaurant Proviant on Campus Albano, a short bus ride – or a decent walk if you need fresh air – from the Swedish Museum of Natural History. The dinner will consist of three courses, composed from seasonal ingredients – vegetarian option available. Restaurant Proviant has a full bar for purchase of beverages. Please join us for this evening of good food and socializing!
In this session we explore the potential perils and pitfalls of using AI in biodiversity research, including AI model-based hallucinations, biased data, fake data, and algorithmic bias.
09:00 - 09:30
Rukaya Sarah Johaadien (Natural History Museum, University of Oslo, Norway)
09:30 - 09:45
Nikolay Oskolkov (Lund University)
09:45 - 10:00
Kim T. Halvorsen (Institute of Marine Research, Norway)
10:00 - 10:15
Allison Hsiang (DEEP, SU)
10:15 - 10:30
Sterre Witte (DTU Aqua, DK)
10:30 - 11:00
In this session we explore the ethics of using AI in biodiversity research, and how to align AI with principles of fairness, accountability, and scientific transparency.
11:00 - 11:30
Dr Tim R Hofmeester (Associate Professor of biology and researcher at the Department of Wildlife, Fish, and Environmental Studies, Swedish University of Agricultural Sciences, Umeå)
11:30 - 11:45
Oleksiy Guzhva (SLU)
11:45 - 12:00
Kristin Brunk (University of Oslo)
12:00 - 12:15
Anna-Lena Axelsson (SLU)
12:15 - 12:30
Melika Baghooee (Aarhus University, DK)
12:30 - 12:45
Wrap up – discussion – final thoughts (SBDI and SciLifeLab Planetary Biology)
12:45 - 13:45
Assistant Professor and SBDI Representative, Department of Organismal Biology, Uppsala University
DDLS Fellow, SciLifeLab, Uppsala University
Biodiversity is disappearing at an alarming rate, as our impact on this planet far exceeds sustainable levels. Through combining AI techniques with large-scale environmental DNA (eDNA) data sets and high-resolution remote sensing data, Tobias aims to contribute to improving our understanding of how biodiversity is distributed and where it is most threatened. Tobias’ vision is the development of standardized methods to measure and model biodiversity for any given site.
UK Centre for Ecology & Hydrology (UKCEH)
David works on the innovative use of AI-assisted technologies to deliver robust information on the status of wildlife and to understand the causes of biodiversity change. He is focused on closing the knowledge gap for insects due to increasing global attention on their decline and the vital role they play all ecosystems — as pests, food for birds and mammals, recycling nutrients, pollinating crops — and as indicators of climate change impacts.
Senior Engineer, Natural History Museum, University of Oslo, Norway
Rukaya works at GBIF Norway, based at the Natural History Museum, University of Oslo, where she explores how AI can automate working with biodiversity data, including its management, quality control, and publication. She has built several applications that use AI to improve how biodiversity data is processed and shared. While integrating these technologies into complex systems is technically demanding, she sees the greater challenge in designing effective user interfaces, accounting for user intent, transparency, effective data visualization and error handling, and the subtle ways people collaborate with AI tools.
Associate Professor of biology and researcher at the Department of Wildlife, Fish, and Environmental Studies, Swedish University of Agricultural Sciences, Umeå
The use of technology to monitor wildlife (often called “Conservation Technology”) has increased tremendously in recent years. Tim works on implementing these technologies in wildlife research and management. A big advantage of collecting data with sensors (camera traps, acoustic recorders, or drones) rather than people is that every observation has a verifiable voucher (a picture or sound file) of the species being present at a specific time and date. It also opens up for non-professionals (hunters or citizen scientists) to help collect the data. Both of these facts increase the transparency and reproducibility of data collection, amongst others, increasing trust in monitoring results as a basis for management decisions. However, what happens when the full workflow is automated using AI and advanced statistical models?
