EcoDL 2025: The 1st Workshop on Digital Libraries and AI-based Information Systems for Ecological Research and Practice in conjunction with TPDL 2025
EcoDL 2025 aims to explore the integration of AI, digital libraries, and FAIR data principles in ecological research to improve knowledge synthesis and predictive modeling. Ecology's complexity and data heterogeneity present challenges in generalization, requiring advanced computational tools for structured knowledge representation, search, and decision support. We invite researchers from ecology, AI, and digital information systems to discuss AI-driven data synthesis, semantic search, causal inference, and machine learning applications in biodiversity and conservation. Through interdisciplinary contributions, EcoDL 2025 seeks to foster innovation in ecological informatics, supporting open science and advancing digital methods for ecological research and environmental sustainability.
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Workshop website: https://sites.google.com/view/ecodl2025/
Paper Submission Deadline: 16th May 2025 (AoE)
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Topics of interest
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The EcoDL 2025 workshop welcomes submissions on, but not limited to, the following topics:
· Knowledge graphs and structured ecological data representation
o Biodiversity knowledge graphs
o Linked open data for integrating scattered ecological knowledge sources
o Ontologies for data interoperability in ecology: Standardizing environmental terms and concepts
o Semantic annotation and classification of ecological data
o AI-driven taxonomy generation for ecological datasets
· Advanced search and retrieval for ecological and environmental data
o Neural search for literature and reports: Improving retrieval of species, habitats, and ecosystem information
o Improving retrieval of study question, research hypothesis and applied method
o LLMs for information extraction: Capturing species interactions, climate impacts, and conservation policies
o Retrieval-Augmented Generation (RAG) for ecological research: Hybrid AI systems for answering complex scientific questions
o Multimodal search for biodiversity and environmental studies: Combining text, image, and geospatial data retrieval
o Automated knowledge discovery from climate and biodiversity repositories
· FAIR data principles in ecological research
o Data interoperability
o Open science infrastructure for ecological and environmental data
o Ontologies for data interoperability in ecology: Standardizing environmental terms and concepts
o FAIR data and software
o Data lifecycle management (Create, Store, Share, Reuse)
o NanopublicationsMapping-based Knowledge Graph Construction
· AI for assisting ecological research
o AI-based literature review
o AI-driven synthesis of ecological knowledge: taking complexity and context-dependence into account
o Monitoring biases in study system, study regions and methods in ecological research
o Tracking Misinformation in Climate Science Using NLP: Identifying and mitigating the spread of false environmental claims
· Digital libraries and ecological informatics
o Methods for digitizing and analyzing historical ecological archives
o Indigenous knowledge and digital archives for sustainability
o AI-powered environmental storytelling and digital heritage
o Human-nature interactions in digital libraries
o Digitization and NLP for analyzing historical climate data
· Methods for integrating heterogeneous ecological datasets
o Integrating remote sensing data with ecological repositories
o Multimodal search for biodiversity studies
· Applications of AI in ecosystem restoration, conservation planning and decision-making
o AI-powered decision support systems for restoration and conservation
o Lay summaries based on ecological evidence
o Impact assessment of conservation policies via digital libraries
· Reflections on knowledge synthesis in ecology and on the contributions of AI
o Evaluating the role of AI in ecological research
o Challenges and limitations of AI-driven ecological modeling
o The impact of automated systems on scientific knowledge creation
o Ethical considerations in AI-assisted ecological analysis
o Future directions for AI in knowledge synthesis for ecology
Submission guidelines
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The EcoDL workshop solicits both long and short paper submissions:
§ Long Papers: Up to 15 LNCS style pages, including references.
§ Short Papers: Up to 10 LNCS style pages, including references.
All accepted workshop papers will be published in the proceedings of the Springer series Communications in Computer and Information Science (CCIS). For detailed formatting instructions, please refer to the following linkhttps://www.springer.com/gp/computer-science/lncs/conference-proceedings-guidelines.
Important dates
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Paper Submission: 16th May 2025 (AOE)
Acceptance Notification: 20th June 2025 (AOE)
Camera-ready Version: 10th July 2025 (AOE)
Workshop: 23rd September 2025 in Tampere, Finland
The EcoDL 2025 Workshop is collocated with the The 29th International Conference on Theory and Practice of Digital Libraries (TPDL 2025) https://tpdl2025.github.io/, 23rd to 26th September 2025.
EcoDL 2025 Organising Committee
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Jennifer D'Souza, TIB Leibniz Information Centre for Science and Technology, Hannover, Germany
Birgitta König-Ries, University of Jena, Germany
Tina Heger, Leibniz Institute of Freshwater Ecology and Inland Fisheries (IGB), Berlin, Germany
Marie Kaiser, Bielefeld University, Germany
The list of workshops and tutorials at TPDL this year can be found at https://tpdl2025.github.io/Program/workshops_tutorials.html