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From objects to connected knowledge
Biodiversity is currently declining faster than at any point in human history. Decisions regarding conservation, restoration and climate adaptation urgently require scientific evidence; yet much of the world’s knowledge on biodiversity remains fragmented across collections, databases, publications and institutions, often making it impossible to combine or reuse on a large scale.
At the Leibniz Institute for the Analysis of Biodiversity Change (LIB), the Centre for Biodiversity Knowledge Science (zcb) has been established to bridge this gap. The zcb advances the emerging field of biodiversity knowledge science and, as LIB’s cross-cutting digital and scientific centre, transforms the institute’s collections and research outputs into connected, trustworthy and AI-ready biodiversity knowledge to serve science, policy, education and society.
Vision
Imagine a shared knowledge space where questions such as “Where is this species thriving?”, “How has its distribution changed?”, and “What evidence links these changes to climate and environmental drivers?” can be answered by drawing on connected, traceable knowledge across collections, disciplines and time.
The zcb exists to turn this vision into reality, and to position LIB as a founding node of a future distributed, federated Open Biodiversity Knowledge Space.
Mission
The Centre pursues three interconnected goals:
Through digitisation support, semantic modelling and AI-assisted tools, the zcb transforms physical specimens and research outputs into open, human- and machine-interpretable knowledge objects that are citable, traceable in terms of provenance, and reusable across disciplines and institutions.
The zcb develops and maintains LIB’s core semantic knowledge infrastructure: an integrated, FAIR, CARE and CLEAR-compliant knowledge environment linking specimens, observations, genomic data, publications, taxa and environmental information. Rather than a collection of isolated databases, the knowledge space will be built on an interoperable knowledge graph in which connections are explicit, interpretable by both humans and machines, and traceable.
The zcb carries out original research into how knowledge of biodiversity can be semantically modelled, validated, and made usable and actionable across generations. This includes developing the Semantic Units Framework based on the FAIR and CLEAR principles, and novel approaches to causal knowledge representation, causal semantic digital twins, and hybrid human–AI reasoning.
Core areas
Digitisation is the foundation of everything the zcb does. Without digitised collections, there is no data to link, represent or analyse. Working closely with LIB’s collections and in line with the LIB Digitisation Strategy and international standards (MIDS, DiSSCo, NFDI4Biodiversity), the zcb supports and advances the digitisation, mobilisation and FAIR publication of LIB’s specimens and associated data, transforming physical holdings into openly accessible digital resources. The long-term goal is the comprehensive digitisation of LIB’s holdings, supported by AI and automation, so that the full scientific value of the collections becomes openly accessible.
The zcb develops the semantic frameworks, knowledge graphs and AI-assisted tools that transform mobilised data into connected, machine-interpretable and actionable biodiversity knowledge, realised within the LIB Open Knowledge Space. This also represents the centre’s research frontier (see Research below).
Knowledge of biodiversity is enhanced when society plays a part in its development. The zcb supports inclusive participation in biodiversity research through collaborative data collection, validation and analysis, linking public engagement with LIB’s scientific infrastructure and contributing to the science–society knowledge interface.
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Open by design
As well as providing the LIB Open Knowledge Space as a resource for the biodiversity community, the zcb is committed to openness at every level. All semantic artefacts and software we produce, including backend and frontend solutions, biodiversity ontologies, and graph schema specifications (in SHACL or LinkML), will be released as open source and made openly available. This ensures that other institutions can adopt, reuse and build upon our work, and lays the foundation for a shared, federated Open Biodiversity Knowledge Space developed by the community, for the community.
Governance and working practices
The zcb operates horizontally across all the other LIB research centres, linked through a network of ambassadors, i.e., colleagues based at two centres, who ensure that the zcb’s infrastructure meets genuine scientific needs and fosters synergies across taxonomic and morphological, molecular, biomonitoring and knowledge-exchange biodiversity research.
Delivering on this mission requires a deliberately interdisciplinary team. The zcb brings together expertise in the semantic web and knowledge engineering, software development (back-end and front-end), data science and AI, ontology development, digital collection management and digitisation, biodiversity informatics, and citizen science.
Internally, the team follows an agile development process, using Objectives and Key Results (OKR) for goal-setting, holding weekly team meetings, and developing minimum viable products in sprints. All outputs that go into production are the result of close collaboration between zcb members and LIB domain experts, working hand in hand with curators, taxonomists, morphologists, ecologists and genomicists across LIB’s collections and research centres.
Roadmap
Building the team, maintaining and expanding the core data infrastructure, laying the semantic and architectural foundations of the LIB Open Knowledge Space, and launching the LIBTellMe prototype.
Operating as an active research and infrastructure centre: deploying LIBTellMe, implementing the LIB Open Knowledge Space using Semantic Ladder pipelines, and delivering interconnected textual and structured biodiversity knowledge.
LIB is a founding node of the federated Open Biodiversity Knowledge Space, with collections serving as living, machine-actionable and globally connected knowledge. The ontologies and semantic models developed at LIB will serve as a national and international anchor for distributed interoperability in biodiversity research.
Why this matters
Without a shared knowledge infrastructure, biodiversity data remains fragmented and increasingly disconnected from the AI-driven tools, interdisciplinary workflows and evidence-based policy processes that science and society urgently need.
With the zcb, LIB is evolving from being a custodian of objects to becoming the steward of a living, connected memory of nature. The LIB Open Knowledge Space becomes LIB’s living memory: a globally connected, future-ready biodiversity knowledge hub that actively contributes to understanding and tackling biodiversity loss.
Contact person
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- Head of Centre for Biodiversity Knowledge Science (zcb)
Phone: +49 40 238317 705
E-Mail: l.vogt@leibniz-lib.de
Contact for enquiries
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Staff
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Dipl. Biol. Katharina Geiger
Phone: +49 228 9122 411
E-mail: k.geiger@leibniz-lib.de/leibniz-lib.de/fileadmin/user_upload/home/Bilder/LIB/Ueber_das_LIB/Mitarbeitende/Bonn/Goretzky-Carina_c-Geiger.jpg%3F1778487668)
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Dr. Tobias Spanke
ztm Postdoctoral researcherPhone: +49 228 9122 407
E-mail: t.spanke@leibniz-lib.de/leibniz-lib.de/fileadmin/user_upload/home/Bilder/LIB/Ueber_das_LIB/Mitarbeitende/Hamburg/Vogt-Lars_01--LIB_-Pour.jpg%3F1772022151)
Projects
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LEPMON: Recording the biodiversity of moths (Lepidoptera) with AI
Management: Dr. Peter Grobe
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Unknown Germany
Management: Prof. Dr. Dr. h. c. Bernhard Misof, Dr. Ralph S. Peters
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NFDI4Biodiversity
Management: Dr. Peter Grobe
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CaBOL - Caucasus Barcode of Life
Management: Prof. Dr. Dr. h. c. Bernhard Misof
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FOGS
Management: Dr. Jonas Astrin
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1KITE
Management: Prof. Dr. Dr. h. c. Bernhard Misof
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GGBN
Management: Dr. Jonas Astrin
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GGBC
Management: Prof. Dr. Dr. h. c. Bernhard Misof
Publications
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2026/09
Connecting biodiversity biobanks in the global infrastructure landscape
BioScience
2026/07
Semantic Modeling in Materials Science and Engineering With Platform MaterialDigital Core Ontology 3.0
Advanced Engineering Materials
2026/07
The "GfI-Fischartenatlas" of the German Ichthyological Society (GfI) - A compilation of validated fish species occurrence records
Biodiversity Data Journal, 14
2026/06
The Semantic Units Framework, a technology-agnostic representational approach to FAIR and CLEAR knowledge infrastructures
Scientific data, 1, 13
2026/06
An annotated type catalogue and a fully digitised Crustacea collection of the Museum of Nature Hamburg, Zoology. Part I: Crustacea, Malacostraca, Peracarida, Cumacea
Evolutionary Systematics, 1, 10
2026/05
Workshop-Übung: Artvorkommensdaten strukturieren und beschreiben
2026/05
Actionable Understanding: Action Units for Bridging the Knowledge-Action Gap in Post-FAIR Knowledge Infrastructures
2026/04
Stadtwildnis fördern: Mit Bildung für nachhaltige Entwicklung (BNE)
2026/03
FörTax and the Future of Biodiversity Literacy: Insights and Impacts of Species Knowlegde Training and Networks
2026/03
Communicating Biodiversity through Participatory Monitoring combined with Education and Stakeholder Engagement– Best Practices from a Natural History Museum
2026/03
The Semantic Ladder: A Framework for Progressive Formalization of Natural Language Content for Knowledge Graphs and AI Systems
2026/01
Rosetta Statements: simplifying FAIR knowledge graph construction with a user-centred approach
Database, 2026
2026/01
Recommendation of scientific fish husbandry: Sulawesi ricefishes (Beloniformes, Adrianichthyidae)
Bulletin of Fish Biology, 1, 21
2025/12
Citizen Science an Universitäten, Hochschulen und Forschungseinrichtungen. Eine Handreichung mit Ressourcen, Informationen und Praxistipps für Multiplikator*innen, Wissenschaftsmanager*innen und weitere Unterstützende
2025/09
Charta der GFBio-Datenzentren
2025/09
The Grammar of FAIR: A Granular Architecture of Semantic Units for FAIR Semantics, Inspired by Biology and Linguistics
2025/09
Ecolink: Towards a Knowledge Graph Schema for Complex Environmental Systems
2025/08
A Framework for FAIR and CLEAR Ecological Data and Knowledge: Semantic Units for Synthesis and Causal Modelling
2025/04
Suggestions for extending the FAIR Principles based on a linguistic perspective on semantic interoperability
Scientific data, 1, 12
2025/03
Towards Machine-Actionable Scientific Knowledge as FAIR Digital Objects
2025/03
Extracting specimen label data rapidly with a smartphone—a great help for simple digitization in taxonomy and collection management
ZooKeys, 1233
2025/03
An annotated catalog of Annelida types at the Museum of Nature Hamburg, Zoology. Part I: Annelida: Errantia: Aciculata: Eunicida, Myzostomida, Aciculata incertae sedis, and Errantia: Protodriliformia
Evolutionary Systematics, 1, 9
2025/01
FOGS: A SNPSTR Marker Database to Combat Wildlife Trafficking and a Cell Culture Bank for Ex‐Situ Conservation
Molecular Ecology resources
2024/10
Enabling technology hand in hand with enabling practices
Journal of Enabling Technologies, 2/3, 18
2024/10
The ASV Registry: a place for ASVs to be
Metabarcoding and Metagenomics, 8