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Zentrum für Biodiversitäts-Wissensforschung  (zcb)

From objects to connected knowledge

Biodiversity is currently declining faster than at any point in human history. Decisions about conservation, restoration, and climate adaptation urgently need scientific evidence, yet much of the world's biodiversity knowledge remains fragmented across collections, databases, publications, and institutions, often impossible to combine or reuse at scale.

At the Leibniz Institute for the Analysis of Biodiversity Change (LIB), the Centre for Biodiversity Knowledge Science (zcb) exists to close 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 make this vision a 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 turns physical specimens and research outputs into open, human- and machine-interpretable knowledge objects that are citable, provenance-tracked, 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 connecting specimens, observations, genomic data, publications, taxa, and environmental information. Instead of a collection of isolated databases, the knowledge space will be built on an interoperable knowledge graph in which connections are explicit, human- and machine-interpretable, and traceable.

  • The zcb conducts original research on how biodiversity knowledge 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 connect, represent, or reason over. In close collaboration with LIB's collections and aligned 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, turning 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 in the LIB Open Knowledge Space. This is also the centre's research frontier (see Research below).

  • Biodiversity knowledge is strengthened when society participates in its creation. The zcb supports inclusive participation in biodiversity research through collaborative data collection, validation, and analysis, connecting public engagement with LIB's scientific infrastructure and contributing to the science–society knowledge interface.

Open by design

Beyond 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 ways of working

The zcb spans horizontally across all the other LIB research centres, connected through a network of ambassadors, i.e., colleagues co-located at two centres, who ensure the zcb’s infrastructure serves real 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 semantic web and knowledge engineering, software development (backend and frontend), data science and AI, ontology development, digital collection management and digitisation, biodiversity informatics, and citizen science.

Internally, the team works with an agile development process, using Objectives and Key Results (OKR) for goal-setting, weekly team meetings, and sprint-based development of minimum viable products. All outputs that go into production are the result of close collaboration between zcb members and LIB domain experts, thus working hand in hand with curators, taxonomists, morphologists, ecologists, and genomicists across LIB's collections and research centres.

Roadmap

  • Building the team, maintaining and extending 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 with Semantic Ladder pipelines, and delivering interconnected textual and structured biodiversity knowledge.

  • LIB as a founding node of the federated Open Biodiversity Knowledge Space, with collections functioning 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 moves from being a custodian of objects to being 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 addressing biodiversity loss.

Ansprechperson

Dr. Lars Martin Vogt

  • Leitung Zentrum für Biodiversitäts-Wissensforschung (zcb)

Tel.: +49 40 238317 705
E-Mail: l.vogt@leibniz-lib.de

Kontakt für Anfragen

Larissa Pape

  • Zentrumsassistenz

Tel.: +49 228 9122 358
Fax: +49 228 9122 212
E-Mail: l.pape@leibniz-lib.de

Mitarbeitende

Projekte

Publikationen

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    2026

  • 2026/09

    Droege, G., Astrin, J.J., Güntsch, A., Bentley, A., Corrales, C., Labuschagne, K., Ocampo, G., Addink, W., Appiah-Madson, H.J., Arita, M., Avrili, H., Barker, K., Bravo, G.A., Buzan, E., Casino, A., Cochrane, G., da Silva, M., Distel, D., Ernst, M., Vargas, B.E., Poulin, R.F., Fantoni, K., Fichtmueller, D., Glöckner, F.O., Grobe, P., Groom, Q., Gupta, V., Häffner, E., Heinemann, K.D., Holetschek, J., Hollingsworth, P.M., Hunter, C., Hvilsom, C., Islam, S., Kadhirvelu, V.B., Kurtböke, D.İ., Lewin, H., McHardy, A.C., Mekarska, A., Meyer, R.S., Muñoz-García, M., Paulmann, C., Paupério, J., Penev, L., Ratnasingham, S., Röpert, D., Ron, S.R., Ryder, O., Schigel, D., Scholz, A.H., Schriml, L.M., Siriaroonrat, B., Tilley, L., Waterhouse, R.M., Misof, B., Borsch, T.

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    Connecting biodiversity biobanks in the global infrastructure landscape

    BioScience

  • 2026/07

    Schilling, M., von Hartrott, P., Waitelonis, J., Hanke, T., Birkholz, H., Nasrabadi, H.B., Razghandi, K., Zaripova, K., Thonagel, F., Neuhaus, F., Glauer, M., Vogt, L., Sack, H., Mädler, L., Bayerlein, B., Eberl, C.

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    Semantic Modeling in Materials Science and Engineering With Platform MaterialDigital Core Ontology 3.0

    Advanced Engineering Materials

  • 2026/07

    Brunken, H., Braubach, L., Engel, T., Grobe, P., Pfaff, C., Rach, B., Vatterrott, H., Friedrichs-Manthey, M.

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    The "GfI-Fischartenatlas" of the German Ichthyological Society (GfI) - A compilation of validated fish species occurrence records

    Biodiversity Data Journal, 14

  • 2026/06

    Vogt, L.

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    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

    Engel, J., Ernst, M., Pauli, M., Penzlin, A., Rach, B., Weibulat, T.M.

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    Workshop-Übung: Artvorkommensdaten strukturieren und beschreiben

  • 2026/05

    Vogt, L.

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    Actionable Understanding: Action Units for Bridging the Knowledge-Action Gap in Post-FAIR Knowledge Infrastructures

  • 2026/04

    Zedda, L., Nöske, N.

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    Stadtwildnis fördern: Mit Bildung für nachhaltige Entwicklung (BNE)

  • 2026/03

    Waskow, K., Nöske, N., Miesen, F.W., Stehr, K., Busch, A., Schneider, T., Griesang, N., Hense, J., Weller, M.

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    FörTax and the Future of Biodiversity Literacy: Insights and Impacts of Species Knowlegde Training and Networks

  • 2026/03

    Nöske, N., Waskow, K.

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    Communicating Biodiversity through Participatory Monitoring combined with Education and Stakeholder Engagement– Best Practices from a Natural History Museum

  • 2026/03

    Vogt, L.

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    The Semantic Ladder: A Framework for Progressive Formalization of Natural Language Content for Knowledge Graphs and AI Systems

  • 2026/01

    Vogt, L., Farfar, K.E., Karanth, P., Konrad, M., Oelen, A., Prinz, M., Strömert, P.

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    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

  • 2025/12

    Brandt, J., Stiebritz-Banischewski, J., Arens, K., Beißert, U., Bittner, L., Blum, C., Braun, C., Gantenberg, J., Hedemann, K., von der Heiden, K., Hülsen, J., Pusoma, M., Rutten, M., Nöske, N., Nolte, N., Schmidt, F.J.

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    Citizen Science an Universitäten, Hochschulen und Forschungseinrichtungen. Eine Handreichung mit Ressourcen, Informationen und Praxistipps für Multiplikator*innen, Wissenschaftsmanager*innen und weitere Unterstützende

  • 2025/09

    Weibulat, T., Rach, B., Holstein, J., Luther, K., Pauli, M., Penzlin, A., Reimer, L., Scholz, U., Thorn, C., Triebel, D., Ebert, B.

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    Charta der GFBio-Datenzentren

  • 2025/09

    Vogt, L., Mons, B.

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    The Grammar of FAIR: A Granular Architecture of Semantic Units for FAIR Semantics, Inspired by Biology and Linguistics

  • 2025/09

    Alamenciak, T., Arnillas, C.A., Caufield, J.H., Compton, K., DREW, K.M., Frühstückl, R., Heger, T., König‐Ries, B., Mungall, C., Moxon, S., Reese, J., Tardif, J., Vogt, L.

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    Ecolink: Towards a Knowledge Graph Schema for Complex Environmental Systems

  • 2025/08

    Vogt, L., König‐Ries, B., Alamenciak, T., Brian, J.I., Arnillas, C.A., Korell, L., Frühstückl, R., Heger, T.

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    A Framework for FAIR and CLEAR Ecological Data and Knowledge: Semantic Units for Synthesis and Causal Modelling

  • 2025/04

    Vogt, L., Strömert, P., Matentzoglu, N., Karam, N., Konrad, M., Prinz, M., Baum, R.

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    Suggestions for extending the FAIR Principles based on a linguistic perspective on semantic interoperability

    Scientific data, 1, 12

  • 2025/03

    Biniossek, C., Betz, D., Vogt, L., Stocker, M.

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    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

    Moore, J., Garilao, C., Kerbl, A.

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    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

    Mozer, A., Di‐Nizo, C.B., Consul, A., Huettel, B., Jäger, R., Akintayo, A., Erhardt, C., Fenner, L., Fischer, D., Forat, S., Gimnich, F., Grobe, P., Martin, S., Nathan, V., Saeed, A., von der Mark, L., Woehle, C., Olek, K., Misof, B., Astrin, J.J.

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    FOGS: A SNPSTR Marker Database to Combat Wildlife Trafficking and a Cell Culture Bank for Ex‐Situ Conservation

    Molecular Ecology resources

  • 2024

  • 2024/10

    Schulz, A.C., Cürlis, D., Goretzky, C., Krüger, D., Pelka, B., Preissner, L.

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    Enabling technology hand in hand with enabling practices

    Journal of Enabling Technologies, 2/3, 18

  • 2024/10

    Bräunig, C., Meid, S., Quast, B., Rduch, V., Grobe, P.

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    The ASV Registry: a place for ASVs to be

    Metabarcoding and Metagenomics, 8

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