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Centre for Biodiversity Knowledge Science (zcb)

From objects to knowledge

Natural history museums are evolving into international centers of open biodiversity knowledge. At the Leibniz Institute for the Analysis of Biodiversity Change (LIB), this transformation is driven by the creation of The Center Biodiversity Knowledge Science — a cross-sectional hub connecting all LIB research and transfer centers.

Vision and mission

The Centre for Biodiversity Knowledge Science will transform the LIB's collections and expertise into a globally accessible knowledge space. By integrating data science, artificial intelligence (AI) and citizen science, the centre combines physical objects with digital knowledge to make biodiversity and its changes understandable and relevant for action.

Strategic goals

  • Build a future-oriented, networked collection: Digitize up to 100% of LIB’s holdings, supported by AI, robotics, and FAIR/CARE-compliant data standards.
  • Enable impactful biodiversity research: Develop data infrastructures and AI tools to monitor, analyze, and predict biodiversity change.
  • Create the LIB Knowledge Space: An open, semantic web-based platform for connecting research data across disciplines and making it accessible to scientists and the public.

Core areas

  1. Data Mobilization – Digitization, data integration, and metadata management across all LIB collections.
  2. Biodiversity Data Science – Development of AI models, semantic knowledge graphs, and analytical tools for ecological and genomic data.
  3. Citizen Science – Inclusive participation in biodiversity research through collaborative data collection, validation, and analysis.

Implementation and governance

  • Cross-location collaboration between the LIB locations Bonn and Hamburg, involving all centers of expertise.
  • Flat, participatory governance encouraging open discussion, agile development, and joint decision-making.
  • Roles and expertise include AI developers, data scientists, digital collection managers, semantic web developers, and strategic researchers.

Effects until 2035

By systematically digitizing, connecting, and interpreting biodiversity data, The Center Biodiversity Data Science will:

  • Position LIB as a globally open object and knowledge hub.
  • Strengthen LIB’s leadership in biodiversity informatics and data-driven conservation science.
  • Foster innovation and social engagement through transparent, participatory research.

Contact person

Dr. Lars Martin Vogt

  • Head of Centre for Biodiversity Knowledge Science (zcb)

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

Contact for enquiries

Larissa Pape

  • Centre assistance

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

Projects

Publications

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    2025

  • 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

  • 2024

  • 2024/07

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

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    Rosetta Statements: Simplifying FAIR Knowledge Graph Construction with a User-Centered Approach

  • 2024/07

    Vogt, L.

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    Rethinking OWL Expressivity: Semantic Units for FAIR and Cognitively Interoperable Knowledge Graphs Why OWLs don't have to understand everything they say

  • 2024/05

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

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    FAIR 2.0: Extending the FAIR Guiding Principles to Address Semantic Interoperability

  • 2024/01

    Rani, F.A., Wang, X., Charania, Z., Vogt, L., Urbas, L.

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    Scalable data pipeline: Ontology-based OPC UA data access for the industrial internet of things

  • 2023

  • 2023/11

    Vogt, L.

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    FAIR Knowledge Graphs with Semantic Units: a Prototype

  • 2023/11

    Bernard‐Verdier, M., Heger, T., Mietchen, D., Musseau, C., Brinner, M., Hillig, A., Kraker, P., Lokatis, S., Nunes, A.L., Scheidweiler, N., Stocker, M., Vial, R., Vogt, L., Bacher, S., Baklouti, E., Gupta, H.B., Beisel, J., Bertolino, S., Briski, E., Castellanos‐Galindo, G.A., Courchamp, F., Daly, E., Dawson, W., Dickey, J.W.E., Evans, T., Itescu, Y., König‐Ries, B., Kumar, L., Kumschick, S., Meyerson, L.A., Pattison, Z., Pfadenhauer, W.G., Renault, D., Rickowski, F., Ruland, F., Schittko, C., Straka, T.M., Yannelli, F.A., Jeschke, J.M.

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    Building an atlas of knowledge for invasion biology and beyond! 2nd enKORE-INAS Workshop

    Research Ideas and Outcomes, 9

  • 2023/07

    David, R., Baumann, K., Le Franc, Y., Magagna, B., Vogt, L., Widmann, H., Jouneau, T., Koivula, H., Madon, B., Åkerström, W.N., Ojsteršek, M., Scharnhorst, A., Schubert, C., Shi, Z., Tanca, L., Vancauwenbergh, S.

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    Converging on a Semantic Interoperability Framework for the European Data Space for Science, Research and Innovation (EOSC)

  • 2023/07

    Vogt, L., Konrad, M., Prinz, M.

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    Towards a Rosetta Stone for (meta)data: Learning from natural language to improve semantic and cognitive interoperability

  • 2023/04

    Vogt, L., Konrad, M., Prinz, M.

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    Knowledge Graph Building Blocks: An easy-to-use Framework for developing FAIREr Knowledge Graphs

  • 2023/04

    Girón, J.C., Tarasov, S., Montaña, L.A.G., Matentzoglu, N., Smith, A.D., Koch, M., Boudinot, B.E., Bouchard, P., Burks, R.A., Vogt, L., Yoder, M., Osumi-Sutherland, D., Friedrich, F., Beutel, R.G., Mikó, I.

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    Formalizing Invertebrate Morphological Data: A Descriptive Model for Cuticle-Based Skeleto-Muscular Systems, an Ontology for Insect Anatomy, and their Potential Applications in Biodiversity Research and Informatics

    Systematic Biology, 5, 72

  • 2023/01

    Vogt, L.

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    The FAIREr Guiding Principles: Organizing data and metadata into semantically meaningful types of FAIR Digital Objects to increase their human explorability and cognitive interoperability

  • 2023/01

    Vogt, L., Kuhn, T., Hoehndorf, R.

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    Semantic Units: Organizing knowledge graphs into semantically meaningful units of representation

  • 2022

  • 2022/03

    Stocker, M., Heger, T., Schweidtmann, A.M., Ćwiek‐Kupczyńska, H., Penev, L., Dojchinovski, M., Willighagen, E., Vidal, M., Turki, H., Balliet, D., Tiddi, I., Kuhn, T., Mietchen, D., Karras, O., Vogt, L., Hellmann, S., Jeschke, J.M., Krajewski, P., Auer, S.

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    SKG4EOSC - Scholarly Knowledge Graphs for EOSC: Establishing a backbone of knowledge graphs for FAIR Scholarly Information in EOSC

    Research Ideas and Outcomes, 8

  • 2022/01

    Girón, J.C., Tarasov, S., González Montaña, L.A., Matentzoglu, N., Smith, A.D., Koch, M., Boudinot, B.E., Bouchard, P., Burks, R., Vogt, L., Yoder, M., Osumi-Sutherland, D., Friedrich, F., Beutel, R., Mikó, I.

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    Formalizing Insect Morphological Data: A Model-Based, Extensible Insect Anatomy Ontology and Its Potential Applications in Biodiversity Research and Informatics

  • 2021

  • 2021/12

    Stefen, C., Wagner, F., Asztalos, M., Giere, P., Grobe, P., Hiller, M., Hofmann, R., Jähde, M., Lächele, U., Lehmann, T., Ortmann, S., Peters, B., Ruf, I., Schiffmann, C., Thier, N., Unterhitzenberger, G., Vogt, L., Rudolf, M., Wehner, P., Stuckas, H.

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    Phenotyping in the era of genomics: MaTrics—a digital character matrix to document mammalian phenotypic traits

    Mammalian Biology, 1, 102

  • 2021/05

    Auer, S., Stocker, M., Vogt, L., Fraumann, G., Garatzogianni, A.

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    ORKG: Facilitating the Transfer of Research Results with the Open Research Knowledge Graph

    Research Ideas and Outcomes, 7

  • 2020

  • 2020/11

    Auer, S., Oelen, A., Haris, M., Stocker, M., D’Souza, J., Farfar, K.E., Vogt, L., Prinz, M., Wiens, V., Jaradeh, M.Y.

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    Improving Access to Scientific Literature with Knowledge Graphs

    BIBLIOTHEK Forschung und Praxis, 3, 44

  • 2020/08

    Vogt, L., D'Souza, J., Stocker, M., Auer, S.

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    Toward Representing Research Contributions in Scholarly Knowledge Graphs Using Knowledge Graph Cells

  • 2019

  • 2019/06

    Grobe, P., Baum, R., Bhatty, P., Köhler, C., Meid, S., Quast, B., Vogt, L.

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    From Data to Knowledge: A semantic knowledge graph application for curating specimen data

    Biodiversity Information Science and Standards, 3

  • 2019/06

    Vogt, L., Auer, S., Bartolomaeus, T., Buttigieg, P.L., Grobe, P., Michalik, P., Stocker, M., Usbeck, R.

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    FAIR.ReD: Semantic knowledge graph infrastructure for the life sciences

    Biodiversity Information Science and Standards, 3

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