GBIF - Global Biodiversity Information Facility

• Islam, Sharif; Koivula, Hanna; Andrew, Carrie; Gordillo, Julian Lopez; Weiland, Claus & Schigel, Dmitry [Show all 10 contributors for this article] (2026). FAIR digital twins for biodiversity: enabling data, model, and workflow integration. npj biodiversity. 5(1). doi: 10.1038/s44185-025-00116-3. Full text in Research Archive Show summary

  Abstract The biodiversity crisis demands computational tools to integrate and analyse complex, disparate data and models. This paper presents the concept of FAIR Digital Twins (FDTs) and, drawing on the work of the Biodiversity Digital Twin (BioDT) project (2022–2025), demonstrates how combining Digital Twins with FAIR principles (Findable, Accessible, Interoperable, and Reusable) can transform biodiversity research and decision-making. We show strategies for integrating heterogeneous data, models, and computational workflows within a FAIR framework, paving the way for operational FDTs. The BioDT project developed ten prototype digital twins addressing a critical range of challenges, including grassland and forest dynamics, bird monitoring, ecosystem services, and crop wild relative genetic resources. We discuss implementation challenges such as data fragmentation, semantic interoperability, and operational complexity. Critically, we highlight the opportunities for dynamic adaptation, modular workflows, and cross-domain collaboration, detailing how tools like Research Object Crate (RO-Crate) operationalise FAIR principles for metadata packaging and standardisation. This convergence of Digital Twins with FAIR principles offers a scalable and reusable approach to advancing biodiversity modeling and simulation, providing a robust foundation for evidence-based policy decisions.

• Weiland, Claus; Bauer, Daniel; Chala, Desalegn; Endresen, Dag; Grieb, Jonas & Kehel, Zakaria [Show all 9 contributors for this article] (2025). FAIRification and AI-Readiness for Biodiversity Digital Twins. Biodiversity Information Science and Standards (BISS). 9. doi: 10.3897/biss.9.181439. Full text in Research Archive Show summary

  The European Green Deal addresses a wide array of critical topics regarding the interaction and exchange between society and ecosystems involving human-induced climate change, biodiversity loss, and deforestation. To support the development of appropriate and sustainable mitigation strategies, both political frameworks as well as large-scale scenario forecast and simulation infrastructures such as Destination Earth Data Lake (DEDL, Puechmaille et al. 2025) and the Green Deal Data Space (Penninga et al. 2021) are currently implemented. Setting up these data spaces requires the consolidation and harmonization of vast amounts of data, among them data from long-term biodiversity monitoring (e.g. eDNA, Abarenkov et al. 2023), near real-time data captured by IoT devices (e.g. camera traps, Grieb et al. (2025)) and large-scale Earth observation data (e.g. ERA5 global reanalysis, Hersbach et al. (2020)). Key tools and research methodologies for integration of such data have been developed in the Destination Earth-linked Biodiversity Digital Twin project (BioDT). Biodiversity digital twins provide digital replicas of biodiversity patterns and processes (Khan et al. 2025), for FAIR-compliant reuse and cross-platform portability, they are packaged in BioDT using the RO-Crate specification. Resulting datasets as well as computational workflows are bundled as digital objects and annotated with rich machine-interpretable metadata using schema.org and its extensions Bioschemas and Croissant (high-level metadata specification supporting AI-Readiness, Bolleman et al. 2025). The workflow.earth pilot was developed to migrate and functionally integrate BioDT's digital twin for crop wild relatives (BioDT CWR) into DEDL. BioDT CWR is designed to identify genetic resources in crop wild relatives (CWR) and aid in creating strategies to mitigate food-related crises linked to climate change (Chala et al. 2024). CWR are crucial sources of untapped genetic diversity, offering greater adaptability to extreme weather events such as droughts, cold waves, and heavy precipitation. They are therefore of particular importance to ensure food security with regard to Sustainable Development Goals (notably Goal 2 “End hunger, achieve food security and improved nutrition and promote sustainable agriculture”, United Nations 2023). Major objectives for workflow.earth are to enhance visibility and long-term availability of the BioDT CWR, to improve its prediction capabilities using DEDL’s near data processing services, and to facilitate (in perspective) the orchestrated interplay with other digital twins such as the Climate Change Adaptation DT (Weiland et al. 2024). to enhance visibility and long-term availability of the BioDT CWR, to improve its prediction capabilities using DEDL’s near data processing services, and to facilitate (in perspective) the orchestrated interplay with other digital twins such as the Climate Change Adaptation DT (Weiland et al. 2024). On top of RO-Crate, workflow.earth employs FAIR Signposting to add machine-interpretable links to human-readable digital objects using link relation types (RFC8288, Fig. 1) to present the web topology of a resource (Soiland-Reyes et al. 2024). In this presentation, we will demonstrate the deployment of agrobiodiversity workflows in DEDL using workflow.earth and the publication of model and results as webby FDOs.

• Mahlangu, Sibusiso; Ewers, Isabelle; Carvalho, Cintia Oliveira; Schrøder-Nielsen, Audun; Dunthorn, Micah & Karlsen, Hans Erik [Show all 12 contributors for this article] (2025). Investigating the dynamics of the aquatic community in Oslofjord through time series analysis of eDNA. Journal of Fish Biology. ISSN 0022-1112. doi: 10.1111/jfb.70105. Full text in Research Archive Show summary

  Understanding the temporal dynamics of marine communities is critical for assessing ecosystem health and guiding conservation efforts. Here, we conducted a survey using environmental DNA (eDNA) metabarcoding with two primer sets, MiFish and Elas02, to investigate seasonal and interannual changes in the fish community of Oslofjord (Norway) over two consecutive years. Using the MitoFish reference database through the Global Biodiversity Information Facility querying tool, we identified 63 fish species and found significant changes in the dominant taxa between seasons and years. Clupea harengus (Atlantic herring) consistently peaked in early spring, while Scomber scombrus (Atlantic mackerel) dominated winter months in the second year. The MiFish primer set showed increased species richness in the second year, whereas the Elas02 primer set showed stable richness despite compositional turnover. Non-metric multidimensional scaling revealed distinct community separation between years in presence/absence of data, driven by species turnover rather than abundance read changes. Our findings support the use of eDNA metabarcoding to capture fine-scale (bi-monthly) temporal dynamics and emphasise the importance of multi-year datasets for distinguishing ecological trends from stochastic changes. This strategy improves monitoring practices for marine ecosystems under anthropogenic stressors.

• Khan, Taimur; Koning, Koen de; Endresen, Dag; Gelete, Desalegn Chala & Kusch, Erik (2025). TwinEco: A Unified Framework for Dynamic Data-Driven Digital Twins in Ecology. Ecological Informatics. ISSN 1574-9541. 91. doi: 10.1016/j.ecoinf.2025.103407. Full text in Research Archive Show summary

  The burgeoning interest in digital twin (DT) technology presents a transformative potential for ecological modelling, offering new ways to model the complex dynamics of ecosystems. This paper introduces the TwinEco framework, designed to mitigate fragmentation in the development and deployment of DT applications in ecology. Compared to traditional modelling frameworks, TwinEco emphasises modularity and flexibility by introducing “layers” and “components” for DTs, accommodating diverse ecological applications without necessitating the deployment of all components. This modular approach ensures adaptability and scalability, promoting interoperability and integration with broader initiatives like Destination Earth. Digital twins in ecology offer significant advancements over traditional approaches by explicitly modelling changing processes and states over time, integrating extensive data, and enabling real-time feedback loops by actuating events or policies in the “real-world”. The framework’s capacity to adjust to changing environmental conditions enhances its predictive accuracy and responsiveness. This paper highlights the necessity for a unified framework to prevent divergent interpretations and ensure the interoperability of DT applications across ecological domains. Future recommendations include expanding case studies to demonstrate the framework’s applicability, assessing the potential of Dynamic Data-Driven Application Systems (DDDAS) paradigm within ecological DTs, and exploring interactions between components to optimise performance. Emphasising model-data fusion and fostering a shared terminology within the ecological community are crucial for the framework’s success. TwinEco aims to provide a robust foundation for ecological digital twins, enabling timely, data-driven decision-making to address global environmental challenges.

• Calvet, Nathalie; Bluhm, Bodil Annikki Ulla Barbro; Yoccoz, Nigel Gilles & Altenburger, Andreas (2024). Shifting invertebrate distributions in the Barents Sea since pre-1900. Frontiers in Marine Science. 11. doi: 10.3389/fmars.2024.1421475. Full text in Research Archive Show summary

  Marine invertebrate habitats are experiencing warming, and oceanic carbon dioxide levels are on the rise. These changes result in shifts in species distributions. Monitoring and understanding these shifts provides vital information because each species plays a unique ecological role, and the human utilization of marine species is intrinsically linked to their geographic locations. Here, we examine distribution shifts of marine invertebrates in the Barents Sea since pre-1900. Using data from the Global Biodiversity Information Facility, we analyzed species occurrences across warm, cold and mixed temperature zones, distinguishing between benthic and pelagic taxa. Our findings indicate community shifts in each of five separated time periods, with the most pronounced shifts occurring after 1980 in the cold and mixed zones, and earlier in the warm zone. The significant biogeographical changes at the community scale occurred both in benthic and pelagic realms, yet with differing trajectories in the period past 2000, and largely coincided with increased Atlantic Water inflow and reduced ice cover. Several invertebrate taxa exhibited a northward movement, falling into two categories: species migrating into the Barents Sea from the Norwegian mainland shelf, and those relocating from the southern Barents Sea to areas with mixed and colder temperatures. Some of these species may serve as indicator species for monitoring ecosystem and community change. The study highlights the importance of long-term datasets in quantifying community distribution shifts and understanding their ecological impacts.

• Lecarpentier, Damien; Biro, Timea; Endresen, Dag; Golivets, Marina; Grimm, Volker & Islam, Sharif [Show all 13 contributors for this article] (2024). Developing Prototype Digital Twins for biodiversity conservation and management: achievements, challenges and perspectives. Research Ideas and Outcomes (RIO). 10(e133474). doi: 10.3897/rio.10.e133474. Full text in Research Archive Show summary

  The BioDT project, funded by the European Union Horizon Europe Programme, seeks to investigate and push the boundaries of methodological, intellectual, data, technical and relevance aspects of the digital twin (DT) approach for understanding and predicting biodiversity patterns and processes. In this special issue, we present the reasoning and goals of the project and the overall advancements made towards the development of ten prototype Digital Twins (pDTs). Based on models of ecosystems, species and biological processes, digital twins integrate diverse data sources with advanced modelling and simulation techniques to provide a comprehensive, dynamic and data-driven understanding of biodiversity. Leveraging the EuroHPC LUMI infrastructure and data and expertise from GBIF, eLTER, DiSSCo and LifeWatch ERIC research infrastructures, the project aims to develop hybrid models combining the strengths of statistical and process-based models for improved predictive capabilities. While there are specific challenges and limitations to biodiversity DTs, the pDTs of BioDT lay the foundation for model-data fusions that will offer potential benefits to a wide range of end-users, from researchers and conservation organisations to policy-makers, land managers, educators and private sector companies. By fostering global interoperability in biodiversity data and research, BioDT paves the way for future collaborative efforts in biodiversity conservation and management.

• Chala, Desalegn; Kusch, Erik; Weiland, Claus; Andrew, Carrie; Grieb, Jonas & Rossi, Tuomas [Show all 8 contributors for this article] (2024). Prototype biodiversity digital twin: crop wild relatives genetic resources for food security. Research Ideas and Outcomes (RIO). 10. doi: 10.3897/rio.10.e125192. Full text in Research Archive Show summary

  Amidst population growth and climate-driven crop stresses such as drought, extreme weather, fungal and insect pests, as well as various crop diseases, ensuring food security demands innovative strategies. Crop wild relatives (CWR), wild plants in the same genus as the crop as well as wild populations belonging to the same species as the crop, offer novel genetic resources crucial for enhancing crop resilience against these stress factors. Here, we introduce a prototype digital twin (pDT) to aid in searching and utilising CWR genetic resources. Using the MoDGP (Modelling the Germplasm of Interest) tool, the pDT enables mapping geographic areas where stress-tolerant CWR populations can be found. With its graphical user interface, it offers flexibility in selecting genetic resources from CWR tailored to enhance resilience of various crops against diverse stress factors.

• Gelete, Desalegn Chala; Endresen, Dag; Demissew, Sebsebe; Slaughter, Laura Ann; Johnsen, Einar Broch & Stenseth, Nils Christian (2024). Address Social Injustices in Taxonomy: Implement Extended Revisions of Names with Ethical Issues and Persistent Identifiers for Tracing Name Changes. preprints.org > mathematics & computer science > information technology & data management. doi: 10.20944/preprints202407.1673.v1. Full text in Research Archive Show summary

  The binomial nomenclature system, introduced by Carl Linnaeus in the 18th century, has been fundamental for scientific communication and data management. Despite its utility, some scientific names reflect historical biases and ethical issues, including colonial legacies, racism, sexism, and derogatory terms. Recent debates highlight the need to address these injustices, with arguments both for and against revising such names. Critics argue that extensive revisions could disrupt scientific stability, while proponents emphasize the moral imperative to correct these issues. In this opinion paper, we advocate for the establishment of a dedicated committee within international nomenclature bodies to revise taxonomic names with clear ethical concerns and recommend the use of persistent identifiers to effectively manage and track name changes, mitigating potential disruptions to taxonomy and the science that depends on it. By adopting transparent revision processes and making use of digital technology, we can address ethical issues without remarkable upheaval. Science should not perpetuate historical injustices, and it is vital for the scientific community to proactively address social injustices in nomenclature to mitigate ongoing debates and resistance.

• Andrew, Carrie; Islam, Shariful; Weiland, Claus & Endresen, Dag (2024). Biodiversity data standards for the organization and dissemination of complex research projects and digital twins: a guide. arXiv.org. ISSN 2331-8422. doi: 10.48550/arXiv.2405.19857. Full text in Research Archive Show summary

  Biodiversity data are substantially increasing, spurred by technological advances and community (citizen) science initiatives. To integrate data is, likewise, becoming more commonplace. Open science promotes open sharing and data usage. Data standardization is an instrument for the organization and integration of biodiversity data, which is required for complex research projects and digital twins. However, just like with an actual instrument, there is a learning curve to understanding the data standards field. Here we provide a guide, for data providers and data users, on the logistics of compiling and utilizing biodiversity data. We emphasize data standards, because they are integral to data integration. Three primary avenues for compiling biodiversity data are compared, explaining the importance of research infrastructures for coordinated long-term data aggregation. We exemplify the Biodiversity Digital Twin (BioDT) as a case study. Four approaches to data standardization are presented in terms of the balance between practical constraints and the advancement of the data standards field. We aim for this paper to guide and raise awareness of the existing issues related to data standardization, and especially how data standards are key to data interoperability, i.e., machine accessibility. The future is promising for computational biodiversity advancements, such as with the BioDT project, but it rests upon the shoulders of machine actionability and readability, and that requires data standards for computational communication.

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• Tykarski, Piotr; Torma, Michal; Theocharides, Soulaine; Rożek, Katarzyna Wszałek-; Addink, Wouter & Endresen, Dag (2026). AI for specimen labels - final dissemination workshop. doi: https:/www.gbif.no/events/2026/ai-for-specimen-labels---final-dissemination-works.html. Full text in Research Archive Show summary

  For participants from previous events and new individuals interested in the use of AI in transcribing specimen labels. We summarize the project's progress, including information about DiSSCo and its annotation infrastructure, as well as the current status of SpLAT - Specimen Label Automated Transcriber. We will also test SpLAT using different LLMs and discuss possible methods of evaluating the tool's results, as well as the future plans and opportunities.

• Endresen, Dag (2026). Building the GBIF network in Norway. doi: 10.5281/zenodo.18310610. Full text in Research Archive
• Pitusi, Vanessa; Kongshavn, Katrine; Endresen, Dag; Morvik, Arfinn; Primo, Rocio Castano & Altenburger, Andreas (2025). Advancing Marine Biodiversity Knowledge: Integrating Norwegian Marine Data into Global Observing Systems. doi: https:/www.livingdata2025.com/program.html?session=6796407_2025-10-23_Ballroom%20B1. Full text in Research Archive Show summary

  Knowledge about marine biodiversity is essential for sustainable development, effective conservation, and the management of ecosystem services. Emerging technologies and advances in data standardization now enable the routine incorporation of biological and ecological data into ocean surveys and monitoring programs at local, regional, and global scales. To support these efforts, the Arctic University Museum of Norway has joined the Ocean Biodiversity Information System (OBIS) network and is actively working to publish all Norwegian marine biodiversity data, including marine data from museum collections to OBIS. We aim to simultaneously publish marine data to both OBIS and the Global Biodiversity Information Facility (GBIF), ensuring broader accessibility and interoperability. This presentation highlights our efforts to integrate Norwegian marine biodiversity data into global observing systems, aligning with the CARE (Collective Benefit, Authority to Control, Responsibility, Ethics) and FAIR (Findable, Accessible, Interoperable, Reusable) principles. By leveraging advances in data standardization, legal frameworks, and open-access databases, we aim to contribute to critical regional and global assessments of biodiversity change. Our work emphasizes the importance of publishing best practices to ensure that biodiversity data are implementable, intercomparable, and scalable across local and global contexts. This case study demonstrates how coordinated efforts in data standardization, capacity development, and interoperability can strengthen marine biodiversity observation systems. By sharing our experiences, we hope to inspire new collaborations and strategies that advance the integration of marine biodiversity data into global frameworks, ensuring that biodiversity knowledge informs sustainable ocean management and conservation efforts.

• Pitusi, Vanessa & Altenburger, Andreas (2025). Engaging Communities and Improving Accessibility: Natural History Collections as Catalysts for Biodiversity Knowledge Sharing. doi: https:/www.livingdata2025.com/program.html?session=6798479-1_2025-10-22_Ballroom%20B1. Full text in Research Archive Show summary

  Natural history collections are invaluable libraries of biodiversity knowledge. By displaying historical occurrences of taxa, these collections can be extremely helpful in addressing the global biodiversity crisis. However, natural history collections often remain underutilized due to their limited visibility, funding, and engagement with non-academics. This presentation highlights our approach to addressing these challenges by publishing natural history collections FAIR through the Global Biodiversity Information Facility (GBIF) and Ocean Biodiversity Information System (OBIS), at the Arctic University Museum of Norway. Through our partnership with GBIF, we have made 495,203 museum records available via a hosted portal (https:||specimens.tromsomuseum.no|en), covering both botanical and zoological collections. Original label information and, when available, specimen photos are included with every record, making them an invaluable tool for research, education, and policy-making. In addition to increasing the visibility of our collections, our digitization and open access initiatives have promoted cooperation among regional, national, and international networks. To date, 1,334 publications have used the occurrence data from our natural history collections and cited them, illustrating the positive impact of disseminating biodiversity knowledge. We hope to encourage increased participation and capacity building by involving communities in the use and access of these resources, guaranteeing that biodiversity data can guide conservation and policy initiatives at all levels. The significance of freely disseminating natural history collections and, by extension, biodiversity knowledge is highlighted by various case studies in this presentation. We present examples of how sharing biodiversity data has sparked interaction with scientists, journalists, and students. To tackle the global biodiversity crisis, we have to work together more effectively, exchange knowledge, and make the most of biodiversity data.

• Endresen, Dag (2025). Agrobiodiversity thematic community introduction. Full text in Research Archive Show summary

  In this session, the Nodes Committee will be joined by representatives from the Science Committee to explore thematic areas of relevance, from agrobiodiversity and marine ecosystems to invasive species and Indigenous data governance. Lightning talks will highlight current and emerging thematic areas, followed by a panel discussion on how GBIF nodes can leverage these themes to engage new data communities, build partnerships, and strengthen GBIF’s network and impact.

• Endresen, Dag; Morris, William; Rodrigues, Andrew & Waller, John (2025). Efficient data access for data reporting - Global Nodes. Full text in Research Archive Show summary

  This topic relates to approaches to efficiently access GBIF-mediated data for the purpose of generating data reports. Recent developments at GBIF include the availability of GBIF snapshots on cloud computing infrastructures and the ability to query GBIF using SQL allowing for e.g. data metrics and custom data reports rather than downloading individual records. Additionally, emerging data cube formats will provide an opportunity to efficiently analyze biodiversity trends on spatiotemporal data.

• Pitusi, Vanessa & Altenburger, Andreas (2025). The hosted portal of the Arctic University Museum of Norway - an example of how to provide open access to natural history collections. doi: https:/www.natsca.org/natsca2025. Full text in Research Archive
• Chala, Desalegn (2025). BioTorsdag: Digital Twins for Ecology, Conservation and Food Security - University of Oslo Library. doi: https:/biodt.eu/events/biodt-biotorsdag-digital-twins-ecology-conservation-and-food-security. Full text in Research Archive Show summary

  This BioTorsdag focuses on Digital twin technology, a technology which is emerging as an innovative tool in life science. Desalegn Chala, from Natural History Museum, will explain what a Digital twin is and how this technology has potential to revolutionizing knowledge production and decision-making processes.

• Endresen, Dag & Schigel, Dmitry (2025). Introduction to GBIF and GBIF Resources. doi: https:/biodt.eu/events/agroclimeumetsat-demonstration-workshop-and-stakeholder-meeting-rabat. Full text in Research Archive
• Endresen, Dag (2025). Improving our knowledge on genetically detected biodiversity distribution. doi: https:/biodt.eu/events/biodiversity-digital-twins-and-destination-earth-ecosystem. Full text in Research Archive
• Russell, Laura Anne; Grant, Sharon; Pamerlon, Sophie; Bloom, David; Musinguzi, Laban & Rabetrano, Tsiky [Show all 8 contributors for this article] (2025). Developing a standard, open and replicable course curriculum to enable mobilization and use of biodiversity data. doi: https:/www.livingdata2025.com/program.html?abstract=7020659. Full text in Research Archive Show summary

  The Global Biodiversity Information Facility (GBIF) empowers its global network through capacity-building activities that promote and enable the efficient mobilization and use of information about biodiversity. These activities work across capacity development levels, targeting individuals, institutions, nations, and global regions. Training plays a key role in expanding the communities of practice engaged with the collection and curation of biodiversity.GBIF’s training efforts build partnerships that institutionalize new capacity within a growing network of data publishing institutions. Development and delivery of training materials is supported through GBIF Participant nodes, regional support teams, and the GBIF community of practice.This presentation will highlight the work GBIF has undertaken over the last 10 years to develop a standardized, open, and replicable training curriculum with examples from the Biodiversity Information for Development (BID) programme and the Capacity Enhancement Support Programme (CESP) where materials have been reused and adapted. The presentation will also outline newly developed materials and encourage their further translation, adaptation and reuse. And finally, we will discuss how the community can engage with the development and delivery of the materials.

• Weiland, Claus; Bauer, Daniel; Kusch, Erik; Chala, Desalegn & Endresen, Dag (2025). Crop Wild Relatives and Destination Earth : Benefits and Lessons Learned. doi: 10.5281/ZENODO.15322592. Full text in Research Archive Show summary

  The presentation of the interoperability between Crop Wild Relatives, a prototype Digital Twin of BioDT project, and Destination Earth project.

• Chala, Desalegn; Kusch, Erik; Rossi, Tuomas; Juottonen, Heli; Weiland, Claus & Grieb, Jonas [Show all 11 contributors for this article] (2025). BioDT uc-CWR: Crop Wild Relative Digital Twin. doi: 10.5281/ZENODO.15696971. Full text in Research Archive Show summary

  BioDT: Crop Wild Relative prototype Digital Twin (CWR pDT). The prototype digital twin (pDT) aids in searching and utilising CWR genetic resources. Using the MoDGP (Modelling the Germplasm of Interest) tool, the pDT enables mapping geographic areas where stress-tolerant CWR populations can be found. With its graphical user interface, it offers flexibility in selecting genetic resources from CWR tailored to enhance the resilience of various crops against diverse stress factors.

• Kongshavn, Katrine (2025). Marine Biodiversity Data: where to find, how to share. FAIR principles, GBIF and OBIS. Full text in Research Archive
• Mahlangu, Sibusiso; Ewers, Isabelle; Carvalho, Cintia Oliveira; Schrøder-Nielsen, Audun; Dunthorn, Micah & Karlsen, Hans Erik [Show all 12 contributors for this article] (2025). Investigating the dynamics of the aquatic community in Oslofjord through time series analysis of eDNA. BioRxiv. ISSN 0362-4331. doi: 10.1101/2025.02.05.636659. Full text in Research Archive
• Endresen, Dag & Raes, Niels (2024). Biodiversity monitoring data via GBIF. Full text in Research Archive
• Endresen, Dag (2024). Accessing and publishing marine biodiversity data in GBIF and OBIS. Full text in Research Archive Show summary

  Webinar about Digital Twins of the Ocean and Biodiversity - plenary presentation of data publication in OBIS and GBIF.

• Chala, Desalegn; Kusch, Erik; Andrew, Carrie; Torma, Michal; Johaadien, Rukaya Sarah & Kehel, Zakaria [Show all 9 contributors for this article] (2024). BioDT Hackathon: Second End-Users Workshop, January 2024. Full text in Research Archive Show summary

  Three-day hackathon titled Harnessing Digital Twinning for Sustainable Agriculture: Predictive Characterisation and Conservation of Crop Wild Relatives, takes place from January 23rd to 25th, 2024 in Oslo, Norway. The event, promises to unravel the immense potential of digital twinning in revolutionizing global agricultural practices.

• Endresen, Dag; Raes, Niels; Kusch, Erik; Katusic, Luka; Borodin, Oleg & Palpurina, Salza (2024). GBIF Europe and Central Asia Nodes meeting 2024. Full text in Research Archive Show summary

  The 16th meeting of the GBIF Europe and Central Asia nodes is hosted by the GBIF Croatia from 26 to 29 of May 2024 the in-person and on-site meeting is open to node managers from the European and Central Asia participant nodes. Non-member countries and international organizations are invited to express their interest in joining the meeting as observers. The ECA nodes have been through an open regional process, led by Dag Endresen and Niels Raes, to select the dates and country to host the meeting. The meeting will be held in Zagreb. The selection of Croatia also reflects the wish to strengthen engagement in the Balkans and the visibility of GBIF in this relatively new GBIF Participant country.

• Johaadien, Rukaya Sarah; Torma, Michal; Boer, Hugo de; Meyke, Evgeniy; Schigel, Dmitry & Karimov, Farkhod (2024). GBIF in Central Asia new aspects of development Workshop. Full text in Research Archive Show summary

  Physical workshop and conference with optional digital participation, in Tashkent, Uzbekistan. Providing capacity-building on digitization techniques, data publication, and data cleaning, and co-creating Russian language resources. This project aims to enhance data publication and bioinformatics in Uzbekistan and Tajikistan.

• Finstad, Anders Gravbrøt; Altenburger, Andreas; Bakken, Vidar; Pitusi, Vanessa; Hovstad, Knut Anders & Endresen, Dag (2024). GBIF seminar in Tromsø, May 2024. Full text in Research Archive Show summary

  The Norwegian GBIF node in cooperation with the Arctic University Museum of Norway would like to welcome you to an open biodiversity data seminar on Thursday 23rd and Friday 24th of May in Tromsø at Tromsø Museum. On day one, we will present the GBIF along with interesting use cases demonstrating how this infrastructure can help make your biodiversity research transparent and reproducible. On day 2 we offer hands-on training with data publishing. This is a fantastic opportunity to work on your data with the assistance of experts. We invite you to bring your own data. It is also possible to practise with dummy data that we can provide for you. No experience is required, as long as you know and understand your own dataset!

• Islam, Sharif; Gordillo, Julian Lopez; Endresen, Dag & Andrew, Carrie (2024). Bridging Data Standards and FAIR Principles in Biodiversity Digital Twinning: Prototyping, Challenges, Lessons Learned, and Future Plans. Biodiversity Information Science and Standards (BISS). 8. doi: 10.3897/biss.8.133089. Full text in Research Archive Show summary

  Digital twins combine modelling, domain knowledge, computing power, and multiple datasets to offer the potential to unlock new insights into biodiversity (de Koning et al. 2023). The Biodiversity Digital Twin (BioDT) project pioneers this approach to aid in understanding biodiversity through prototyping digital twins (Golivets et al. 2024). However, working with biodiversity data presents challenges due to their dynamic and diverse nature as well as the need for having to deal with incompleteness, uncertainties (Rocchini et al. 2011), disproportionate representation patterns in global studies from wealthier economies (Hughes et al. 2024), and issues with data aggregation and integration (Wüest et al. 2020). Similar to BioDT, there are also plans for creating a Digital Twin of the Ocean (DTO). DTO-Bioflow project addresses these data challenges in the marine domain, where studies show that although European seas host 48,000 marine species (75% described), the data are not yet FAIR (Findable, Accessible, Interoperable, and Reusable) (Ramírez et al. 2022). These challenges hamper the modelling capabilities needed for effective predictions and conservation prioritisation. The adaptability of digital twins across temporal and spatial scales and their ability to model dynamic ecosystems make them ideal for biodiversity research and real-time conservation efforts. However, their success hinges on the consistent integration and alignment of data from disparate sources (Trantas et al. 2023). This integration involves standardising terms used to describe datasets, such as temporal coverage or controlled vocabularies like "Forest" for targetHabitatScope. Thus, adopting data standards is essential. Additionally, challenges such as model bias (Lewers 2023), research context, and data provenance must be considered, adding complexity to metadata capture and alignment. BioDT addresses these challenges with modular building blocks for data integration, model deployment, and workflow management. This approach facilitates the gradual adoption of data standards and FAIR principles, which need to encompass not just data, but also models and software. As automation, ease of reproducibility, and deployability are critical for digital twinning success, data integration and interoperability issues may arise due to missing or insufficient parameter descriptions in the model, incomplete information on data selection, and the unavailability of required software package details. Thus, data standardisation provides a pathway for a consistent approach that can be adopted for different use cases. Common data sources in BioDT, like species occurrences and environmental variables, benefit from standards such as Darwin Core (Wieczorek et al. 2012) and the Ecological Metadata Language (Jones et al. 2019). While valuable, these standards may not fully encompass the complexity needed for comprehensive biodiversity digital twins. Additionally, differing familiarity with these standards and FAIR principles among communities pose challenges. Continuous adoption of data standards, alongside exploring complementary approaches like schema.org or bioschemas.org for capturing diverse (meta)data, is essential. Collaboration with data providers, modellers, and various research infrastructures is also crucial (Andrew et al. 2024).

• Weiland, Claus; Grieb, Jonas; Bauer, Daniel; Gelete, Desalegn Chala; Kusch, Erik & Andrew, Carrie [Show all 7 contributors for this article] (2024). Dataspace Integration for Agrobiodiversity Digital Twins with RO-Crate. Biodiversity Information Science and Standards (BISS). 8. doi: 10.3897/biss.8.134479. Full text in Research Archive Show summary

  A severe impact of human-induced climate change is the global decrease in crop yields, threatening the United Nations sustainable development goal (SDG) to end hunger, achieve food security, improve nutrition, and promote sustainable agriculture (SDG 2: “Zero Hunger Goal”). Decision-making on appropriate mitigation strategies requires data integration from heterogeneous data-rich contexts including Earth observation (EO), biodiversity monitoring, gene banks as well as socio-economic data. Accordingly, large-scale initiatives for thematic data spaces, such as the European projects Destination Earth (DestinE) and the Green Deal Data Space, have been launched. Underutilized crops and crop wild relatives (CWR) can contribute to mitigating the impacts of climate change since their greater genetic diversity allows adaptation of agro-food sources to extreme weather events such as flooding and drought or emerging crop pests. Within the framework of Biodiversity Digital Twin (BioDT), a prototype digital twin for crop genetic resources modeling is under development. This prototype combines the scanning of genetic resources of CWRs and traditional cultivars for promising pest resistance and abiotic tolerance traits with advanced species distribution modeling and actual climate scenarios from EO. The aim is to generate habitat suitability maps and identify potential areas where relevant populations are potentially growing (Chala et al. 2024). The talk gives an overview of data models used to facilitate the required interoperability of both Earth models and environmental data within and across different data spaces such as the DestinE Data Lake (Duatis Juarez et al. 2023). Based on our findings from the use case of agrobiodiversity digital twins, we will discuss approaches for processing machine-actionable digital objects (Fig. 1) containing workflow information (i.e., in the Common Workflow Language format, Crusoe et al. 2022), and for sharing resulting research data in a FAIR (Findable, Accessible, Interoperable, and Reusable) manner by leveraging on so-called webby FAIR Digital Objects involving Research Object Crate (RO-Crate, Soiland-Reyes et al. 2022), FAIR Signposting (Soiland-Reyes et al. 2024) and schema.org and its Bioschemas extension respectively (Castro et al. 2020),

• Mering, Sabine von; Cubey, Robert W. N.; Endresen, Dag; Hendriksen, Annika; Leachman, Siobhan & Mietchen, Daniel [Show all 7 contributors for this article] (2024). Advancing Community Curation of Research Expeditions: A Collaborative Journey with Wikidata and Biodiversity Information Standards. Biodiversity Information Science and Standards (BISS). 8(e138921). doi: 10.3897/biss.8.138921. Full text in Research Archive Show summary

  Research expeditions are an important source of specimens in natural history collections. To further open up and increase the accessibility of related collection data, unambiguous naming of such events is required, and stable identifiers for the expeditions are needed. In the absence of a global catalogue for expeditions, we recommend the usage of Wikidata Q identifiers. The sharing of metadata and descriptions will facilitate the linking of material distributed across museums and related research data. It will also help to identify further specimens with missing metadata belonging to the same expeditions.

• Torma, Michal & Endresen, Dag (2024). Biodiversity data publication workshop at UiO 17 September 2024. Full text in Research Archive Show summary

  The Natural History Museum MaNa group and Norwegian Global Biodiversity Information Facility (GBIF) node invite students, PhDs, postdocs, researchers, and faculty at the University of Oslo and other institutions for a 1-day workshop on Tuesday, 17 September 2024.

• Kongshavn, Katrine; Altenburger, Andreas & Endresen, Dag (2024). GBIF Norway - we help publishing your biodiversity data. Full text in Research Archive Show summary

  GBIF—the Global Biodiversity Information Facility—is an international network and data infrastructure funded by the world’s governments and aimed at providing anyone, anywhere, open access to data about all types of life on Earth. Coordinated through its Secretariat in Copenhagen, the GBIF network of participating countries and organizations, working through the participant nodes, provides data-holding institutions around the world with common standards, best practices, and open-source tools enabling them to share biodiversity information. This knowledge derives from many different kinds of sources, including everything from museum specimens collected in the 18th and 19th centuries to DNA barcodes and smartphone photos recorded in recent days and weeks. Information aggregated by GBIF serves a wide variety of uses and data products developed by stakeholders external to the core GBIF community. The GBIF network operates capacity development programs targeting support for biodiversity data services, including in close collaboration with international and national academic institutions such as ForBio. The role of GBIF aligns very well with and complements the focus of ForBio to build capacity “to meet society’s needs for biodiversity expertise”. GBIF Norway is the Norwegian participant node in the Global Biodiversity Information Facility, GBIF. Our main task is to make primary data on biological diversity from the Norwegian collections and observation databases freely available and to coordinate and support GBIF-related activities and data use in Norway and internationally.

• Chala, Desalegn; Endresen, Dag; Demissew, Sebsebe; Slaughter, Laura Ann; Johnsen, Einar Broch & Stenseth, Nils Christian (2024). Stop using racist, unethical, and inappropriate names in taxonomy. Proceedings of the National Academy of Sciences of the United States of America (PNAS). ISSN 0027-8424. 121(45). doi: 10.1073/pnas.2415490121. Full text in Research Archive Show summary

  In this opinion piece, we address the growing debate surrounding the historical biases embedded in scientific names, which reflect colonialism, racism, sexism, and casteism. While many advocate for revising these names to align with modern ethical standards, concerns about disrupting binomial nomenclature stability persist. We argue that, in the digital era, effective solutions exist to manage name changes without significant disruption. Our paper proposes the creation of dedicated committees to handle names with clear ethical issues, the implementation of persistent identifiers to track changes, and the establishment of strict rules and guidelines against using scientific names with ethical issues and mechanisms to check for such problems before endorsing any new names. We emphasize that science must evolve to reflect contemporary values and not perpetuate historical injustices.

• Bonchev, Georgi; Kamenova, Stefaniya; Wirta, Helena; Boer, Hugo de; Endresen, Dag & Frøslev, Tobias Guldberg [Show all 9 contributors for this article] (2023). Course on DNA barcode data in BOLD and GBIF - Bulgaria. Full text in Research Archive Show summary

  Accelerating biodiversity research through DNA barcodes, collection, and observation data. Regional Training course for M.Sc. and Ph.D. students with expert trainers and trainers-in-training - Bulgaria

• Kongshavn, Katrine; Endresen, Dag; Johaadien, Rukaya Sarah; Bakken, Vidar & Torma, Michal (2023). University Museum of Bergen - Data publication workshop. Full text in Research Archive Show summary

  The Norwegian Global Biodiversity Information Facility (GBIF) node and the University Museum of Bergen welcomes you to a 2-day workshop to publish biodiversity data as Darwin Core Archives on March 13-14th, 2023.

• Chala, Desalegn (2023). Crop wild relatives Digital Twin: where data flow meets computation to revolutionize agricultural research. Full text in Research Archive Show summary

  While the human population is rapidly increasing and expected to reach 11 billion by the end of this century, global agricultural production is challenged due to climate change. To meet the UN Sustainable Development Goal targets and to bring about zero hunger, we need to boost our food production. For this, we need crops with higher yields, nutritional values, and the ability to resist diseases and adapt to changing environments. Untapped genetic resources to meet these goals are often harbored in crop wild relatives. Digital twinning represents a promising technology for the model-based identification and use of these resources by facilitating: 1) data flow and fusion from distributed data sources), 2) dynamic model updating, 3) automated model uncertainty analysis (validation against real-life data), and 4) provision of automated alerts for new genetic resources with predicted target genetic properties for plant breeders, conservation scientists and policymakers. Here, we showcase the importance of data flow to develop a digital twin that facilitates improving the nutritional quality of grasspea but can be transferable across traits and crops. Grasspea is a climate-smart crop that requires only residual moisture to complete its life cycle and is considered a lifesaver during severe droughts in tropical and subtropical regions. While it is protein-rich and could potentially help in beating protein malnutrition in the future, it also contains a neurotoxin that can cause paralysis of the lower limbs in adults and brain damage in children, if consumed over longer periods. Specific goals of our work include modelling geographic areas that present populations of grasspea wild relatives and land races with potential alleles to lower the toxicity content of grasspea to a non-harmful level.

• Kusch, Erik (2023). Workshop 1. Accessing, handling, and referencing open biodiversity data using the Global Biodiversity Information Facility (GBIF). Full text in Research Archive Show summary

  In the age of changes and threat to the ecosphere at macroecological scales, big data has crystalized as a go-to tool for ecological research. To facilitate the creation of, access to, and referencing of contributors to such big data repositories, the Global Biodiversity Information Facility (GBIF) has established data streams that make readily available a wealth of biodiversity data. Navigating and accessing such large data sets and ensuring fair use and accreditation of observations can seem daunting. In this workshop, we will introduce GBIF, show how to navigate its data portal, demonstrate data streams to obtain and handle data programmatically, and communicate accreditation procedures.

• Johaadien, Rukaya Sarah; Frøslev, Tobias Guldberg; Plessis, Morne Du; Torma, Michal; Kamenova, Stefaniya & Braathen, Catherine [Show all 7 contributors for this article] (2023). Course on DNA barcode data in BOLD and GBIF - Cape Town, South Africa. Full text in Research Archive Show summary

  Accelerating biodiversity research through DNA barcodes, collection, and observation data. Regional Training Course for M.Sc. and Ph.D. students with expert trainers and trainers-in-training - Cape Town, South Africa.

• Endresen, Dag (2023). Presentation of the Biodiversity Digital Twin (BioDT) project for the University of Oslo (UiO) Natural History Museum (NHMO) Department of Research and Collections on 2023-03-24. Full text in Research Archive Show summary

  Presentation of the Biodiversity Digital Twin (BioDT) project for the University of Oslo (UiO) Natural History Museum (NHMO) Department of Research and Collections on 2023-03-24.

• Rechsteiner, Aud Helen Halbritter; Grainger, Matthew; Telford, Richard James; Kusch, Erik; Nilsen, Erlend Birkeland & Andrew, Carrie [Show all 9 contributors for this article] (2023). Living Norway Course on Open, Reproducible and Transparent Science in Ecology. Full text in Research Archive Show summary

  Universities, journals, and funding bodies increasingly demand open and reproducible research practices across the scientific community. Research data needs to be FAIR (findable, accessible, interoperable, and reusable), workflows need to be reproducible, and science needs to be transparent. This aims to improve the efficiency and quality of research and thus to increase the credibility of science. This course offers hands-on training on methods and technologies to make research more open, reproducible and transparent. The course is centred around the life-cycle of data from planning, managing, collecting, curating, analysing, publishing, storing, sharing and reusing data. It is aimed at PhD students (will be prioritised) as well as early-career researchers in ecology, who produce their own data (i.e. collect data in the field/lab), use data from others (i.e. databases) or both.

• Marsden, Luke; Johaadien, Rukaya Sarah; Torma, Michal & Endresen, Dag (2023). Marine data publishing workshop. Full text in Research Archive Show summary

  The Norwegian Global Biodiversity Information Facility (GBIF) node, in collaboration with the Nansen Legacy project, 2-day workshop to help you publish your biodiversity data as Darwin Core Archives! This is a fantastic opportunity to work on your data with the assistance of experts who are involved in developing the Darwin Core standards.

• Johaadien, Rukaya Sarah (2023). Zenodo and usage of communities. Full text in Research Archive Show summary

  What are the pros and cons of different general data archives? Which one suits your needs as researcher? In this Data Managers Network meeting UiO researchers will share their experiences with using different general open research data archives.

• Endresen, Dag & Tykarski, Piotr (2023). Europe and Central Asia Nodes meeting 2023. Full text in Research Archive Show summary

  The 2023 regional GBIF Europe and Central Asia Nodes meeting (ECA2023) in Warsaw, 15-18 May 2023.

• Kusch, Erik & Endresen, Dag (2023). BioDT task 4.3 kickoff workshop. Full text in Research Archive Show summary

  The BioDT task 4.3 kickoff was organized at the GBIF Europe and Central Asia regional nodes meeting in Warsaw 17th and 18th of May 2023.

• Endresen, Dag (2023). Biodiversity ontologies. Full text in Research Archive Show summary

  GBIF Norway was invited to the UiO Digital Scholar Centre Data Managers Network to present how we use biodiversity ontologies.

• Puglisi, Giuseppe; Bailo, Daniele; Gehlen, Karsten Peters-von; Bumberger, Jan; Steenbeek, Jeroen & Lange, Otto [Show all 18 contributors for this article] (2025). A Framework for Data Readiness (DaReFF). Zenodo. doi: 10.5281/ZENODO.15186741. Full text in Research Archive Show summary

  The Data Readiness Framework was developed in support of the EOSCLIMA proposal by the consortium responding to the call. From the proposal text: "EOSCLIMA will deliver a Data Readiness and FAIRness Framework (DaReFF) to support researchers contributing to the adaptation to climate change in understanding, adopting, and capitalising on FAIR and open data practices. [...] The framework allows assessment of the FAIRness and the readiness level of research data from a publication-, reproducibility-, analysis-, decision- (and machine-processing readiness) perspective [...]. It helps the researchers identify shortcomings in terms of FAIR and open data practices and provides them with suggestions in terms of tools that can be adopted to fill such gaps. Finally, it also helps the researchers in documenting the benefits of using FAIR and open data practices as the new norm."

• Hovstad, Knut Anders; Sommerli, Sindre Lysfjord; Endresen, Dag; Endrestøl, Anders; Fossøy, Frode & Heimstad, Ragnhild [Show all 11 contributors for this article] (2024). Kartlegging av artar og dataflyt for artsdata i Noreg - ei konseptutredning. Artsdatabanken. ISSN 9788292838686. doi: 10.48387/ARTSKARTLEGGING2024. Full text in Research Archive Show summary

  I arbeidet med konseptutredninga, har ein drøfta i kor stor grad ein skal detaljere beskrivingar av feltmetodikk. Variasjon mellom artar og ulike kartleggingsformål krev variasjon i kartleggingsmetodikk. Konseptutredninga vil ikkje kunne gi detaljerte svar på alle metodiske utfordringar, men gir eit metodisk rammeverk der fleire av elementa vil vere vesentlege bidrag til både å heve nivået og standardisere artskartlegging i Noreg.

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