GBIF - Global Biodiversity Information Facility

• de Koning, Koen; Broekhuijsen, Jeroen; Kühn, Ingolf; Ovaskainen, Otso Tapio; Taubert, Franziska & Endresen, Dag [Show all 8 contributors for this article] (2023). Digital twins: dynamic model-data fusion for ecology. Trends in Ecology & Evolution. ISSN 0169-5347. 38(10), p. 916–926. doi: 10.1016/j.tree.2023.04.010. Full text in Research Archive Show summary

  Digital twins (DTs) are an emerging phenomenon in the public and private sectors as a new tool to monitor and understand systems and processes. DTs have the potential to change the status quo in ecology as part of its digital transformation. However, it is important to avoid misguided developments by managing expectations about DTs. We stress that DTs are not just big models of everything, containing big data and machine learning. Rather, the strength of DTs is in combining data, models, and domain knowledge, and their continuous alignment with the real world. We suggest that researchers and stakeholders exercise caution in DT development, keeping in mind that many of the strengths and challenges of computational modelling in ecology also apply to DTs.

• Parker-Allie, Fatima; Pando, Francisco; Telenius, Anders; Ganglo, Jean C.; Vélez, Danny & Gibbons, Mark John [Show all 17 contributors for this article] (2021). Towards a Post-Graduate Level Curriculum for Biodiversity Informatics. Perspectives from the Global Biodiversity Information Facility (GBIF) Community. Biodiversity Data Journal. ISSN 1314-2836. 9(e68010). doi: 10.3897/BDJ.9.e68010. Full text in Research Archive Show summary

  Biodiversity informatics is a new and evolving field, requiring efforts to develop capacity and a curriculum for this field of science. The main objective was to summarise the level of activity and the efforts towards developing biodiversity informatics curricula, for work-based training and/or academic teaching at universities, taking place within the Global Biodiversity Information Facility (GBIF) countries and its associated network. A survey approach was used to identify existing capacities and resources within the network. Most of GBIF Nodes survey respondents (80%) are engaged in onsite training activities, with a focus on work-based professionals, mostly researchers, policy-makers and students. Training topics include data mobilisation, digitisation, management, publishing, analysis and use, to enable the accessibility of analogue and digital biological data that currently reside as scattered datasets. An initial assessment of academic teaching activities highlighted that countries in most regions, to varying degrees, were already engaged in the conceptualisation, development and/or implementation of formal academic programmes in biodiversity informatics, including programmes in Benin, Colombia, Costa Rica, Finland, France, India, Norway, South Africa, Sweden, Taiwan and Togo. Digital e-learning platforms were an important tool to help build capacity in many countries. In terms of the potential in the Nodes network, 60% expressed willingness to be recruited or commissioned for capacity enhancement purposes. Contributions and activities of various country nodes across the network have been highlighted and a working curriculum framework has been defined.

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• Meeus, Sofie; Ariño, Arturo; Bakken, Torkild; Braun, Paul; Dillen, Mathias & Endresen, Dag [Show all 12 contributors for this article] (2023). Who is Who in Natural History Collections? Show summary

  The "Who is Who in Natural History Collections?" trifold leaflet is an outcome from the People Identifiers workshop/hackathon organized in Oslo in January 2023 by the COST Action MOBILISE, CA17106, supported by COST (European Cooperation in Science and Technology). The leaflet points at resources to manage biographical data in natural history collections more efficiently and contains recommendations for researchers, curators, database managers and publishers to avoid duplication of effort between collections.

• von Mering, Sabine; Braun, Paul Jean-Charles; Cubey, Robert W. N.; Groom, Quentin; Haston, Elspeth M. & Hendriksen, Anikka [Show all 12 contributors for this article] (2023). Modelling research expeditions in Wikidata: best practice for standardisation and contextualisation. Biodiversity Information Science and Standards (BISS). ISSN 2535-0897. 7. doi: 10.3897/biss.7.111427. Show summary

  Expeditions and other collecting events are a major source of objects in natural history museums (e.g., Mesibov 2021). Historically, these trips were often transdisciplinary: biological and Earth science specimens were collected at the same time as ethnological or anthropological objects. As a result, specimens and other material gathered during the same expedition, as well as the related data and metadata, are often distributed across multiple institutions. Many expeditions were driven by colonial agendas, aiming to discover new resources to exploit, and their findings were seldom shared with the source countries and local people. Understanding these expeditions illuminates the colonial origins of museum collections, and contributes to recognizing and addressing their impacts (e.g., Das and Lowe 2018, Ashby and Machin 2021).

• Kusch, Erik (2023). Workshop 1. Accessing, handling, and referencing open biodiversity data using the Global Biodiversity Information Facility (GBIF). 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.

• Chala, Desalegn (2023). Crop wild relatives Digital Twin: where data flow meets computation to revolutionize agricultural research. 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.

• Halbritter Rechsteiner, Aud Helen; 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. 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.

• Melteig, Elina; Endresen, Dag; de Boer, Hugo; Khodosovtsev, Alexander & Moysiyenko, Ivan (2023). Mens bombene falt, snek forskerne ut en unik herbariesamling fra Kherson. [Internet]. Forkning.no. Show summary

  Hva var det som fikk forskere til å risikere livet i Ukraina for en objektsamling? Kherson State University i Ukraina har et unikt herbarium med 30.000 objekter. Forskerne hadde for lengst blitt evakuert. Likevel våget de seg tilbake mens krigen herjet rundt dem.

• Islam, Sharif; Koivula, Hanna; Endresen, Dag; Kusch, Erik; Schigel, Dmitry & Addink, Wouter (2023). Data Standards and Interoperability Challenges for Biodiversity Digital Twin: A novel and transformative approach to biodiversity research and application. Show summary

  The Biodiversity Digital Twin (BioDT) project (2022-2025) aims to create prototypes that integrate various data sets, models, and expert domain knowledge enabling prediction capabilities and decision-making support for critical issues in biodiversity dynamics. While digital twin concepts have been applied in industries for continuous monitoring of physical phenomena, their application in biodiversity and environmental sciences presents novel challenges (Bauer et al. 2021, de Koning et al. 2023). In addition, successfully developing digital twins for biodiversity requires addressing interoperability challenges in data standards. BioDT is developing prototype digital twins based on use cases that span various data complexities, from point occurrence data to bioacoustics, covering nationwide forest states to specific communities and individual species. The project relies on FAIR principles (Findable, Accessible, Interoperable, and Reusable) and FAIR enabling resources like standards and vocabularies (Schultes et al. 2020) to enable the exchange, sharing, and reuse of biodiversity information, fostering collaboration among participating research infrastructures (DiSSCo, eLTER, GBIF, and LifeWatch) and data providers. It also involves creating a harmonised abstraction layer using Persistent Identifiers (PID) and FAIR Digital Object (FDO) records, alongside semantic mapping and crosswalk techniques to provide machine-actionable metadata (Schultes and Wittenburg 2019, Schwardmann 2020). Governance and engagement with research infrastructure stakeholders play crucial roles in this regard, with a focus on aligning technical and data standards discussions. In addition to data, models and workflows are key elements in BioDT. Models in the BioDT context are formal representations of problems or processes, implemented through equations, algorithms, or a combination of both, which can be executed by machine entities. The current twin prototypes are considering both statistical and mechanistic models, introducing significant variations in (1) data requirements, (2) modelling approaches and philosophy, and (3) model output. The BioDT consortium will develop guidelines and protocols for how to describe these models, what metadata to include, and how they will interact with the diverse datasets. While discussions on this topic exist within the broader context of biodiversity and ecological sciences (Jeltsch et al. 2013, Fer et al. 2020), the BioDT project is strongly committed to finding a solution within its scope. In the twinning context, data and models need to be executed within a computing infrastructure and also need to adhere to FAIR principles. Software within BioDT includes a suite of tools that facilitate data acquisition, storage, processing, and analysis. While some of these tools already exist, the challenge lies in integrating them within the digital twinning framework. One approach to achieving integration is through workflow representation, encompassing standardised procedures and protocols that guide the acquisition, packaging, processing, and analysis of data. The project is exploring Research Object Crate (RO-Crate) implementation for this (Soiland-Reyes et al. 2022). Implementing workflows can ensure reproducibility, scalability, and transparency in research practices, enabling scientists to validate and replicate findings. The BioDT project offers a novel and transformative approach to biodiversity research and application. By leveraging collaborative research infrastructures and adhering to data standards, BioDT aims to harness the power of data, software, supercomputers, models, and expertise to provide new insights. The foundation provided by the data standards, including those of Biodiversity Information Standards (TDWG), is crucial in realising the full potential of digital twins, facilitating the seamless integration of diverse data sources and combinations with models.

• Johaadien, Rukaya Sarah; Frøslev, Tobias Guldberg; Du Plessis, Morne; 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. 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.

• Kusch, Erik & Endresen, Dag (2023). BioDT task 4.3 kickoff workshop. 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.

• Kongshavn, Katrine; Endresen, Dag; Johaadien, Rukaya Sarah; Bakken, Vidar & Torma, Michal (2023). University Museum of Bergen - Data publication workshop. 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.

• Endresen, Dag; Bakken, Vidar & Mckay, Reed April (2023). Data and Stats Forum at MINA NMBU. 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. Data available through the GBIF portal are primarily distribution data on plants, animals, fungi, and microbes for the world, and scientific names data. The workshop will demonstrate how you can access different types of biodiversity data published through the GBIF platform. And we will also have a brief "bring-your-own-data" workshop to demonstrate how you can publish your own research data to the GBIF platform and get a dataset DOI with data citation tracking services to follow what your dataset is reused for and by whom.

• Endresen, Dag & Tykarski, Piotr (2023). Europe and Central Asia Nodes meeting 2023. Show summary

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

• Marsden, Luke; Johaadien, Rukaya Sarah; Torma, Michal & Endresen, Dag (2023). Marine data publishing workshop. 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.

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

• Endresen, Dag (2023). Biodiversity ontologies. Show summary

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

• 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. 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.

• Johaadien, Rukaya Sarah (2023). Zenodo and usage of communities. 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 & Miller, Joe (2023). Overview of the Global Biodiversity Information Facility. Show summary

  GBIF Norway and the GBIF Secretariat were invited as speakers at the Plant Treaty (ITPGRFA) fifth meeting of the Scientific Advisory Committee (SAC) of the Global Information System (GLIS) in Rome from 8th to 9th May 2023.

• Johaadien, Rukaya Sarah (2023). AI seminar.
• Altenburger, Andreas (2023). Research at the Arctic University Museum of Norway.
• Frafjord, Karl; Bergersen, Robert & Altenburger, Andreas (2023). Fish collection (TSZP) The Arctic University Museum of Norway. Show summary

  Overview over specimens of Fish that are stored in the collection of the Arctic University Museum of Norway (previously Tromsø Museum).

• Frafjord, Karl; Dahlen, Håkon & Altenburger, Andreas (2023). Mammal collection (TSZM) The Arctic University Museum of Norway. Show summary

  Overview over specimens of mammals that are stored in the collection of the Arctic University Museum of Norway (previously Tromsø Museum).

• Dahlen, Håkon; Barrett, Robert & Altenburger, Andreas (2023). Bird collection (TSZ-bird) The Arctic University Museum of Norway. Show summary

  Overview over bird skins that are stored in the collection of the Arctic University Museum of Norway (previously Tromsø Museum).

• Dahlen, Håkon; Barrett, Robert & Altenburger, Andreas (2023). Bird egg collection (TSZ-bird-egg) The Arctic University Museum of Norway.
• Johaadien, Rukaya Sarah & Torma, Michal (2023). "Publish First": A Rapid, GPT-4 Based Digitisation System for Small Institutes with Minimal Resources. Biodiversity Information Science and Standards (BISS). ISSN 2535-0897. 7(e112428). doi: 10.3897/biss.7.112428. Show summary

  We present a streamlined technical solution ("Publish First") designed to assist smaller, resource-constrained herbaria in rapidly publishing their specimens to the Global Biodiversity Information Facility (GBIF). Specimen data from smaller herbaria, particularly those in biodiversity-rich regions of the world, provide a valuable and often unique contribution to the global pool of biodiversity knowledge (Marsico et al. 2020). However, these institutions often face challenges not applicable to larger herbaria, including a lack of staff with technical skills, limited staff hours for digitization work, inadequate financial resources for specialized scanning equipment, cameras, lights, and imaging stands, limited (or no) access to computers and collection management software, and unreliable internet connections. Data-scarce and biodiversity rich countries are also often linguistically diverse (Gorenflo et al. 2012), and staff may not have English skills, which means pre-existing online data publication resources and guides are of limited use. The "Publish First" method we are trialing, addresses several of these issues: it drastically simplifies the publication process so technical skills are not necessary; it minimizes administrative tasks saving time; it uses simple, cheap and easily available hardware; it does not require any specialized software; and the process is so simple that there is little to no need for any written instructions. "Publish first" requires staff to attach QR code labels containing identifiers to herbarium specimen sheets, scan these sheets using a document scanner costing around €300, then drag and drop these files to an S3 bucket (a cloud container that specialises in storing files). Subsequently, these images are automatically processed through an Optical Character Recognition (OCR) service to extract text, which is then passed on to OpenAI's Generative Pre-Transformer 4 (GPT-4) Application Programming Interface (API), for standardization. The standardized data is integrated into a Darwin Core Archive file that is automatically published through GBIF's Integrated Publishing Toolkit (IPT) (GBIF 2021). The most technically challenging aspect of this project has been the standardization of OCR data to Darwin Core using the GPT-4 API, particularly in crafting precise prompts to address the inherent inconsistency and lack of reliability in these Large Language Models (LLMs). Despite this, GPT-4 outperformed our manual scraping efforts. Our choice of GPT-4 as a model was a naive one: we implemented the workflow on some pre-digitized specimens from previously published Norwegian collections, compared the published data on GBIF with GPT-4's Darwin Core standardized output, and found the results satisfactory. Moving forward, we plan to undertake more rigorous additional research to compare the effectiveness and cost-efficiency of different LLMs as Darwin Core standardization engines. We are also particularly interested in exploring the new "function calling" feature added to the GPT-4 API, as it promises to allow us to retrieve standardized data in a more consistent and structured format. This workflow is currently under trial in Tajikistan, and may possibly be used in Uzbekistan, Armenia and Italy in the near future.

• Islam, Sharif; Koivula, Hanna; Endresen, Dag; Kusch, Erik; Schigel, Dmitry & Addink, Wouter (2023). Data Standards and Interoperability Challenges for Biodiversity Digital Twin: A novel and transformative approach to biodiversity research and application. Biodiversity Information Science and Standards (BISS). ISSN 2535-0897. 7. doi: 10.3897/biss.7.112373. Show summary

  The Biodiversity Digital Twin (BioDT) project (2022-2025) aims to create prototypes that integrate various data sets, models, and expert domain knowledge enabling prediction capabilities and decision-making support for critical issues in biodiversity dynamics. While digital twin concepts have been applied in industries for continuous monitoring of physical phenomena, their application in biodiversity and environmental sciences presents novel challenges (Bauer et al. 2021, de Koning et al. 2023). In addition, successfully developing digital twins for biodiversity requires addressing interoperability challenges in data standards. BioDT is developing prototype digital twins based on use cases that span various data complexities, from point occurrence data to bioacoustics, covering nationwide forest states to specific communities and individual species. The project relies on FAIR principles (Findable, Accessible, Interoperable, and Reusable) and FAIR enabling resources like standards and vocabularies (Schultes et al. 2020) to enable the exchange, sharing, and reuse of biodiversity information, fostering collaboration among participating research infrastructures (DiSSCo, eLTER, GBIF, and LifeWatch) and data providers. It also involves creating a harmonised abstraction layer using Persistent Identifiers (PID) and FAIR Digital Object (FDO) records, alongside semantic mapping and crosswalk techniques to provide machine-actionable metadata (Schultes and Wittenburg 2019, Schwardmann 2020). Governance and engagement with research infrastructure stakeholders play crucial roles in this regard, with a focus on aligning technical and data standards discussions. In addition to data, models and workflows are key elements in BioDT. Models in the BioDT context are formal representations of problems or processes, implemented through equations, algorithms, or a combination of both, which can be executed by machine entities. The current twin prototypes are considering both statistical and mechanistic models, introducing significant variations in (1) data requirements, (2) modelling approaches and philosophy, and (3) model output. The BioDT consortium will develop guidelines and protocols for how to describe these models, what metadata to include, and how they will interact with the diverse datasets. While discussions on this topic exist within the broader context of biodiversity and ecological sciences (Jeltsch et al. 2013, Fer et al. 2020), the BioDT project is strongly committed to finding a solution within its scope. In the twinning context, data and models need to be executed within a computing infrastructure and also need to adhere to FAIR principles. Software within BioDT includes a suite of tools that facilitate data acquisition, storage, processing, and analysis. While some of these tools already exist, the challenge lies in integrating them within the digital twinning framework. One approach to achieving integration is through workflow representation, encompassing standardised procedures and protocols that guide the acquisition, packaging, processing, and analysis of data. The project is exploring Research Object Crate (RO-Crate) implementation for this (Soiland-Reyes et al. 2022). Implementing workflows can ensure reproducibility, scalability, and transparency in research practices, enabling scientists to validate and replicate findings. The BioDT project offers a novel and transformative approach to biodiversity research and application. By leveraging collaborative research infrastructures and adhering to data standards, BioDT aims to harness the power of data, software, supercomputers, models, and expertise to provide new insights. The foundation provided by the data standards, including those of Biodiversity Information Standards (TDWG), is crucial in realising the full potential of digital twins, facilitating the seamless integration of diverse data sources and combinations with models.

• Johaadien, Rukaya Sarah; Torma, Michal; Rindal, Eirik & Barotov, Samariddin (2022). CESP mentoring - data publication and digitisation course for Tajikistan September 2022. Show summary

  GBIF data mobilization and publication course for the Tajikistan GBIF Node at the Institute of Botany, Plant Physiology and Genetics, Tajikistan National Academy of Sciences, Armenia (3 days). https://www.gbif.no/events/2022/cesp-tajikistan.html https://www.gbif.org/project/CESP2022-001/

• Marsden, Luke; Endresen, Dag; Johaadien, Rukaya Sarah; Torma, Michal & Altenburger, Andreas (2022). Nansen Legacy - Marine data publishing workshop in Tromsø in September 2022. Show summary

  Nansen Legacy (AeN) 3-day workshop to publish marine biodiversity data from the AeN project as Darwin Core Archives on September 20-22, 2022. With support from the Norwegian Global Biodiversity Information Facility (GBIF) node, and the Ocean Biodiversity Information System (OBIS, EurOBIS). https://www.gbif.no/events/2022/nansen-legacy-tromso.html

• Johaadien, Rukaya Sarah; Endresen, Dag & Torma, Michal (2022). An Update on Persistent Identifiers in Norwegian Biodiversity Data. Biodiversity Information Science and Standards (BISS). ISSN 2535-0897. doi: 10.3897/biss.6.91585. Show summary

  Persistent identifiers (PIDs) are reference keys to pieces of digital information or digital objects (Meadows and Haak 2018). PIDs are long-lasting, trustworthy and ideally globally unique, allowing information to be unambigiously associated with a digital object. This allows, for example, collection objects to be annotated with data (e.g., improved geographic coordinates) from different web services and databases (Page 2008). In 2014, Norway began an initiative to provide all museum specimens at the University of Oslo's Natural History Museum (UiO NHM) with PIDs persistent and globally unique identifiers (PIDs) in the form of universally unique identifiers (UUIDs) prefixed by a persistent uniform resource locator (PURL) (Endresen and Svindseth 2014). This poster provides an update of progress made in this endeavor, and details the technical set up and workflow, as well as problems encountered and reflections on the process. So far, roughly 40% of UiO NHM's collections have PIDs entered in the Darwin Core materialSampleID field for the collections management system. The main technical problem has been in configuring the PURL service to set up redirects correctly. In the future, we plan to migrate from PURLs to the Handle system which provides identifiers for digital objects, or to using DOIs (Digital Object Identifiers), which are an implementation of the Handle system (Paskin 2017).

• Endresen, Dag; Russell, Laura Anne; Schigel, Dmitry; Prylutskyi, Oleh; Johaadien, Rukaya Sarah & Torma, Michal [Show all 11 contributors for this article] (2022). Four-day program on open biodiversity data publishing and high-level data paper publishing, online for Ukraine in August 2022. Show summary

  Regional training course for M.Sc. and Ph.D. students from Ukraine with expert trainers and trainers-in-training, Tuesday 16 to Friday 19 August 2022. Plus preparatory assignments from 1st to 12th August, and post-course assignments from 22nd August to 3rd September. Successful attendees will be issued a certificate of attendance corresponding to 2 ECTS and a digital GBIF Certified Trainer badge. This training model has been tested in the Biodiversity Information for Development (BID) programme and is adapted to BioDATA needs. The course is designed for 16-20 participants. All applicants must submit a motivation letter as part of their registration. Lectures will be in English with teaching materials available both in English and Russian languages, with the support of Ukrainian-speaking mentors. https://www.nhm.uio.no/english/research/projects/biodata/activities/2022-ukraine.html

• Endresen, Dag; Russell, Laura Anne; Schigel, Dmitry; de Boer, Hugo; Johaadien, Rukaya Sarah & Torma, Michal [Show all 10 contributors for this article] (2022). Five-day program curriculum on open biodiversity data publishing, including excursion and bioblitz in Dilijan, Armenia in May 2022. Show summary

  Regional Training course for M.Sc. and Ph.D. students with expert trainers and trainers-in-training - Dilijan, Armenia (5 days), 1 to 5 May 2022. Successful attendees will be issued a certificate of attendance corresponding to 2 ECTS and a digital GBIF Certified Trainer badge. This training model has been tested in the Biodiversity Information for Development (BID) programme and is adapted to BioDATA needs. The course is designed for 16-20 participants. All applicants must submit a motivation letter as part of their registration. The lectures will be in English (with some teaching materials available in Armenian). https://www.nhm.uio.no/english/research/projects/biodata/activities/2022-armenia.html

• de Boer, Hugo; Endresen, Dag; Schigel, Dmitry; Russell, Laura Anne; Rydmark, Marcella Christine Orwick & Abrahamyan, Armine [Show all 9 contributors for this article] (2022). BioDATA final symposium for partner universities, ForBio, and GBIF at Tøyen in Oslo in November 2022. Show summary

  Typically, established researchers, museum curators, and collection managers are involved in data management and data publishing to national and global biodiversity data facilities. By training early career (student) biodiversity scholars, we will efficiently turn the current academic and education landscape into a more open-data-friendly one. The closing event will focus on addressing students from the University of Oslo. Two students from each BioDATA partner country will be able to participate and present their studies and data activities as dataset publications through GBIF.org and/or as data papers, an emerging and student-friendly publication type. GBIF Norway with the support from the GBIF Secretariat will act as a data publishing facilitator. BioDATA final symposium for partner universities, ForBio, and GBIF. Venue in Oslo (11-12 November 2022). https://www.nhm.uio.no/english/research/projects/biodata/activities/2022-final-seminar.html

• Halbritter Rechsteiner, Aud Helen; Endresen, Dag; Nilsen, Erlend Birkeland; Chipperfield, Joseph; Grainger, Matthew & Telford, Richard James [Show all 8 contributors for this article] (2022). Open, Reproducible, and Transparent Science in Ecology. Show summary

  Manage, produce, use, and reuse data with reproducible workflows. A course at Finse Alpine Research Centre organized by the University of Bergen (UiB) Ecological and Environmental Change Research Group together with Living Norway and GBIF Norway, 14-18 November 2022. 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 increase the credibility of science. Do you want to gain new skills in data management, making your data FAIR, and your workflows reproducible? Do you want training in open-source tools such as GitHub and R that can be used to achieve this? We offer hands-on training on methods and technologies to make research more open, reproducible, and transparent. The course is centered around the life-cycle of data from planning, managing, collecting, curating, analyzing, publishing, storing, sharing, and reusing data. It is aimed at Ph.D. students (will be prioritized) 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. The course will be held at the Finse Alpine Research Centre, from 14 - 18 November 2022. Students will be introduced to open science, data management, data repositories/databases, data standards (e.g. FAIR, CARE), best practice, and reproducible workflows (e.g. data curation, analysis, GitHub, reporting results). Experts will give lectures on these topics and provide hands-on training that will give you opportunities to practice new skills. We will provide examples, but also encourage you to bring your own data and problems to work on.

• Endresen, Dag (2022). Global Biodiversity Information Facility - Free and open access to biodiversity data. Show summary

  The aim of the Living Norway open science lab is to reach out to students and researchers in ecology, conservation science and ecology that share an interest in open, transparent and reproducible science. Sharing and reusing research data will be a particular focus area, but the lab will be a place for discussions about all kinds of aspects of open science practices.

• Endresen, Dag; Tykarski, Piotr & Braun, Paul (2022). GBIF Europe and Central Asia Nodes meeting May 2022 in Luxembourg. Show summary

  The regional GBIF Europe and Central Asia Nodes meeting (ECA2022) in Luxembourg, 23-25 May 2022.

• Mayfield-Meyer, Teresa Jegelewicz; Baskauf, Steven J; Endresen, Dag; Bölling, Christian; Wieczorek, John & Pyle, Richard L. [Show all 7 contributors for this article] (2022). MaterialSample and its Properties. Biodiversity Information Science and Standards (BISS). ISSN 2535-0897. 6. doi: 10.3897/biss.6.91407. Show summary

  The Biodiversity Information Standards (TDWG) Material Sample Task Group*1 kicked off in the third quarter of 2021. The group’s initial focus was to 1) achieve a clear conceptual delineation between the terms MaterialSample, PreservedSpecimen, LivingSpecimen, and FossilSpecimen (the terms used in basisOfRecord in the current DwC-A provided to the Integrated Publishing Toolkit (IPT) for describing physical material) 2) define the conceptual relationship between these terms and the term Organism 3) consider the possible implications of the activities towards the diversification of the Global Biodiversity Information Facility (GBIF) data model*2 and what standards already exist that should inform our work. Based on this conceptual work, the group is now developing a concrete proposal for a clarification of a MaterialSample class with its own properties. Our presentation will provide a brief review of the task group's progress and our thoughts about what comes next.

• Giuffrida, Rita; Dmitry, Schigel; Endresen, Dag; Taubert, Franziska; Ovaskainen, Otso & Chala, Desalegn [Show all 15 contributors for this article] (2022). The BioDT use cases: unique demonstrators to test the biodiversity Digital Twin prototype. Show summary

  The BioDT project aims to develop the biodiversity digital twin prototype to help better predict global biodiversity dynamics and how species interact with their environment and with each other. In order to test the work developed by the BioDT team in the three years of the project, groups of use cases will showcase how BioDT can examine its predictive performance and address biodiversity challenges through scenario simulations, predictions and biomonitoring methods. In order to speed up with the development of the BioDT use cases, the project team has met from 5 to 7 September 2022 in Potsdam, Germany, for an internal technical workshop. The aim of the event was to: * Consolidate the use cases leads and project teams; * Develop the scientific questions for each use case; * Start developing requirements for each use case; * Identify data types and sources to be used; * Prioritise UCs and exact scenarios to be addressed by initial development work; * Define the process of data flow from Research Infrastructures (RIs) to modellers; * Define data format and quality requirements between 1) RIs and 2) RIs and modellers. The workshop was organised by UFZ and welcomed 17 participants from BioDT partners. Following this workshop, and in order to present the use cases developments also to external partners, a free BioDT webinar was organised on 27 September 2022. The event showcased through presentations, interactive sessions with the audience and a Questions & Answers session the main achievements of the use cases and the next steps. During the 1-hour webinar, it was possible for attendees to learn more about the scope, challenges, solutions and benefits brought by the BioDT use cases and how their development can help scientists in predicting future trends in biodiversity. The webinar was organised by Trust-IT in cooperation with the use cases leaders.

• Altenburger, Andreas & Bergersen, Robert (2022). Bivalvia collection (TSZB) The Arctic University Museum of Norway.
• Altenburger, Andreas & Bergersen, Robert (2022). Gastropoda collection (TSZG) The Arctic University Museum of Norway.
• Altenburger, Andreas & Bergersen, Robert (2022). Cnidaria and Ctenophora (TSZR) The Arctic University Museum of Norway.
• Altenburger, Andreas & Bergersen, Robert (2022). Foraminifera and other protozoa (TSZF) The Arctic University Museum of Norway.
• Schuppe, Birte Katarina; Wernström, Joel Vikberg & Altenburger, Andreas (2022). Marine invertebrates registered on the Nansen Legacy JC3 Winter Gaps cruise 19th February - 11th March 2022.
• Altenburger, Andreas (2022). The Global Biodiversity Information Facilty (GBIF), a research infrastructure to facilitate findable, accessible, interoperable and reusable (FAIR) sharing of biodiversity data. Show summary

  Availability of high-quality species occurrence data is a prerequisite for good management decisions. On average, only 20% of research data are available 20 years after a scientific paper has been published. Inaccessibility of data leads to erroneous conclusions in scientific publications and potentially poor management decisions. GBIF is a research infrastructure facilitating FAIR sharing of biodiversity data, coalescing occurrence records from multiple datasets. GBIF Norway has more than 48 million occurrence data points in 1516 datasets provided by 42 countries and 435 data publishers. Norway has a long tradition in marine research and not all marine data is shared FAIR. There is a potential for improvement to facilitate research and management of Norway’s marine area of 933.028 km2 (to the limit of the exclusive economic zone), 6375 km2 of which have some form of protection from fishing.

• Endresen, Dag & Johaadien, Rukaya Sarah (2021). Update on BioDATA - DNA metabarcoding data management. Show summary

  GNM 2021 (Virtual) Group 1 – data mobilization training and guidance on sequence-derived data mobilization, presentation by Dag Terje Filip Endresen, GBIF Node Manager

• Endresen, Dag (2021). Biodiversity informatics for the Norwegian museums at Tøyen in Oslo in March 2021. Show summary

  The Norwegian university museums have started a process to maintain but re-evaluate the collaboration structures. This process includes an evaluation of informatics solutions including digitization solutions, collection management software, and GBIF data streams. https://www.gbif.no/news/2021/biodiversity-informatics-for-the-norwegian-museums.html

• Endresen, Dag Terje Filip (2021). The role of biodiversity informatics in the global biodiversity information facility, GBIF. Show summary

  Role of biodiversity informatics in the Global Biodiversity Informatics Facility (GBIF). Seminar at the Government College University of Lahore in Pakistan 18th of May, 10:00 CEST Oslo, 13.00 PKT Lahore, 08:00 UTC. Pakistan is an affiliated observer in GBIF (since August 2001), and the Government College University of Lahore is registered and endorsed as a GBIF data publisher (since October 2020).

• Belbin, Lee; Kampmeier, Gail; Endresen, Dag & Baskauf, Steve (2021). Guidelines for Review Managers of Proposed TDWG Standards. Show summary

  The guidelines for review managers of proposed standards were originally written in 2009 by Lee Belbin and have been used by review managers of most of the standards that have been ratified since then. They were revised in 2021 based on feedback from former review managers in order to update the recommendations based on changes in technology and practical experience. They describe the best practices for carrying out the expert and public reviews required as part of the TDWG Process, the bylaws that govern how TDWG standards are ratified.

• Endresen, Dag (2021). Råd fra GBIF-Norge til datainfrastrukturutvalget i dialogmøte 2021-11-19. Show summary

  [Råd 1] Norske forskningsdata bør publiseres i henhold til internasjonale data-standarder. Internasjonale data-standarder sikrer interoperabilitet og reelle muligheter for gjenbruk av data. Etablerte data-standarder innenfor et fagområde gir ofte best effekt for realisert gjenbruk, men kan hindre gjenbruk av data i nye og uforutsette tverrfaglige studier og sammenhenger. Norge bør derfor også bidra til tverrfaglig videreutvikling av interoperabilitet på tvers av data-standarder som er i anvendelse innenfor de enkelte fagområder. [Råd 2] Måloppnåelse for økt deling av forskningsdata blir enklere med effektive insentiver. Vi tror at etablering av forskningsdata som siterbart vitenskapelig produkt slik som DORA (sfdora.org, 2012) og Force11 (force11.org, 2011) beskriver gir viktige retningslinjer som datainfrastrukturutvalget bør forsøke å integrere i nye Norske retningslinjer. [Råd 3] Metrikk for å måle gjennomslag og innflytelse (impact) av forskning ("tellekanter") bør utvides til å inkludere metrikk for anerkjennelse av datakilde (data-publikasjon, data-sitering) for både forsker og institusjon. Publisering av forskningsdata bør fortrinnsvis utføres gjennom en profesjonell infrastruktur (slik som GBIF) der opphavsmann og de ulike bidragsytere til produksjon, innsamling, tilretteleggelse, håndtering, og bevaring av data kan registreres. Dataset bør tilordnes stabil digital identitet, gjennom løsninger slik som DOI (digital object identifier). Personer bør knyttes til stabil digital identitet gjennom løsninger slik som ORCID (Open Researcher and Contributor ID, orcid.org). Institusjoner bør knyttes til stabil digital identitet gjennom system løsninger slik som ROR (Research Organization Registry, ror.org). [Råd 4] Etablering av infrastruktur for forskningsdata tar tid og behøver derfor kontinuitet og forutsigbare rammer, mandat, og langsiktig strategisk investering. Effektiv langsiktig investering i felles internasjonale løsninger krever ofte bedre kontinuitet enn det som er mulig innenfor handlingsrommet for basisfinansiering for enkelte forskningsinstitusjoner og universiteter. Samtidig som felles multi-nasjonal investering i fellesløsninger ofte har en betydelig lavere kostnad enn en alternativ mere fragmentert infrastruktur. GBIF Norge (GBIF.no) er den norske deltagernoden i Global Biodiversity Information Facility (GBIF.org). GBIF er en internasjonal organisasjon som arbeider for fri og åpen tilgang til globalt dekkende informasjon om biologisk mangfold. GBIF ble etablert i 2001 etter en beslutning i OECDs Science Forum i 1999. Norge ble medlem av GBIF i 2004 og den norske deltagernoden, GBIF Norge, ble etablert med sekretariat ved Universitet i Oslo Naturhistorisk Museum i nært samarbeid med Artsdatabanken og med finansiering fra Forskningsrådet. GBIF Norges mandat omfatter nasjonal deltagelse i GBIF med internasjonal publisering av norske artsdata i henhold til internasjonale data-standarder som er forvaltet av GBIF.

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