Despite methodological progress, the extraction, synthesis, and assessment of biodiversity information is often biased and seldom transparent, comprehensive, systematic, nor reproducible. Reasons range from the fact that biodiversity literature is widely distributed and inconsistently structured to difficulties with vocabularies and definitions. Collaborations between biodiversity, social, and computer scientists are needed to achieve progress in literature-based biodiversity knowledge extraction.
Digitization and AI offer ways to enhance access and usability, but major challenges remain.
The Disentis Roadmap, a decadal initiative supported by over 100 scientists and organizations, addresses these by making literature data machine-accessible and actionable. Practical steps include discovering and gathering publications via the Biodiversity Literature Repository and the Biodiversity Heritage Library, converting them for structured reuse, and integrating outputs into infrastructures such as GBIF and Biodiversity PMC.
This 2×90-minute is divided in two parts: 1) Provides an overview of current applications, methods and approaches highlighting the diversity of questions that can be tackled via evidence synthesis. Contributions from searching/reviewing the grey and scientific literature to knowledge synthesis are invited. 2) Presents and critically assesses the Disentis Roadmap’s approach to creating a reusable biodiversity literature corpus, explore pathways to scale it for researchers, policy-makers, and the public, and invite community involvement.
This session is part of the “Biodiversity Evidence” series.
Co-convener: Mark Snethlage, Patrick Ruch, Rainer Krug, Rob Waterhouse
The accelerating expansion of biodiversity knowledge—across peer-reviewed publications, grey literature, policy documents, and project reports—creates increasing challenges in identifying timely, trustworthy, and policy-relevant evidence. Organisations working at the science–policy interface face rising demands to locate, screen, organise, and prepare ever larger bodies of literature while maintaining transparency, reproducibility, and methodological robustness. To address these shared challenges, a full-day, workshop (CON20: Biodiversity Evidence – Foundations of a Community of Practice to Streamline and Innovate Literature Workflows) was held on Sunday, 14 June 2026 here at the World Biodiversity Forum.
This presentation provides an overview of the workshop and the themes, discussions, and needs that emerged throughout the day. In the morning, short talks offered a state-of-the-art snapshot of current tools, techniques, and initiatives, along with case studies illustrating how different communities approach literature identification, screening, and preparation for synthesis. These contributions provided a shared reference point for reflecting on strengths, persistent challenges, and areas where workflows struggle to scale to large and very large bibliographic corpora.
In the afternoon, breakout groups explored the requirements of diverse user communities, ranging from science–policy bodies and assessment teams to researchers, practitioners, and independent projects. Discussions focused on what is currently missing, what is needed next, and where improved guidance, interoperability, automation, or standards could help streamline workflows across contexts. Rather than prescribing fixed solutions, the workshop aimed to articulate a clearer picture of the landscape of needs and opportunities.
A major component of the workshop was to outline the foundations of a new Community of Practice for Literature Workflows (CoPLit). The presentation will summarise how participants envisioned the role of CoPLit, the areas where collective action may be most beneficial, and the types of collaboration and coordination that could strengthen future development.
The session concludes by highlighting how researchers, practitioners, and institutions can engage with CoPLit and help build a coordinated, open, and practical approach to making biodiversity literature more accessible, relevant, and ready for evidence-based research, practice, and policy.
How to cite: Urbach, D., Krug, R., Agosti, D., Camperio, G., Ruch, P., and Zemp, D. C.: Literature workflows from search to analysis – Workshop report, World Biodiversity Forum 2026, Davos, Switzerland, 14–19 Jun 2026, WBF2026-634, https://doi.org/10.5194/wbf2026-634, 2026.
Ongoing changes in mountain biodiversity have important consequences for the future provision of ecosystem services across scales and for human livelihoods and wellbeing worldwide, calling for effective action. However, the formulation of environmental policies and measures that address the challenges of sustainable management and conservation of mountain ecosystems relies on knowledge that is ‘trapped’ inside a vast and rapidly increasing corpus of unstructured text - the scientific literature, which to date is not accessible to machine-based approaches. Our objective is to develop MoBiKo, an open access global mountain biodiversity knowledge graph built from the entities and relations extracted from the corpus of mountain biodiversity literature. This knowledge graph will ‘liberate’ and structure available knowledge pertaining to the state of, trends in, and drivers of mountain biodiversity. By following principles of findability, accessibility, interoperability, and reusability, we enable broad usage, its expansion with new entities of interest, and its application for varied downstream tasks. Here, we present ongoing work towards achieving a first version of MoBiKo with (i) an approach to improve named-entity recognition based on a hybrid framework that combines structured resources with large language models, and (ii) a preliminary attempt towards relationship extraction using models that are pre-trained on existing datasets and fine-tuned on synthetically generated mountain biodiversity triplets. In addition, we present the domain-specific gazetteers used to address widespread issues of heterogeneous terminologies and enable targeted inference and efficient pre-filtering of relevant sentences, and we provide examples of the contribution of such gazetteers to linked open data and to the systematic mapping of mountain biodiversity literature. Our preliminary results highlight the potential of hybrid and iterative natural language processing pipelines to bridge rule-based and generative methods. By developing this structured, curated, and digitally accessible knowledge base, we aim to support scientific research and inform policy as well as conservation efforts. We further contribute to “opening up what is known about biodiversity” and thereby support the Disentis Roadmap 2024 vision to fully “leverage the power of biodiversity knowledge from research publications within an open science framework”.
How to cite: Kantiskaia, A., Snethlage, M., El-Bachir, Y., Remlinger, C., Urbach, D., and Salamanca, L.: Towards a mountain biodiversity knowledge graph, World Biodiversity Forum 2026, Davos, Switzerland, 14–19 Jun 2026, WBF2026-111, https://doi.org/10.5194/wbf2026-111, 2026.
Combining text mining of species taxonomy and traits with biodiversity genomics is a transformative approach to enhance how data are used for species and habitat protection. A recently started Swiss National Science Foundation project aims at tackling this problem in an interdisciplinary setting. The project will deliver an open-access knowledge graph and modelling portal that links text-mined traits, genomic indicators, and environmental layers for transparent and reusable analyses. The main goals are to improve (1) spatiotemporal species distribution mapping and (2) taxonomic richness modelling by integrating organismal traits extracted from literature with genomic data, supported by benchmarking of these integrated models against occurrence-only baselines.
Although species distribution modelling increasingly incorporates traits and genomic information, progress is limited by difficulties in accessing and standardising these data. We address this gap through AI-assisted literature digitisation, named-entity recognition and normalisation, relationship extraction, and semi-automated expert curation that convert heterogeneous sources into machine-actionable formats. Uncertainties in taxonomic richness and the prevalence of undescribed “dark taxa” will be explicitly propagated into model predictions using taxonomic concept reconciliation and uncertainty quantification.
To overcome data scarcity and heterogeneity, we will mobilise “grey literature” and public genomic repositories to harmonise traits and genetic information for modelling at scale. Achieving this requires advances in biodiversity-focused text mining and the integration of extracted data with genomic analyses for species and population differentiation. The geographic and taxonomic scope is designed around key research questions and centres on birds, bats, and fish in Switzerland, and butterflies, bumblebees, and amphipods in Europe. These groups represent a gradient of taxonomic resolution (well-defined species, cryptic species, and dark taxa), varying volumes of existing knowledge that can be mined from the literature, differing baselines for trait-collection efforts, and increasing genomic data availability.
The liberation of trapped information about species life histories, interactions, habitat preferences, etc. from the vast resources of published literature is a challenge that must be tackled in a systematic manner to advance biodiversity science.
How to cite: Waterhouse, R., Agosti, D., and Rinaldi, F.: Literature mining of species traits integrated with genomics to transform biodiversity modelling, World Biodiversity Forum 2026, Davos, Switzerland, 14–19 Jun 2026, WBF2026-395, https://doi.org/10.5194/wbf2026-395, 2026.
Community-led initiatives that have focused on providing standardized protocols and ready-to-use data are transforming our understanding of terrestrial ecosystems, for example, by allowing the inclusion of above- and below-ground plant functional traits. However, as plant diversity comprises more than 300,000 species globally, continuous data collection, mobilization, and curation are necessary to address gaps in species’ traits and their ecological functions (Raunkiaer’s shortfall) and in geographical distribution (Wallacean shortfall). For instance, root traits capture key dimensions of plant responses to environmental conditions and their effects on ecosystem processes. Recent increases in publicly available data through initiatives such as the Fine Root Trait Database (FRED)1 and the Global Root Trait (GRooT)2 database have facilitated integration of root traits with aboveground traits and ecosystem processes across local to global scales. Focused initiatives such as the Tropical Root Initiative (TropiRoot)3 have targeted the mobilization of root-trait data from some of the most diverse ecosystems on Earth. These data are being leveraged to understand natural and anthropogenic factors shaping plant (functional) diversity and better represent tropical ecosystems in global analyses. While these initiatives have contributed significantly to putting roots on the map, they cover fewer than 5% of the world's plant species. Further, they currently depend on manual data extraction. Thus, we aim to have an open discussion of how new advances in data mobilization could catalyze the integration of other facets of biodiversity, such as functional diversity and, particularly, the mobilization of key root traits.
These community initiatives are made possible by the engagement and support of multiple contributors.
1Iversen CM, McCormack ML, Baer JK, Powell AS, et al., 2021. Fine-Root Ecology Database (FRED): A Global Collection of Root Trait Data with Coincident Site, Vegetation, Edaphic, and Climatic Data. Oak Ridge National Laboratory, TES SFA, U.S. Department of Energy, Oak Ridge, Tennessee, U.S.A. https://doi.org/10.25581/ornlsfa.014/1459186.
2Guerrero-Ramirez N, Mommer L, Freschet GT, Iversen CM, McCormack ML, Kattge J, et al., 2021. Global Root Traits (GRooT) Database. Global Ecology and Biogeography 30(1):25-37 https://doi.org/10.1111/geb.13179
3Cordeiro A, Cusack DF, Guerrero-Ramírez N, Norby RJ, et al., 2025. TropiRoot 1.0: Database of tropical root characteristics across environments. Ecology 106(5):e-70074 https://doi.org/10.1002/ecy.70074
How to cite: Guerrero-Ramírez, N., McCormack, L., and Longhi Cordeiro, A.: Leveraging scientific literature to integrate root functional traits in our understanding of terrestrial ecosystems, World Biodiversity Forum 2026, Davos, Switzerland, 14–19 Jun 2026, WBF2026-615, https://doi.org/10.5194/wbf2026-615, 2026.
The published literature on biodiversity spans centuries, from accounts of expeditions to remote parts of the world, spectacular illustrations of new species (labelled with a Latin name), through to modern studies employing the latest technologies to understand how many species are on the planet, where those species live, and what they are doing.
Much of this literature now resides in the open access Biodiversity Heritage Library (BHL), perhaps the largest corpus of biodiversity literature available. BHL comprises over 63 million pages, spread across 200,000 books and journals in multiple languages. BHL content has been cited over 400,000 times by researchers.
Preliminary text mining suggests that BHL contains the original descriptions for some 400,000 species, with additional information on up to 3 million species. But this only scratches the surface of BHL’s potential. At the most basic level, content in BHL needs to be made discoverable and citable by researchers. ML tools are speeding up the discovery of these articles, enabling scholars to find them more easily. Inspired by the success of Pensoft and Plazi in making recent biodiversity knowledge findable, a second goal is to convert BHL content from static scans of pages into structured publications, so that centuries of knowledge become as accessible as if it were published today.
BHL is well known for the glorious colour plates of plants and animals, many created by artists in the 19th and 20th centuries. But BHL is also full of detailed line drawings of species, maps of their distribution, photos of their habitats, and sonograms of their calls. These images are buried within the corpus, but new Large Language Models (LLMs) can be used to identify and extract them, enhancing efforts to build tools to automatically identify species from images, as well as documenting how distributions and habitats have changed over time.
The talk will present examples of using ML to extract images and structured data from BHL at scale, and outline the future role BHL can play in making fundamental biodiversity knowledge vastly more discoverable and accessible.
How to cite: Page, R.: Unlocking Centuries of Biodiversity Knowledge: Machine Learning and the Biodiversity Heritage Library, World Biodiversity Forum 2026, Davos, Switzerland, 14–19 Jun 2026, WBF2026-822, https://doi.org/10.5194/wbf2026-822, 2026.
The rapidly growing volume of scientific publications, grey literature, policy documents, research datasets, and materials reflecting Indigenous and Local Knowledge (ILK) and diverse worldviews has outpaced the capacity of expert teams to screen, assess, and synthesise the global evidence base. This challenge is particularly acute for IPBES assessments, which depend on comprehensive, transparent, and globally representative evidence syntheses undertaken by large international, multidisciplinary author teams. As the available literature and knowledge sources expand, so does the risk of overlooking emerging developments, underrepresenting regional, cultural, or knowledge-system perspectives, and placing increasing demands on already stretched experts.
Artificial intelligence (AI)—especially large language models (LLMs)—is often presented as a powerful response to these pressures. AI tools promise to help analyse, filter, and structure vast multilingual bodies of evidence, potentially making it feasible to work with corpora comprising several million references. They appear to offer opportunities for topic clustering, literature triage, metadata enrichment, semantic search, summarisation, and support for drafting specific components of assessments. However, it remains uncertain to what extent these promises can be realised reliably and responsibly in science–policy contexts. Many capabilities are evolving rapidly, but so too are concerns about accuracy, reproducibility, opacity, and the risk of over-reliance on automated outputs.
This talk outlines the current IPBES principles - but also best practices from other communities, e.g., DOME or ARR recommendations - and guidelines governing the use of AI in assessment processes. It highlights the central requirements of transparency, traceability, expert oversight, and methodological rigour when integrating AI tools into evidence-synthesis workflows. Particular attention is given to issues such as confidentiality, risks of bias and hallucination, validation of automated outputs, and the need for reproducible documentation that allows independent verification.
Rather than framing AI as either a universal solution or an emerging threat, the presentation provides a subjective and pragmatic perspective on where AI tools may offer genuine value—and where their limitations warrant caution or exclusion. The aim is to help situate AI within a balanced, responsible evidence-synthesis framework that strengthens, rather than replaces, the scientific expertise at the core of IPBES assessments.
How to cite: Krug, R. and Ruch, P.: The Role of AI in IPBES Assessments and Biodiversity Literature Analysis - hype or Salvation?, World Biodiversity Forum 2026, Davos, Switzerland, 14–19 Jun 2026, WBF2026-968, https://doi.org/10.5194/wbf2026-968, 2026.
The extraction and liberation of biodiversity knowledge from scientific literature increasingly depends on both automated and community-driven workflows. The Wikimedia ecosystem comprised of Wikipedia, Wikidata, Wikimedia Commons, Wikisource, Wikispecies and related projects has become a large, open, multilingual environment consistently ranked amongst the world’s top 10 websites. It reflects many of the challenges and opportunities outlined in the Disentis Roadmap. This contribution presents Wikimedia projects as complementary infrastructures for literature-based biodiversity evidence synthesis and examines how scientific publications enter and are transformed within this ecosystem.
Biodiversity literature reaches Wikimedia through several pathways, including (1) papers cited from encyclopedic entries related to biodiversity and beyond, (2) suitably licensed digital publications or digitized out-of-copyright publications hosted in Wikisource, (3) images and other media extracted from the literature and deposited in Wikimedia Commons, (4) structured bibliographic, taxonomic and methodological metadata represented in Wikidata through both automated imports (e.g., WikiCite workflows) and community editing, and (5) taxonomic concepts curated in Wikispecies. Entities named in the literature can further propagate across Wikimedia projects, creating a rich network of linked context.
We examine how these distributed contributions together form a community-maintained pipeline that captures, structures, and redistributes biodiversity knowledge from the scientific literature to the large, diverse, global and multilingual audience of Wikimedia projects. We outline how taxonomic groups, geographic regions, habitat types and publication types are represented across Wikimedia platforms, how media extraction compares to the volume of available literature, how community editing patterns introduce or mitigate various types of biases, and how these facets change over time. We also discuss Wikidata’s increasing integration with research biodiversity infrastructures like BHL, Bionomia or GBIF, and we explore the strengths and limitations of query-based evidence synthesis using Wikidata-related tools like Scholia.
By situating Wikimedia workflows within the broader goals of the Disentis Roadmap, we highlight how community curation, open licensing, and machine-readable knowledge graphs can complement large-scale digitization and text-mining pipelines. Finally, we outline pathways for integrating Wikimedia-derived biodiversity information further with infrastructures such as GBIF and Biodiversity PMC, thereby enhancing the accessibility, reusability, and interoperability of literature-based biodiversity evidence.
How to cite: Mietchen, D. and Dearborn, J.: Wikimedia as a Platform for Evidence Synthesis: Quantifying Bias and Literature Coverage in Crowd-Sourced Knowledge Graphs, World Biodiversity Forum 2026, Davos, Switzerland, 14–19 Jun 2026, WBF2026-845, https://doi.org/10.5194/wbf2026-845, 2026.
The transformation of biodiversity knowledge into policy-relevant evidence depends not only on what we know, but on how data are shared, curated, and made accessible across scientific and institutional boundaries. As the science-policy interface (SPI) evolves to support decision-making under complex institutional frameworks such as the EU Biodiversity Strategy for 2030 and the Global Biodiversity Framework, supported by the evidence provided by IPBES assessments. Within this context, the importance of establishing efficient mechanisms for biodiversity policy relies strongly on open biodiversity science and data. The principles of FAIR data - Findable, Accessible, Interoperable, and Reusable - have become essential to building trust, transparency, and usability of scientific knowledge in the field of biodiversity.
This session will explore the role of FAIR biodiversity data infrastructures and open science practices in reinforcing the credibility, legitimacy, and salience of the evidence used in policymaking. It will examine how open-access academic publishing and initiatives for making biodiversity data FAIR advance the standards and tools that enable scientists, policymakers, and practitioners to interact within shared knowledge systems.
Through practical examples stemming from various initiatives, including several EU-funded projects (e.g. BioAgora, SELINA, CO-OP4CBD or RESPIN), the session will provide a focus on the following topics:
- how the combination of FAIR data principles and open science approaches can enhance knowledge synthesis and policy relevance,
- how interoperable datasets facilitate cross-sectoral policy integration (e.g., linking biodiversity, climate, and land-use policies), and
- how FAIR-based infrastructures support long-term sustainability of the SPI.
Beyond technical solutions, discussions will focus on the institutional and social dimensions of FAIR science - governance, incentives, and collaboration models - that determine whether data are actually used to inform policy. This presentation aims to identify practical pathways for turning FAIR data into FAIR policy, supporting the co-creation of evidence-based actions for nature.
Keywords:
FAIR data, biodiversity informatics, science-policy interface, open science, data governance, evidence-based policymaking, interoperability
How to cite: Barov, B., Mietchen, D., Korcheva, A., Yovcheva, N., Popova, G., Metodiev, T., Bozakov, P., and Penev, L.: From FAIR Data to FAIR Policy: Strengthening the Biodiversity Science-Policy Interface through Open Science, World Biodiversity Forum 2026, Davos, Switzerland, 14–19 Jun 2026, WBF2026-587, https://doi.org/10.5194/wbf2026-587, 2026.
Natural History Institutions (NHIs), such as research institutions, herbaria, botanical gardens, and museums, have traditionally and continuously contributed to the understanding of the natural world and to the dissemination of this knowledge. Their core mission can be divided into three main objectives: (1) to establish and maintain biological collections (carried out by herbaria, zoological archives, etc.); (2) to conduct scientific research associated with the collections; and (3) to disseminate scientific knowledge within the scientific community and to the general public.
To assess their impact, national research institutes traditionally rely on indicators based on their researchers' publications and the number of times these have been cited. However, these indicators are outdated. Since the shift to open access and the global consensus in favor of improving the research evaluation process beyond the impact factor of journals, most institutions have signed the San Francisco Declaration on Research Assessment (DORA).
Over the past decade, academic publishing in taxonomy, based on material preserved in natural history collections, has undergone many significant transformations to ensure that the information contained in publications is findable, accessible, interoperable, and reusable (FAIR). The adoption of semantic markup and the assignment of persistent identifiers to content allow comprehensive citations of the article, including elements therein, such as images, taxonomic treatments, and material citations.
The data provided allow more in-depth analyses and visualization of the contribution of collections, authors, or specimens to taxonomic output and third parties, such as the Global Biodiversity Information Facility, for reuse of the data or building the catalogue of life.
In this presentation, the authors will showcase dashboards and GBIF-hosted portals that allow visualization of the data provided by publications, from names (authors and their affiliations, collectors, taxon names, etc.) as a reference system, to collection locations (where the specimen was collected, where it is deposited, etc.), and collection tracking (which group is covered, what are the gap in the collection…). In a second part, the presentation will explore how the data can be used to create more relevant indicators to measure scientific impact, while enabling NHIs to set up a collective strategy for research assessment.
How to cite: Bénichou, L., Le Coquet, C., Agosti, D., Giora, J., and Wingert, J.: The value of data imprisoned in biodiversity literature seen through data portals and dashboards, World Biodiversity Forum 2026, Davos, Switzerland, 14–19 Jun 2026, WBF2026-711, https://doi.org/10.5194/wbf2026-711, 2026.
A vast share of biodiversity knowledge remains inaccessible, embedded in traditional literature and fragmented electronic resources. This limits scientific progress, constrains evidence-based policy, and hinders full use of rapidly expanding digitised data from natural history collections, citizen science, monitoring programmes including eDNA, and environmental impact assessments. Although biodiversity information is inherently well-structured and suitable for training emerging AI systems, current bottlenecks hinder its integration into Large Language Models and other automated tools. Overcoming these barriers is both urgent and transformative.
The Disentis Roadmap—developed at a 2024 symposium in Disentis, Switzerland—provides a decadal strategy for liberating biodiversity knowledge from publications. Building on the 2014 Bouchout Declaration, the Roadmap reflects coordinated contributions from publishers, Plazi, the Biodiversity Literature Repository at Zenodo, TreatmentBank, GBIF, ChecklistBank, and Biodiversity PubMedCentral (SiBILS). Automated workflows have already demonstrated the feasibility of large-scale data mobilisation, converting 198 journals and releasing FAIR data from over 95,000 publications, including 760,000 taxonomic treatments, 630,000 figures, and 1.7 million material citations. Complementary efforts by the Biodiversity Heritage Library, Taxodros, and research groups further showcase the value of liberated literature for IPBES assessments, biotic-interaction mining, and global biodiversity inventories.
As of November 2025, the Roadmap has been endorsed by 107 signatories who commit to ambitious objectives: universal enforcement of FAIR data standards by major funders and publishers; fully machine-actionable biodiversity publications with non-copyrightable components deposited openly; AI-readiness of all biodiversity knowledge through well-curated, semantically structured data; and dedicated funding to sustain the infrastructures enabling these goals.
At the centre of the Roadmap is the concept of a Libroscope: a globally deployed workflow that enables seamless discovery and reuse of biodiversity knowledge currently trapped in text. Priority actions include developing empirical use-cases, defining standards for machine-actionable publications, linking literature to specimen infrastructures such as DiSSCo and iDigBio, building efficient and legally robust workflows, and establishing a global training programme to maximise the reusability of biodiversity research.
The presentation will summarise progress towards the Disentis Roadmap objectives, and explain how the community can actively participate in shaping its implementation.
How to cite: Agosti, D., Hirsch, T., and Bénichou, L.: The Disentis Roadmap: a decadal roadmap for liberating global biodiversity knowledge from scientific literature, World Biodiversity Forum 2026, Davos, Switzerland, 14–19 Jun 2026, WBF2026-678, https://doi.org/10.5194/wbf2026-678, 2026.
In the digital age, taxonomic information can be systematically extracted from scholarly publications and transformed into FAIR data—findable, accessible, interoperable, and reusable. Once liberated, these data are deposited in multiple online repositories covering different dimensions of biodiversity knowledge. TreatmentBank (TB), a service provided by Plazi, supports this process by extracting taxonomic treatments from the literature and converting, enriching, linking, storing, and disseminating them as FAIR data.
The information liberated by Plazi feeds the Biodiversity Literature Repository (BLR), a community within Zenodo that enables the creation of FAIR data through the use of custom metadata, and mints persistent identifiers for datasets. It also contributes structured articles as treatment datasets, and geographic occurrence data to the Global Biodiversity Information Facility (GBIF), and provides machine-actionable versions of publications to Biodiversity PMC. To date, Plazi has processed 124 320 papers, resulting in the liberation of 1 172 582 taxonomic treatments. A feedback mechanism between GBIF and Plazi allows the curation of data, or refinement of the data for additional reuses. Data and data transfer standards used in the biodiversity community are applied to guarantee a wide as possible reuse of the data.
Researchers, collaborators, and the broader scientific community are invited to join Plazi’s mission to support persistent, openly accessible digital taxonomic literature by exploring its search tools and reusing its openly available data. Through Plazi’s databases, users can access extensive information contained in taxonomic treatments, including names, descriptions, distributions, material citations, synonymic lists, images, tables, and bibliographic references. To cultivate a vibrant community of publication converters, Plazi provides online training courses, a certification programme, on-site workshops, and mentoring for ongoing projects.
The extraction workflow consists of three steps: (1) locating specific information within a publication, (2) highlighting and analysing it, and (3) making the resulting structured data available in other repositories or formats. Using Plazi’s data, users can assess their own contributions to biodiversity knowledge or generate dashboards focused on individual researchers, journals, institutions, or taxonomic groups processed by Plazi and its collaborators.
How to cite: Giora, J., Agosti, D., Simoes, F., and Castro, J.: Engaging communities to turn publications into FAIR, open biodiversity data, World Biodiversity Forum 2026, Davos, Switzerland, 14–19 Jun 2026, WBF2026-694, https://doi.org/10.5194/wbf2026-694, 2026.
The volume of scientific literature is growing at an unprecedented rate, making it increasingly difficult to remain up to date. Traditional bibliographic catalogues such as Web of Science and Scopus, and open alternatives like OpenAlex or Google Scholar, primarily allow searches based on bibliographic metadata and abstracts. This often results in large corpora containing many irrelevant articles or missing crucial works.
Biodiversity PMC, supported by the SIB Literature Services and building on the work of Plazi and also continuously amended with full-text articles from Pensoft’s and and MNHN journals, offers a powerful one-stop search engine for researchers in biodiversity. By enriching bibliographic records with semantic and topic-related metadata, it enables more precise and comprehensive retrieval of biodiversity-related literature.
In this presentation, participants will be introduced to the capabilities of Biodiversity PMC and its advantages over traditional catalogues. They will explore how to conduct targeted searches via the web interface and see how the APIs can be used for programmatic workflows, with demonstrations with Postman. Through guided examples and real-world case studies, the session aims to raise awareness of this resource, showcase the benefits of semantic metadata, and provide participants with practical skills for integrating Biodiversity PMC into their research practice.
The different collections available wihin BiodiversityPMC/SIBilS will be introduced with their specificities (e.g., highly structured semantically riched JATS XML and BioC vs. PDF files in the Biodiversity Literature Repository, hosted by Zenodo). We will also report on the evaluations performed with the BiodiversityPMC/SIBilS search engine and how it can support the search of supplementary data files, including OCR-ized images, normalized tables (e.g., XLS, CSV) and other file types.
By the end of the presentation, attendees will be able to identify when Biodiversity PMC is the most appropriate tool for their needs, confidently perform searches through its web platform, and understand how to access its data programmatically.
How to cite: Pasche, E., Gobeill, J., Penev, L., Agosti, D., Bénichou, L., Flament, A., Michel, P.-A., Liyanapathirana, J., and Ruch, P.: How Biodiversity PMC can support literature search for biodiversity research ?, World Biodiversity Forum 2026, Davos, Switzerland, 14–19 Jun 2026, WBF2026-511, https://doi.org/10.5194/wbf2026-511, 2026.
Zenodo, hosted at CERN, is a general-purpose research repository designed to preserve and disseminate the long tail of research across all disciplines. While Zenodo has a long tradition of enabling FAIR (Findable, Accessible, Interoperable, Reusable) research outputs, domain-specific communities—such as biodiversity science—require richer metadata, structured deposition workflows, and support for highly interlinked digital objects.
TreatmentBank, Plazi’s taxonomic literature processing pipeline exemplifies this need by converting biodiversity publications into machine-actionable outputs—including over one Million taxonomic treatments, figures, and digital specimens from 103,000 converted publications—published in the Biodiversity Literature Repository (BLR) community on Zenodo. Through Zenodo’s deposition policy and community management model, these deposits are systematically organized and transparently linked to downstream infrastructures such as GBIF. Each deposit receives extensive metadata, a DataCite DOI, licence information, and both human- and machine-readable representations. Visual materials are further enhanced through the IIIF viewer, enabling deep zoom, annotation display, and interoperability with external biodiversity platforms.
To support these sophisticated domain workflows, Zenodo introduced custom metadata, allowing communities like Plazi, the Berlin Museum für Naturkunde Dark Taxon project, and the Bat Literature Project to embed vocabulary-based semantic annotations (e.g., Darwin Core, Audubon Core) directly into deposits. This ensures accurate representation of interlinked objects and long-term FAIR compliance, even for granular items such as individual treatments, physical objects, or figures.
All components—including deposition, metadata enhancement, and cross-platform linking—are powered by REST APIs and are exposed as open metadata datasets, enabling automated workflows and self-sustaining community ecosystems. The BiCIKL project demonstrates how such an infrastructure can serve as a modular building block for an integrated biodiversity knowledge graph. The Biodiversity PMC is an example of how BLR can be used as a launch pad for downstream usage in research of conservation projects or for detailed annotations.
Using in an exemplary way Zenodo’s Biodiversity Literature Repository community, this poster explains the concepts underpinning the Zenodo repository, governance and community management, Zenodo’s community-driven deposition model, the role of custom metadata, and IIIF support to produce very rich FAIR, interlinked, and interoperable biodiversity data.
How to cite: Ioannidis, A., Sautter, G., and Agosti, D.: Biodiversity Literature Repository: a repository and gateway to data in publications, World Biodiversity Forum 2026, Davos, Switzerland, 14–19 Jun 2026, WBF2026-718, https://doi.org/10.5194/wbf2026-718, 2026.
Regional scientific journals are invaluable resources for dissemination of research findings and local knowledge about our world. Maintaining even long-established journals has become increasingly difficult. This article presents Carinthia Nature Tech, published by the Natural Science Association for Carinthia (Naturwissenschaftlicher Verein für Kärnten), as an example of a successful adaptation of such a journal.
Founded in 1811, the journal series Carinthia is among the oldest published scientific collections of the German-speaking world. Some eight decades following establishment of Carinthia, and concomitant with a change of publisher, the journal was rebranded as Carinthia II, which to this day features two parts published exclusively in German. Traditionally, Carinthia II Part 1 serves the popular science readership, while Carinthia II Part 2 features peer reviewed scientific works from the province of Carinthia, Austria and the surrounding regions. Changing cost structures, evolving requirements for scholarly publishing, and the desire to reach new readerships has now prompted further strategic realignment. Since 2024, Carinthia II features an additional, thematically focused series, Carinthia II Part 3, Carinthia Nature Tech. This open access scientific journal is being managed in accordance with the framework of Plan S as supported by the cOAlition S initiative of the European Science Foundation. The periodical is published online twice per year in English, with peer-reviewed sections featuring research findings and non-peer-reviewed sections featuring project summaries and book reviews. The journal focuses on application of new technologies for recording and monitoring biodiversity (so-called “BiDiTecs”) in the Alps-Adriatic region of Europe, combining region-specific knowledge with state-of-the-art methods.
The Natural Science Association for Carinthia publishes Carinthia Nature Tech in cooperation with Carinthia University of Applied Sciences and its Interdisciplinary Centre for Ecosystem Services and Biodiversity (ICEB). Contributions to the journal encompass environmental and biodiversity assessment using remote sensing, geoinformatics, robotics, sensor technologies, and molecular biological methods, as well as data science, information and communication technologies, and artificial intelligence. An editorial management system is currently being established, and the journal aims to be indexed in key citation databases in the medium term, promoting enhanced visibility and impact.
How to cite: Dalton, D., Jungmeier, M., and Schmalzl, L.: Realigning a Traditional Journal – The Story of Carinthia Nature Tech, World Biodiversity Forum 2026, Davos, Switzerland, 14–19 Jun 2026, WBF2026-644, https://doi.org/10.5194/wbf2026-644, 2026.
Islands contribute disproportionately to global biodiversity, harboring exceptional levels of endemic species. Simultaneously, they are highly vulnerable to anthropogenic pressures, with the magnitude and speed of human impacts making islands epicenters of species extinctions and species invasions. Our knowledge of changes in island biodiversity is scattered across journals, repositories, and data formats. Moreover, knowledge about island biodiversity is often diluted in global, continental, or national syntheses, limiting its inclusion in policy and decision-making. Mobilizing and integrating this literature is essential, as islands may provide early warning systems for ecological tipping points worldwide.
Here, we present a user-oriented workflow for finding, screening, and structuring biodiversity literature relevant to island ecosystem monitoring. The workflow integrates established evidence-synthesis practices following Collaboration for Environmental Evidence guidelines with AI-enabled tools to improve the scalability, efficiency, and reproducibility of the review process.
A comprehensive search across Web of Science, Scopus, and OpenAlex yielded over 14,000 publications. Given the number of publications, a transformer-based binary classification model was fine-tuned using a 10% subset (1,500 articles) to rank publications by their relevance. The subset is the result of a restricted search string applied at the title and abstract level on OpenAlex. The subset was manually screened by island biodiversity experts relying on an ontology describing key concepts related to islands and Essential Biodiversity Variables (EBVs), ensuring consistency throughout the screening and coding process. Title and abstract screening retained approximately 1,100 records, and full-text assessment resulted in a final list of 700 publications, from which structured information, including island location, geological type, EBV categories covered, and protocols, was extracted.
All selected publications have been transformed into machine-readable formats and deposited in Biodiversity PMC via the Biodiversity Literature Repository (BLR) community on Zenodo, enabling systematic annotation and data extraction to improve transparency and replicability. We present insights into global patterns and gaps in island biodiversity monitoring, and discuss how to make island literature FAIR (Findable, Accessible, Interoperable, and Reusable), and machine-actionable, can contribute to the Disentis Roadmap vision of liberating biodiversity knowledge from publications, thereby providing evidence for conservation planning and policy on islands and beyond.
How to cite: Camperio, G., Zemp, C., Downes, J., Wildpret, W., Borges, P. A. V., Agosti, D., Ah-Peng, C., Catogni, L., de Nascimento, L., Emerson, B. C., Fernández-Palacios, J. M., Gabriel, R., Lenzner, B., Mologni, F., Patiño, J., Ruck, P., Simões, F. L., Suter, S., Kreft, H., and Guerrero-Ramírez, N. and the BioMonI (Biodiversity Monitoring of Island Ecosystems) and BioMoQA (Biodiversity Monitoring via Question Answering): Synthesizing evidence on island biodiversity monitoring: from scattered literature to structured knowledge, World Biodiversity Forum 2026, Davos, Switzerland, 14–19 Jun 2026, WBF2026-686, https://doi.org/10.5194/wbf2026-686, 2026.
