Bibliographic record
Abstract
The information provided here represents the EBV workflow templates collected during the EuropaBON online workshop on Essential Biodiversity Variable (EBV) workflows from 22–24 February 2023. The templates were designed to capture comprehensive descriptions about the three workflow components (data collection and sampling, data integration, and modelling) that are typical for generating EBVs. Recognising the potential value of those EBV templates for European biodiversity monitoring, our objective is to share them for enhancing transparency, knowledge exchange and collaboration, and promoting the operationalisation of EBVs across Europe. EuropaBON (https://europabon.org/) is a Horizon 2020 research and innovation action funded by the European Commission that seeks to co-design a European Biodiversity Observation Network. This network aims to bridge the gap between the biodiversity data needs of policy-makers and authorities on the one hand and the existing reporting streams and available data sources on the other hand, considering both present obligations and forthcoming policy needs. Essential Biodiversity Variables (EBVs) are a central concept of EuropaBON as they provide a standardised framework for biodiversity monitoring and reporting. In 2023, EuropaBON had identified 70 EBVs (Junker et al., 2023) that are policy-relevant for the EU, and measurable with available and existing technologies and with a proven track record of feasibility in ongoing initiatives. EBVs require workflows to process the raw data (primary observations) through data integration and modelling into spatially-explicit EBV data products (Kissling et al., 2018; Schmeller et al., 2017). These workflows can be broken down into three main components (data collection and sampling, data integration, and modelling), with additional aspects of data interoperability and IT infrastructure being recognised as crucial for transnational data streams (Kissling & Lumbierres, 2023). To capture information about the EBV workflows, an online workshop was held on 22–24 February 2023 with 520 registered participants from 49 countries, covering a large range of expertise (Lumbierres & Kissling, 2023). Participants contributed information on EBV workflow components and advanced monitoring techniques, discussed initiatives, and identified tools and requirements for implementing 70 proposed EBVs. The information from the workshop participants was collected through pre-defined EBV workflow templates (provided as Google Docs). Templates were organised into rows representing the workflow components (‘Data collection and sampling’, ‘Data integration’, and ‘Modelling’) and columns reflecting the levels of maturity ('Current initiatives', 'Emerging tools and projects' or 'Future needs'). Prior to the workshop, some information on existing workflows was pre-filled based on previous EuropaBON deliverables, namely an assessment of the current biodiversity monitoring gaps in the EU (Santana et al., 2023) and an assessment of current EU monitoring workflows and bottlenecks (Morán-Ordóñez et al., 2023). After the workshop, the EBV workflow templates were processed to ensure the accuracy and relevance of the information. Each listed initiative was verified to be part of an active biodiversity monitoring scheme and pertinent to the specific EBV under consideration, cross-referencing with the initiative’s websites and other data collected by the EuropaBON deliverables (Morán-Ordóñez et al., 2023; Santana et al., 2023). Moreover, we ensured correct alignment of each initiative and listed requirements and needs with the appropriate workflow components and maturity levels. The EBV workflow templates provide insights into the current biodiversity monitoring landscape in Europe and how EBV production could be operationalized at the EU level. They offer detailed information about ongoing initiatives and projects, methodologies, and technologies that can be used to generate EBVs at a continental scale. Nevertheless, it is important to note that they do not encompass an exhaustive list of all ongoing or proposed initiatives of biodiversity monitoring in all member states of the EU. It is suggested to use them as a starting point and baseline for the further development of EBVs in a European context.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.018 | 0.061 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.010 | 0.007 |
| Open science | 0.004 | 0.008 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.082 | 0.084 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".