Notice bibliographique
Résumé
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.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,012 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; les deux têtes enseignantes s’accordent sur ce qui est montré ici.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».