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Creating the vision of rapid, repeatable, reactive data workflows for policy on biodiversity

Unfortunately the abstract isn't available in English yet.
Abstract Effective biodiversity management and policymaking requires timely access to accurate and reliable scientific data on biodiversity status, trends and threats. However, current biodiversity monitoring processes are often time-consuming, complex and irreproducible. Moreover, the quality and types of biodiversity data are diverse, which challenges their integration and impedes effective monitoring. A major step to overcome such challenges would be the availability of standardized species occurrence data. However, challenges arise in aggregating and integrating these heterogeneous data with environmental and landscape data. By creating standardized biodiversity data cubes and automated workflows for post-processing, we envision that (1) information from complex datasets will be available in a known format to efficiently communicate biodiversity variables to policymakers; (2) the adoption of repeatable Open Data workflows will make biodiversity data more accessible, efficient and cost-effective; and (3) cloud computing will make it easier to analyse large datasets, benefit from a broader range of models, share resources and work together on biodiversity projects. This revolution in biodiversity monitoring will rely on community collaboration. By bridging the gap between policymakers' needs, bioinformation specialists' skills and data collectors' motivations, biodiversity monitoring can become a more inclusive and community-driven effort. As such, we advocate for the development of tools and workflows in close consultation with stakeholders to enhance the impact and use of biodiversity information. Practical implication. The proposed approach faces challenges in maintaining software, data standards and addressing biodiversity data complexity. However, leveraging existing infrastructures like GBIF and Copernicus, and building on the knowledge from GEO and GEO BON offers a feasible path.

Details

Number of pages 9
Volume 6
Magazine issue 3
Pages (to-from) e70113
Type A1: Web of Science-article
Category Research
Magazine Ecological Solutions and Evidence
Issns 2688-8319
Publisher John Wiley & Sons, Ltd
Language English
Bibtex

@misc{730a966a-90df-4782-92b0-04633f15a133,
title = "Creating the vision of rapid, repeatable, reactive data workflows for policy on biodiversity",
abstract = "Abstract Effective biodiversity management and policymaking requires timely access to accurate and reliable scientific data on biodiversity status, trends and threats. However, current biodiversity monitoring processes are often time-consuming, complex and irreproducible. Moreover, the quality and types of biodiversity data are diverse, which challenges their integration and impedes effective monitoring. A major step to overcome such challenges would be the availability of standardized species occurrence data. However, challenges arise in aggregating and integrating these heterogeneous data with environmental and landscape data. By creating standardized biodiversity data cubes and automated workflows for post-processing, we envision that (1) information from complex datasets will be available in a known format to efficiently communicate biodiversity variables to policymakers; (2) the adoption of repeatable Open Data workflows will make biodiversity data more accessible, efficient and cost-effective; and (3) cloud computing will make it easier to analyse large datasets, benefit from a broader range of models, share resources and work together on biodiversity projects. This revolution in biodiversity monitoring will rely on community collaboration. By bridging the gap between policymakers' needs, bioinformation specialists' skills and data collectors' motivations, biodiversity monitoring can become a more inclusive and community-driven effort. As such, we advocate for the development of tools and workflows in close consultation with stakeholders to enhance the impact and use of biodiversity information. Practical implication. The proposed approach faces challenges in maintaining software, data standards and addressing biodiversity data complexity. However, leveraging existing infrastructures like GBIF and Copernicus, and building on the knowledge from GEO and GEO BON offers a feasible path.",
author = "Quentin Groom and Laura Abraham and Tim Adriaens and Lissa Breugelmans and David A Clarke and Michele Di Musciano and Shawn Dove and Lina M. Estupinan-Suarez and Katelyn T Faulkner and Miguel Fernandez and Louise A Hendrickx and Cang Hui and Alexis Joly and Sabrina Kumschick and Ward Langeraert and Matilde Martini and Joe Miller and Damiano Oldoni and Henrique M. Pereira and Cristina Preda and Tim Robertson and Duccio Rocchini and Andrew Rodrigues and Maxime Ryckewaert and Hanno Seebens and Yanina V. Sica and Heliana Teixeira and Maarten Trekels and Toon Vandaele and John R.U. Wilson and Tsungai Zengeya and Peter Desmet",
year = "2025",
month = sep,
day = "18",
doi = "https://doi.org/10.1002/2688-8319.70113",
language = "English",
publisher = "John Wiley & Sons, Ltd",
address = "Belgium,
type = "Other"
}

Authors

Quentin Groom
Laura Abraham
Tim Adriaens
Lissa Breugelmans
David A Clarke
Michele Di Musciano
Shawn Dove
Lina M. Estupinan-Suarez
Katelyn T Faulkner
Miguel Fernandez
Louise A Hendrickx
Cang Hui
Alexis Joly
Sabrina Kumschick
Ward Langeraert
Matilde Martini
Joe Miller
Damiano Oldoni
Henrique M. Pereira
Cristina Preda
Tim Robertson
Duccio Rocchini
Andrew Rodrigues
Maxime Ryckewaert
Hanno Seebens
Yanina V. Sica
Heliana Teixeira
Maarten Trekels
Toon Vandaele
John R.U. Wilson
Tsungai Zengeya
Peter Desmet