Ressources bibliographiques

Vous trouvez ci-dessous un florilège non exhaustif de ressources bibliographiques dont nous nous servons régulièrement. Ces dernières portent aussi bien sur des concepts & théories scientifiques que sur des outils & approches techniques.

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Articles scientifiques

Grüning B. et al., 2018. Practical Computational Reproducibility in the Life Sciences. Cells Systems. https://doi.org/10.1016/j.cels.2018.03.014

Costello M.J. et al., 2013. Biodiversity data should be published, cited, and peer reviewed. Trends in Ecology and Evolution. https://doi.org/10.1016/j.tree.2013.05.002

Gadelha Jr. L.M.R. et al., 2022. A survey of biodiversity informatics: Concepts, practices, and challenges. WIREs Data Mining and Knowledge Discovery. https://doi.org/10.1002/widm.1394

Gomes D.G.E et al., 2022. Why don't we share data and code? Perceived barriers and benefits to public archiving practices. Proc. R. Soc. B.2892022111320221113 http://doi.org/10.1098/rspb.2022.1113

Gries C. et al., 2023. The Environmental Data Initiative: Connecting the past to the future through data reuse. Ecology and Evolution. https://doi.org/10.1002/ece3.9592

Hardisty A. and Roberts D. 2013 A decadal view of biodiversity informatics: challenges and priorities. BMC Ecology https://doi.org/10.1186/1472-6785-13-16

Hardisty A. et al., 2019 The Bari Manifesto: An interoperability framework for essential biodiversity variables. Ecological Informatics https://doi.org/10.1016/j.ecoinf.2018.11.003

Hiltemann S. et al.. 2023. Galaxy Training: A powerful framework for teaching! PLOS Computational Biology. https://doi.org/10.1371/journal.pcbi.1010752

Jones M.B. et al., 2006 The New Bioinformatics: Integrating Ecological Data from the Gene to the Biosphere. Annual review in Ecology, Evolution and Systematics. https://doi.org/10.1146/annurev.ecolsys.37.091305.110031

Kissling W.D. et al., 2018. Building essential biodiversity variables (EBVs) of species distribution and abundance at a global scale Biological Reviews https://doi.org/10.1111/brv.12359

König C. et al., 2019. Biodiversity data integration—the significance of data resolution and domain. PLOS Biology. https://doi.org/10.1371/journal.pbio.3000183

Mcintire E.J.B. et al., 2022. PERFICT: A Re-imagined foundation for predictive ecology. Ecology Letters. https://doi.org/10.1111/ele.13994

Magagna, B, et al. 2020. Reusable FAIR Implementation Profiles as Accelerators of FAIR Convergence. Advances in conceptual modeling. https://link.springer.com/chapter/10.1007/978-3-030-65847-2_13

Michener W.K. et al., 1997 Non geospatial metadata for ecological sciences. Ecological Applications. https://doi.org/10.1890/1051-0761(1997)007[0330:NMFTES]2.0.CO;2

Michener W.K. and Jones M.B. 2012 Ecoinformatics: supporting ecology as a data-intensive science. Trends in Ecology and Evolution https://doi.org/10.1016/j.tree.2011.11.016

Michener W.K. 2014. Ecological Data Sharing. Ecological Informatics. https://doi.org/10.1016/j.ecoinf.2015.06.010

Michener W.K. et al., 2015 Ten Simple Rules for Creating a Good Data Management Plan. PLOS Computational Biology  https://doi.org/10.1371/journal.pcbi.1004525

Page R. 2016 Towards a biodiversity knowledge graph. Research Ideas and Outcomes https://doi.org/10.3897/rio.2.e8767

Peterson A.T. et al., 2015 A global perspective on decadal challenges and priorities in biodiversity informatics BMC Ecology https://doi.org/10.1186/s12898-015-0046-8

Poisot T. et al., 2019 Ecological Data Should Not Be So Hard to Find and Reuse. Trends in Ecology and Evolution. https://doi.org/10.1016/j.tree.2019.04.005

Powers S.M. & Hampton S.E., 2018. Open science, reproducibility, and transparency in ecology. https://doi.org/10.1002/eap.1822

Recknagel F. 2023. Cyberinfrastructure for sourcing and processing ecological data. Ecological Informatics. https://doi.org/10.1016/j.ecoinf.2023.102039

Rilling M.C. et al., 2015 Biodiversity Research: data without theories - theories without data. Frontiers in Ecology and Evolution https://doi.org/10.3389/fevo.2015.00020

Todman L.C. et al., 2023 ‘Small Data’ for big insights in ecology. Trends in Ecology and Evolution https://doi.org/10.1016/j.tree.2023.01.015

Urban M.C. et al., 2021 Designing a Platform for Projecting and Protecting Global Biodiversity. BioScience https://doi.org/10.1093/biosci/biab127  


Livres

Borgman C.L. (Traduction de Charlotte Matoussowsky), 2020. Qu'est-ce que le travail scientifique des données ? Big data, little data, no data. Encyclopédie numérique. DOI : 10.4000/books.oep.14692

Recknagel F., Michener W.K. et al. 2018. Ecological Informatics : Data management and knowledge discovery. Springer Cham. 3ième édition. 482 pages. https://doi.org/10.1007/978-3-319-59928-1


Rapports - Synthèses

Delavaud A. et al. 2014. État des lieux et analyse des paysages des observatoires français de recherche sur la biodiversité. Expertise et synthèse de la Fondation pour la Recherche sur la Biodiversité. Disponible en ligne sur www.fondationbiodiversite.fr/etat-des-lieux-et-analyse-des-paysages-des-observatoires-francais-de-recherche-sur-la-biodiversite/

Mahé S., Marlin C. et al. 2020 Livre Blanc sur les infrastructures françaises de recherche du domaine des sciences du système Terre et de l’environnement - Vision stratégique d’AllEnvi 2020-2030. Paris, France : AllEnvi, 116 p. Disponible en ligne sur https://www.allenvi.fr/wp-content/uploads/2022/06/Livre_blanc_Infrastructures_2020-2030.pdf

Ministère de l'Ensignement Supérieur et de la Recherche. 2022. Feuille de route nationale des infrastructures de recherche. disponible en ligne sur https://www.enseignementsup-recherche.gouv.fr/sites/default/files/2022-03/feuille-de-route-nationale-des-infrastructures-de-recherche---2021-v2--17318.pdf