A look inside the Pl@ntNet experience. The good, the bias and the hope

Joly Alexis, Bonnet Pierre, Goeau Hervé, Barbe Julien, Selmi Souheil, Champ Julien, Dufour-Kowalski Samuel, Affouard Antoine, Carré Jennifer, Molino Jean-François, Boujemaa Nozha, Barthélémy Daniel. 2016. A look inside the Pl@ntNet experience. The good, the bias and the hope. Multimedia Systems, 22 (6) : 751-766.

https://doi.org/10.1007/s00530-015-0462-9

Article de revue ; Article de revue à facteur d'impact

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Quartile : Q1, Sujet : COMPUTER SCIENCE, THEORY & METHODS / Quartile : Q2, Sujet : COMPUTER SCIENCE, INFORMATION SYSTEMS

Résumé : Pl@ntNet is an innovative participatory sensing platform relying on image-based plants identification as a mean to enlist non-expert contributors and facilitate the production of botanical observation data. One year after the public launch of the mobile application, we carry out a self-critical evaluation of the experience with regard to the requirements of a sustainable and effective ecological surveillance tool. We first demonstrate the attractiveness of the developed multimedia system (with more than 90K end-users) and the nice self-improving capacities of the whole collaborative workflow. We then point out the current limitations of the approach towards producing timely and accurate distribution maps of plants at a very large scale. We discuss in particular two main issues: the bias and the incompleteness of the produced data. We finally open new perspectives and describe upcoming realizations towards bridging these gaps.

Mots-clés Agrovoc : données de production, identification, durabilité, innovation, écologie

Classification Agris : F70 - Taxonomie végétale et phytogéographie
C30 - Documentation et information

Champ stratégique Cirad : Axe 6 (2014-2018) - Sociétés, natures et territoires

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