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

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.

Bibliographic Details

Main Authors:	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
Format:	article biblioteca
Language:	eng
Subjects:	F70 - Taxonomie végétale et phytogéographie, C30 - Documentation et information, données de production, identification, durabilité, innovation, écologie, http://aims.fao.org/aos/agrovoc/c_32548, http://aims.fao.org/aos/agrovoc/c_3791, http://aims.fao.org/aos/agrovoc/c_33560, http://aims.fao.org/aos/agrovoc/c_27560, http://aims.fao.org/aos/agrovoc/c_2467,
Online Access:	http://agritrop.cirad.fr/577377/ http://agritrop.cirad.fr/577377/7/art%253A10.1007%252Fs00530-015-0462-9.pdf
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