Occurrence

Pl@ntNet observations

Latest version published by Pl@ntNet on 8 February 2023 Pl@ntNet
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Publication date:
8 February 2023
Published by:
Pl@ntNet
License:
CC-BY 4.0

Download the latest version of this resource data as a Darwin Core Archive (DwC-A) or the resource metadata as EML or RTF:

Data as a DwC-A file download 1,714,213 records in English (320 MB) - Update frequency: not planned
Metadata as an EML file download in English (16 KB)
Metadata as an RTF file download in English (11 KB)

Description

Pl@ntNet is a participatory botanical observation platform allowing to identify plants from photos (using deep learning) and to share the observations with the community. The platform has three main front-ends: Pl@ntNet androïd (http://bit.ly/1K4D1eU), Pl@ntNet iOS (http://apple.co/2cMtWgu) and Pl@ntNet web (https://identify.plantnet.org/). Pl@ntNet was founded in 2010 by a consortium of four French research organisms (CIRAD, Inria, INRAE and IRD) and is now open to other members. More information about Pl@ntNet project can be found at https://plantnet.org/. The observations in this collection are the ones for which the authors agree to share the associated pictures under a creative common licence and for which the species name is considered as valid.

Data Records

The data in this occurrence resource has been published as a Darwin Core Archive (DwC-A), which is a standardized format for sharing biodiversity data as a set of one or more data tables. The core data table contains 1,714,213 records.

1 extension data tables also exist. An extension record supplies extra information about a core record. The number of records in each extension data table is illustrated below.

Occurrence (core)
1714213
Multimedia 
2131755

This IPT archives the data and thus serves as the data repository. The data and resource metadata are available for download in the downloads section. The versions table lists other versions of the resource that have been made publicly available and allows tracking changes made to the resource over time.

Versions

The table below shows only published versions of the resource that are publicly accessible.

How to cite

Researchers should cite this work as follows:

AFFOUARD A, JOLY A, LOMBARDO J, CHAMP J, GOEAU H, CHOUET M, GRESSE H, BONNET P (2023): Pl@ntNet observations. v1.8. Pl@ntNet. Dataset/Occurrence. https://ipt.plantnet.org/resource?r=observations&v=1.8

Rights

Researchers should respect the following rights statement:

The publisher and rights holder of this work is Pl@ntNet. This work is licensed under a Creative Commons Attribution (CC-BY) 4.0 License.

GBIF Registration

This resource has been registered with GBIF, and assigned the following GBIF UUID: 7a3679ef-5582-4aaa-81f0-8c2545cafc81.  Pl@ntNet publishes this resource, and is itself registered in GBIF as a data publisher endorsed by GBIF France.

Keywords

Occurrence; Observation; Occurrence

Contacts

Who created the resource:
-

Antoine AFFOUARD
Engineer
Inria
LIRMM
34095 Montpellier
FR
Julien CHAMP
Research Engineer
Inria
LIRMM
34095 Montpellier
FR
Hervé GOEAU
Researcher
CIRAD, AMAP Joint Research Unit
Cirad, Umr Amap - TA A-51/ps1, Bd de La Lironde
34398 Montpellier Cedex 5 (France)
FR
Mathias CHOUET
Engineer
Inria
LIRMM
34095 Montpellier
FR
Hugo GRESSE
Engineer
Inria
LIRMM
34095 Montpellier
FR
Pierre BONNET
Botanist
CIRAD, AMAP Joint Research Unit
Cirad, Umr Amap - TA A-51/ps1, Bd de La Lironde
34398 Montpellier Cedex 5 (France)
FR
http://agents.cirad.fr/index.php/Pierre+BONNET

Who can answer questions about the resource:

Pierre BONNET
Botanist
CIRAD, AMAP Joint Research Unit
Cirad, Umr Amap - TA A-51/ps1, Bd de La Lironde
34398 Montpellier Cedex 5 (France)
FR
http://agents.cirad.fr/index.php/Pierre+BONNET

Who filled in the metadata:
-

Antoine AFFOUARD
Engineer
Inria
LIRMM
34095 Montpellier
FR

Who else was associated with the resource:

Antoine AFFOUARD
Programmer
Engineer
Inria
LIRMM
34095 Montpellier
FR

Geographic Coverage

Plant observations from Pl@ntNet network come from all around the world.

Bounding Coordinates South West [-90, -180], North East [90, 180]

Taxonomic Coverage

Pl@ntNet observations focus on plants.

Kingdom Plantae (Plant)

Project Data

PlantNet is a participatory botanical observation platform allowing to identify plants from photos (using deep learning) and share observations with the community. This resource contains illustrated observations explicitly shared by PlantNet users under a Creative Common license.

Title Pl@ntNet Observations
Identifier observations
Funding PlantNet is an open consortium founded by four French research organizations (CIRAD, Inria, INRAE, IRD) and supported by Agropolis Fondation. The two main funding resources are: (i) the annual contribution of the members of the consortium, (ii) donations from the end-users of PlantNet application (>10 million users).
Study Area Description Entire world

The personnel involved in the project:

Antoine AFFOUARD
Programmer
Alexis JOLY
Pierre BONNET

Sampling Methods

No sampling protocol, opportunistic observations by Pl@ntNet users.

Study Extent Entire world, Plantae.
Quality Control The validation is based on three main criteria: - the identification confidence score greater than a given threshold, the score being inferred from (i) the output of the automated identification algorithm (categorical probability) and (ii) the species names proposed by the members - the contributor has a reputation score higher than a given threshold - the species name matches the checklist considered as the most trusted one for the country where the observation was done

Method step description:

  1. This collection contains observations of plants shared by Pl@ntNet users using one the three Pl@ntNet applications (androïd, iOS, web, more information here: https://plantnet.org/). The following filters were applied: - image license cc-* - is geolocated - is valid (identification score > threshold) - from a user with an enabled account - with a known species name (valid or synonym) in Pl@ntNet - species name != Cannabis - date_observation > 0 - must be in one of the WGSRPD polygon level 3 and the binomial species name (without author) must match a species of the corresponding Kew checklist

Bibliographic Citations

  1. Joly, A., Goëau, H., Bonnet, P., Bakić, V., Barbe, J., Selmi, S., ... & Yahiaoui I., Carré J., Mouysset E., Molino J.-f., Boujemaa B., Barthélémy D., (2014). Interactive plant identification based on social image data. Ecological Informatics, 23, 22-34. https://doi.org/10.1016/j.ecoinf.2013.07.006
  2. Joly, A., Bonnet, P., Goëau, H., Barbe, J., Selmi, S., Champ, J., Dufour-Kowalski, S., Affouard, A., Carré, J., Molino, J.-f., Boujemaa, N., & Barthélémy D., (2016). A look inside the Pl@ntNet experience. Multimedia Systems, 22(6), 751-766. https://doi.org/10.1007/s00530-015-0462-9
  3. Goëau, H., Bonnet, P., Joly, A., 2017. Plant identification based on noisy web data: the amazing performance of deep learning (LifeCLEF 2017). CLEF: Conference and Labs of the Evaluation Forum, Sep 2017, Dublin, Ireland. ⟨hal-01629183⟩ https://hal.archives-ouvertes.fr/hal-01629183
  4. Affouard, A., Goëau, H., Bonnet, P., Lombardo, J. C., & Joly, A., (2017). Pl@ntNet app in the era of deep learning. ICLR: International Conference on Learning Representations, Apr 2017, Toulon, France. ⟨hal-01629195⟩ https://hal.archives-ouvertes.fr/hal-01629195

Additional Metadata

Alternative Identifiers 7a3679ef-5582-4aaa-81f0-8c2545cafc81
https://ipt.plantnet.org/resource?r=observations