Supporting cross-disciplinary research in natural sciences

This story derives from a market need identified by the service provider. There are thousands of applications in the natural sciences field who were asking for an automated plant identification system within their own applications. Examples include apps that need plant identification systems because they use this information to study the properties of soil and its quality, or because they need to identify specific agricultural practices or promote biodiversity. There are different types of services that build on plant identification which is therefore horizontal to the needs of many related communities. The developers of such apps need to access plant information easily to include this in their research or commercial workflow.

The challenge of providing this service mainly lies in the very high diversity of plant species to be identified and in managing the large number of queries and connected users without destabilising the system.

The proposed solution is called Pl@ntNET, a citizen observatory and AI-based Platform designed to monitor plants biodiversity and help identify plants via pictures. It is organised in different thematic and geographical floras operational via a search engine.

Pl@ntNET enables  cross-disciplinary research, as the  types of data that can be collected and shared encompass various natural science fields, such as agriculture, environment and biodiversity. Through the EOSC Portal the cross-disciplinarity, credibility and accessibility of this service across Europe have increased”
Alexis Joly, Researcher and Leader of Pl@ntNet @ INRIA, Partner @Cos4Cloud

The service was developed within the Cos4cloud project.

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