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Abstract
Building accurate knowledge of the identity, the geographic
distribution and the evolution of living species is essential for a sustainable
development of humanity, as well as for biodiversity conservation.
Unfortunately, such basic information is often only partially available
for professional stakeholders, teachers, scientists and citizens, and often
incomplete for ecosystems that possess the highest diversity. In this context,
an ultimate ambition is to set up innovative information systems
relying on the automated identication and understanding of living organisms
as a means to engage massive crowds of observers and boost
the production of biodiversity and agro-biodiversity data. The LifeCLEF
2019 initiative proposes three data-oriented challenges related to this vision,
in the continuity of the previous editions but with several consistent
novelties intended to push the boundaries of the state-of-the-art in several
research directions. This paper describes the methodology of the
conducted evaluations as well as the synthesis of the main results and
lessons learned.