BIG_PICTURE: Developing data management and analytical tools to integrate and advance professional and citizen science camera-trapping initiatives across Europe

The main objective of the BIG_PICTURE project is to bring together the enormous amount of species data that is collected by the thousands of wildlife camera traps (automatic cameras) distributed across Europe by professional researchers, citizen scientists and other private individuals. By developing the appropriate electronic infrastructure (databases and artificial intelligence-driven image processing capability) and statistical tools for data analysis, the BIG_PICTURE project will facilitate the sharing, integration and joint analysis of data collected by many different institutions, allowing continental-scale assessments of species’ status.

BIG_PICTURE will have 5 main areas of activity.

1. We will examine the legal and institutional issues that enable or constrain data
   sharing.
2. We will build procedures to connect different databases and develop robust
   AI-enabled image processing tools.
3. We will develop best practice procedures for different statistical analysis tools
   that can be best applied to different types of data.
4. Using the results of the previous parts, we will conduct some demonstration analyses to show the added value of data sharing.
5. Finally, we will ensure the dissemination of the project’s tools, focusing on a diversity of end users, including wildlife / nature managers at regional, national, and European levels, hunters, foresters, naturalists and scientists, as well as the general public.

The expected impacts of the project include (a) motivating data sharing, by creating easy to use and efficient mechanisms and demonstrating the value of doing so, (b) enhancing our knowledge of wildlife status and ecology across Europe, (c) provide guidance for management and conservation activities, and d) increasing public awareness of the spectacular recovery of our continent’s wildlife and of the challenges represented by “living with success” in conservation.

Partners of the project

• LEADER: Department of Forestry and Wildlife Management, Inland Norway University of Applied Sciences, Koppang, Norway
• NINA Lillehammer, Norwegian Institute for Nature Research, Lillehammer, Norway
• Department for National Park Monitoring, Bavarian Forest National Park, Grafenau, Germany
• Department of Wildlife Management and Invasive Species, Research Institute for Nature and Forest, Brussels, Belgium
• Centre for Functional Ecology and Evolution, CNRS Campus, Montpellier, France
• Animal Ecology Unit, Research and Innovation Centre, Edmund Mach Foundation, Trentino, Italy
• Institute for Complex Systems – Florence Section, National Research Council of Italy, Sesto Fiorentino, Italy
• Department of Public Law and Governance, Tilburg Law School, Partners of the project Tilburg, Netherlands
• Population Ecology Research Unit, Mammal Research Institute, Bialowieza, Poland
• Department of Biology, University of Florence, Florence, Italy
• Institute for Game and Wildlife Research, University of Castilla-LaMancha, Ciudad Real, Spain
• Department of Wildlife, Fish and Duration Environmental Studies, Swedish University of Agricultural Sciences, Umeå, Sweden
• Faculty of Mathematics, Natural Sciences and Information Technology, University of Primorska, Koper, Slovenia
• Faculty of Environmental Protection, Velenje, Slovenia
• Biotechnical Faculty, University of Ljubljana, Slovenia
• Department of Migration, Max Planck Institute of Animal Behavior, Radolfzell, Germany
• Department of Environmental Sciences, Wageningen University, Wageningen, Netherlands