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

Conserving wildlife in European landscapes requires continual access to good quality data on their status and distribution. Obtaining such data on shy and low density species is a challenge. Recent developments in digital camera trap technology represent a game change. Widely used by researchers, hunters and naturalists these camera traps collect millions of images of species every year across Europe. However, this data remains fragmented and is not effectively used. The BIG_PICTURE project aims to develop procedures to make this data more available. Firstly, we will examine the legal and social conditions necessary for different individuals and institutions to share data and make it more widely available. Secondly, we will develop the databases and artificial intelligence tools to bring this data together and determine which species the cameras have photographed. Thirdly, we will examine the most relevant statistical tools to analyse data of different types. Finally, we will conduct some demonstration analyses that demonstrate the benefits of widespread data sharing to produce Europe wide overviews of certain topics. This ambitious project involves researchers from 17 institutions in 10 countries from across Europe. Our ambition is to motivate both professional scientists and stakeholders with an interest in wildlife to more openly share data for the long term benefit of wildlife, and people.

Finding pathways for human-biodiversity coexistencein Europe requires up-to-date knowledge on species status, distribution, relative abundance, and their interactions with humans. Effective conservation requires continental scale coordination, which requires continental scale data. This can only be achieved if we avail of methods that (1) can target many species at the same time, and (2) can make use of data collected for many different purposes by a diversity of professional and citizen scientists. Digital camera traps are one such tool, the use of which has exploded in recent years. However, the state of data processing tools and data sharing procedures are not yet developed to allow an efficient classification, storage, and sharing of this data. It is also unclear to what extent data collected under different regimes can be compared. This project proposes a set of four interlinked workpackages that will; (1) Explore legal, institutional, and social contraints on data sharing with a view to identify pathways that faciliate making data as open and available as possible. (2) Develop efficient and AI-enabled database structures that facilitate the efficient processing of raw data, the safe storage of the data, and export formats that conform to emerging data standards to facilitate data sharing and comparative analysis. (3) An exploration of statistical analysis tools and procedures that find ways to maximise the integration of data collected under different protocols into common analysis, essentially determining which data, on which species, can be used to determine which inferences. (4) A set of demonstration analyses that reveal the possibility and added-value that can be obtained when data is pooled across projects and countries. These illustrative analyses will cover a range of biodiversity policy areas, including One Health, Climate Change, Invasive Species, Natura 2000 site management, and conservation of Habitat Directive listed species.