1 Introduction -- 2 Developing mobile applications for environmental and biodiversity citizen science: considerations and recommendations -- 3 A toolbox for understanding and implementing a citizens' observatory on air monitoring -- 4 A Real-Time Streaming and Detection System for Bio-acoustic Ecological Studies after the Fukushima Accident -- 5 Towards improved air quality monitoring using publicly available sky images -- 6 Traits: Structuring species information for discoverability, navigation and identification -- 7 Unsupervised Bioacoustic Segmentation by Hierarchical Dirichlet Process Hidden Markov Model -- 8 Plant Identification: Experts vs. Machines in the Era of Deep Learning -- 9 Automated identification of herbarium specimens at different taxonomic levels -- 10 A deep learning approach to species distribution modelling -- A Existing Data and Metadata Standards and Schemas related to Citizen Science -- B Creative Commons (CC) and Open Data Commons (ODC) Licenses -- C List of Apps, Platforms and their Functionalities in Citizen Science Projects -- D Examples of Symbolic and Non-symbolic Rewards in Citizen Science Projects -- E List of Apps for Sonic Environment and Noise Pollution Monitoring.