MOTIVATION: In recent years, public image resources have emerged, but finding quality data efficiently remains a challenge, therefore limiting reuse. RESULTS: IDR searcher is an open-source search engine designed to facilitate the exploration of datasets hosted in public bioimaging resources. The application offers a fast, efficient, cost-effective solution for discovering datasets and has the potential to address current disparities in finding quality datasets for exploratory research and can be combined with metadata visualization tools to enhance usability for the scientific community. AVAILABILITY: IDR searcher is deployed using Ansible playbooks and released under the GPL v2 license. The source code associated with this manuscript is available at https://doi.org/10.5281/zenodo.20641515.

The recycling of organic waste through composting or fermentation is an easy yet underestimated way to bind CO. Due to a lack of awareness, society is still insufficiently separating recyclable organic waste from unsuitable residual waste. Any impurities inevitably reduce the quality of a single container and, thus, the entire load of a waste transporter, resulting in its expensive and less sustainable energy recovery through incineration. To prevent the addition of impurities and the inevitable incineration of valuable organic waste, the problem must be tackled directly at the producer’s site. In the context of a preliminary experimental study, a Smart Trash Can has been developed to automatically take photos of the waste each time it is filled. It serves as a convenient means to collect a series of photos that will contribute to a large dataset for the training of machine-learning models to assess and monitor waste quality. In this way, not only can contaminated waste be separated from pure organic waste, but also feedback, incentives, or nudges can be provided to the user to lead to better waste separation.