Accepted Poster
Poster Short Abstract
We propose a framework to assess efficiency and to improve the data quality and suitability of citizen and participatory science projects that monitor litter. The proposed framework supports improved resource use, project planning, and public engagement for lasting and sustainable impact.
Poster Abstract
Citizen and participatory science (CPS) play a critical role in expanding spatial and temporal monitoring of anthropogenic litter, while also offering underrecognized societal benefits and personal wellbeing. However, concerns remain regarding the efficiency of CPS projects, particularly in terms of data reliability and resource demands. To support more efficient CPS initiatives, we propose a framework for assessing efficiency in CPS data management workflows through key performance indicators (KPIs). Efficiency is defined here as the competent, and cost- and time-effective production of high-quality and suitable scientific data. We suggest 25 plus KPIs across six main data management phases: planning, collection, validation, standardizing and harmonizing, analysis, and data description and archiving. Thereby, we categorized indicators into (1) generic, (2) participant-oriented, (3) scientific data, and (4) data management indicators. Each KPI is aligned with specific actions and intended outcomes based on practical experience in managing CPS projects, on-site sampling, and interviews with project practitioners and researchers. This KPI Framework serves both as a planning tool for new projects and as a review mechanism for ongoing or completed projects. By applying this KPI-based assessment in every project phase, CPS practitioners can better allocate resources, ensure data quality and suitability, and enhance participant engagement. Ultimately, this approach aims to improve CPS project efficiency and thereby help popularize the utilization of CPS and contribute to greater public awareness and behavioral change regarding anthropogenic litter.
Poster Session