DMTES aims to approach and to promote the interaction between the Environmental Sciences community and the Data Mining/Data Science community and related fields, such as Artificial Intelligence, Statistics, Intelligent Decision Making Support Systems or other fields, all providing methodologies to extract added value from data, so that actionable knowledge to support further decision-making is generating. We invite submissions of papers and presentations about applications of data science, data mining and related methodologies to environmental problems. In this edition we encourage works oriented to explainable AI, digital transformation and H2030 agenda for Sustainable Development Goals (SDG).
The session welcomes applications related with, but not limited to water, air quality and natural resources management to ecological footprint and circular economy or environmental policies, and works addressing issues related to data quality, explainability of models, and role in decision support processes.
New or improved techniques or methods are welcomed, as well as innovative applications, including heterogenous sources of information, like classical data, images, open text, semmantic data, georeferenced data, data streams among others.