LabelledGreenData4All – Annotated Datasets as a Driving Force for Innovation in the Environmental Sector

Annotated data provides the foundation for good modeling and serves as a driving force for advancing AI-driven environmental research. However, the availability of high-quality, harmonized annotated data is extremely limited. The overarching goal is the development of strategic recommendations for the environmental department to identify which applications and data have the greatest potential for ML modeling.

• Harnessing the added value of AI to achieve sustainability goals
• Contributing to the dual transformation (sustainability and digitalization)
• Increasing the availability and visibility of environmental data and environmentally relevant data
• Enhancing the power of annotated data sets to drive innovation

Training Data as a Key

Evaluation and analysis of existing annotation methods will be part of the project, with particular focus on the scalability, quality of results and sustainability of methods used. On this basis, a process model for data annotation will be developed, taking into account different data types and use cases.

“Our aim is to develop an innovative process model that enables efficient and scalable solutions for data annotation. By doing so, AI solutions for the environmental sector can be made profitable and sustainable for the future.”

Data Spaces as a Digital Ecosystem

A key aspect is to improve the availability of annotated environmental data and environmentally relevant data and to share this data across sectors in green data spaces. As a result, data preparation can be significantly reduced and the focus can be placed on innovation.