Project description
Data governance for improved wastewater management
Accurate and updated information on the state of underground wastewater and stormwater networks is important, but it is also a big challenge to collect and maintain. The difficulty stems from the large quantities and multiple sources of information – from digital maps and geographical data to imprecise data that needs to be assessed, not to mention evolving and conflicting data. In this context, the EU-funded STARWARS project will provide novel proposals for the management of heterogeneous data in stormwater and wastewater networks. To that end, it will bring together researchers from the fields of AI and water sciences to find solutions for handling data of different forms in a variety of ways.
Objective
Public and private stakeholders of the wastewater and stormwater sectors are increasingly faced with large quantities and multiple sources of information/data of different nature: databases of factual data, geographical data, various types of images, digital and analogue maps, intervention reports, incomplete and imprecise data (on locations and the geometric features of networks), evolving and conflicting data (from different eras and sources), etc. Obtaining accurate and updated information on the underground wastewater and stormwater networks is a challenge and a cumbersome task, especially in cities undergoing urban expansion.
Within this context, the main objective of this multidisciplinary project, STARWARS (STormwAteR and WastewAteR networkS heterogeneous data AI-driven management), is to address this challenge by providing novel proposals for the management of heterogeneous data in stormwater and wastewater networks.
The STARWARS project aims to bring together researchers from the AI and Water Sciences communities in order to enhance the emergence of new practical solutions for representing, managing, modelling, merging, completing, reasoning, explaining and query answering over data of different forms pertaining to stormwater and wastewater networks.
The project is implemented through five work packages (WP). The first four WP concern research developments of new AI methodologies for managing heterogeneous stormwater and wastewater networks’ data. The fifth WP is dedicated to project management and dissemination activities.
The second objective of the project is to produce new knowledge and to promote knowledge exchange, with a strong will and a plan to encourage knowledge sharing between the researchers involved in this STARWARS project. The scheduled secondment plan is designed with the aim of maximizing knowledge transfer and training between the two fields of Water Sciences and AI and thus facilitating the achievement of the project objectives.
Fields of science
Keywords
Programme(s)
- HORIZON.1.2 - Marie Skłodowska-Curie Actions (MSCA) Main Programme
Funding Scheme
HORIZON-TMA-MSCA-SE - HORIZON TMA MSCA Staff ExchangesCoordinator
75794 Paris
France