Horizon Europe STARWARS 2020
STormwAteR and WastewAteR networkS heterogeneous data AI-driven managementThis project has received funding from the European Union’s Horizon 2020 research and innovation programme under the MSCA (Marie Skłodowska-Curie Actions, Staff Exchanges)-SE (Staff Exchanges) grant agreement No 101086252 ).
WORK PACKAGE LIST
WP1: Data Collection and Data Completion
Objective 1.1 consists in identifying data sources and collecting data/knowledge. Objective 1.2 deals with unstructured data and building terminological knowledge bases. Objective 1.3 consists in using machine learning and inference algorithms, enhanced by knowledge, for extracting and deriving missing data
WP2: Unreliable and Heterogeneous Data/Information Modelling
Objective 2.1 concerns the definition languages for representing different forms of data and knowledge. Objective 2.2 aims at studying the problem of heterogeneity of data description models or uncertainty frameworks that may happen when the different information sources, to be combined, do not share a common data description language.
WP3: Practical Merging, Inconsistency and Clustering
Objective 3.1 deals with the problem of combining, knowledge dynamic and integration. Objective 3.2 addresses the issue of handling conflicts which is a central feature in fusion and an increasingly important topic within AI. Objective 3.3 relates to the development of classification and graph clustering methods in the context of wastewater and stormwater networks data.
WP4: Tractable Query-answering, Explainability, Algorithms and Validations
Objective 4.1 aims at developing tractable query answering mechanisms that take into account uncertainties and inconsistency of information/data. It also aims at proposing different strategies for explainability, including clustering solutions and argumentations, that go beyond mere weighted answers representations. . Objective 4.2 concerns the building of datasets and the development of algorithms and tools that require empirical validations where experiments will be carried out on real datasets (collected in WP1 and undergone processing steps defined in WP2-3)
WP5: Project management, Communication, Dissemination and Training
This is fully dedicated to the project management, training activities and the dissemination of the research results. It covers in particular i) training sessions and communication of the research results, ii) two summer schools (one on the heterogeneity of wastewater and stormwater networks data and the other on data fusion), iii) two AI specialized workshops (one on information fusion and the other on reasoning with uncertainty), iv) a side event (for the Water Science community) and v) a final workshop aimed at large audience.
DATA GOVEMANCE 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.
WASTEWATER AND STORMWATER DATA TO MODELLING
Dataset for STARWARS
Within this context, the scientific guiding principle of this multidisciplinary project, STARWARS (STormwAteR and WastewAteR networkS heterogeneous data AI-driven management), is to address the challenges identified above by providing novel proposals for the management of heterogeneous data in stormwater and wastewater networks.
Heterogeneous wastewater and stormwater network data first refer to data of different natures such as datasets of factual data, geographical data, various types of images, digital maps (e.g., Figure 3), analogue maps, intervention reports, etc
Heterogeneous wastewater and stormwater network data first refer to data of different natures such as datasets of factual data, geographical data, various types of images, digital maps (e.g., Figure 3), analogue maps, intervention reports, etc
CONSORTIUM PARTNERS
COLLABORATION
Acknowledgement
This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the MSCA (Marie Sklodowska-Curie Actions, Staff Exchanges)-SE (Staff Exchanges) grant agreement No 101086252.