The complexity of database systems has increased alongside the exponential growth of data, necessitating Information Systems (IS) architects to continuously refine data models and meticulously select storage and management options that align with requirements. While existing solutions focus on data model transformation, none offer guidance in selecting the most suitable model. In this context, we propose DaMoOp , an automated approach for leading data model selection process. DaMoOp starts from a conceptual model and associated use case comprising queries, settings and infrastructure constraints, to generate relevant logical data models. A cost model, considering environmental, financial, and temporal factors, facilitates comparison and selection of the most suitable data model. Our cost model incorporates both data model and queries costs. Additionally, we suggest a data model selection process that enhances the ability to choose the optimal data model(s) for a specific use case, while also adapting to rapidly evolving use cases. We provide a strategic optimization approach designed to identify the most cost-efficient and stable data model as use case scenarios evolve. Moreover, we offer a simulation tool for the entire process, which enables visualizing the impact of use case variations on data model costs, thus empowering IS architects to make informed decisions.

International audience

International audience

Monitoring Sustainable Development Goal (SDG) indicators requires integrating heterogeneous open datasets from sources such as relational databases, NoSQL stores, and APIs. While SDG indicators follow standardized definitions, open data sources are often fragmented, schema-less, and inconsistent, making both integration and computation challenging. In this demonstration, we present SDG-KG , a spatio-temporal Knowledge Graph (KG) framework designed to structure metadata, guide data retrieval, and formalize indicator computation workflows. Our approach leverages graph-based modeling to construct a Metadata Graph, apply conflict resolution techniques when multiple sources provide overlapping data, and dynamically generate query-driven execution plans. Through an interactive interface, users can explore United Nations specifications, inspect data provenance and the generated KG, and visualize the computed indicators.

International audience