Languages, namely, fragments, of the Datalog+/- family are attracting interest in both academia and industry because of their possibility to balance high expressive power and computational complexity. However, understanding the differences among the fragments, mastering them to achieve scalable industrial applications, and communicating their peculiarities to a non-expert audience is challenging for researchers, developers, logicians, and educators. In this demo, we introduce Vadacode, an IDE for Datalog+/- designed to support a broad category of users. The tool offers advanced features, including fragment detection, syntax highlighting, code completion, error diagnostics, schema inference, debugging support, and AI-assisted coding capabilities. Thanks to our experience in the financial context, our demo will guide the audience in modeling financial Datalog+/- programs, showcasing a seamless and effective coding experience.

Logic-based Knowledge Graphs (KGs) are gaining momentum in academia and industry thanks to the rise of expressive and efficient languages for Knowledge Representation and Reasoning (KRR). These languages accurately express business rules, through which valuable new knowledge is derived. A versatile and scalable backend reasoner, like Vadalog, a state-of-the-art system for logic-based KGs---based on an extension of Datalog---executes the reasoning. In this demo, we present KG-Roar, a web-based interactive development and navigation environment for logical KGs. The system lets the user augment an input graph database with intensional definitions of new nodes and edges and turn it into a KG, via the metaphor of reasoning widgets---user-defined or off-the-shelf code snippets that capture business definitions in the Vadalog language. Then, the user can seamlessly browse the original and the derived nodes and edges within a "Virtual Knowledge Graph", which is reasoned upon and generated interactively at runtime, thanks to the scalability and responsiveness of Vadalog. KG-Roar is domain-independent but domain aware, as exploration controls are contextually generated based on the intensional definitions. We walk the audience through KG-Roar showcasing the construction of certain business definitions and putting it into action on a real-world financial KG, from our work with the Bank of Italy.