Harnessing the Power of Large Language Models for Conceptual Modeling in Dataspecer
Parent project: Dataspecer - Date modelling a schema generation
Conceptual modeling plays a crucial role in data and software engineering, serving as the foundation for designing complex systems and offering a clear representation of the domain. However, creating precise and comprehensive conceptual models remains a challenge for many engineers. In this project, we aim to explore how large language models can be harnessed to develop an intelligent assistant that guides human modelers in creating structured conceptual models from an abundance of existing resources, including unstructured verbose textual sources, emails, and stakeholder interview notes, as well as structured resources, including existing database structures or excel spreadsheets where users collect their proprietary data. The goal is to support and streamline the modeling process, enhancing the overall quality of data and software engineering projects.
In this project, students will have the opportunity to delve into cutting-edge artificial intelligence and data engineering technologies by working with large language models and applying them to real-world problems. The project's success could open new doors for AI-driven conceptual modeling assistance tools and revolutionize how we design and develop intricate systems. By joining this project, you'll contribute to the future of data and software engineering, honing your skills and making a tangible impact on the field. Don't miss this chance to be part of an innovative research endeavor that could transform the way we approach conceptual modeling in data and software engineering with the help of intelligent assistants.
Contact: Martin Nečaský