Databases and Information Systems

The Databases and Information Systems research group is at the forefront of exploring innovative approaches to managing, accessing, and processing Big Data. Our work spans three key areas of research, each contributing to the advancement of the data management foundations of data science and technology and addressing the challenges of a connected and data-driven world:

• Big Data Management and Storage: In this area, we focus on the development of novel multi-model database systems that are designed to handle the ever-increasing volume, variety, and velocity of data in modern applications. Our research seeks to enhance the way data is stored, integrated, and retrieved by creating more efficient and scalable database systems that support a diverse range of data models, ensuring high performance and flexibility for large-scale data storage.
• Big Data Access and Retrieval: As the volume of multimedia data grows, the ability to search and visualize large (multimedia) collections becomes a critical challenge. In this area, we develop cutting-edge techniques for improving search capabilities, making it easier to retrieve relevant information from vast datasets. Our work includes designing algorithms and interfaces for efficient data retrieval, as well as creating innovative visualization tools to help users explore and understand complex datasets in an intuitive way.
• Big Data Processing and Analytics: To unlock the full potential of Big Data, efficient processing and real-time analytics are essential. In this research area, we focus on the development of novel data stream processing systems that enable real-time analysis of large, continuous data flows. Our work includes the creation of advanced systems that can handle dynamic data streams, perform complex event detection on the fly, and support decision-making processes based on streaming and non-streaming data.

In addition to our core research in Big Data, the Databases and Information Systems group is also dedicated to advancing eHealth technologies. We collaborate on projects that aim to improve healthcare through the use of data-driven insights, ensuring that innovations in data management can enhance patient care, clinical decisions, and public health initiatives.

Our commitment to open source development plays a central role in our work. We actively contribute to the creation and dissemination of open-source software solutions, providing tools, libraries, and platforms that are freely available to researchers, developers, and practitioners. By making our software open and accessible, we foster collaboration, transparency, and innovation in both academia and industry.