The current business reality induces frequent acquisitions and merges of companies and organizations, and more and more tight interaction between information systems of cooperating companies. We present our contributions to Context-ADDICT, a framework supporting on-the-fly (semi-) automatic data integration, context modeling and context-aware data filtering. Data Integration is achieved in Context-ADDICT by means of automatic ontology-based data source wrapping and integration. While this approach lays its foundations in a solid theoretical background, it also provides heuristics to solve the practical aspects of data integration in a dynamic context. 

More details on this research effort can be found at: http://kid.dei.polimi.it/

Another research topic I have worked on is the exploitation of the Java language as an Hardware Description Language for IP-Core definition in the context of the DRESD project. The main advantage will be the leveraging of the familiarity of the developer with an existing language, and the exploitation of existing IDE for the Java language, while maintaining the performance typical of the Caronte architecture, developed in the DRESD project.

More details can be found at: http://www.dresd.org/

TinyLIME is a middleware for wireless sensor networks (WSN) that departs from the traditional WSN setting where sensor data is collected by a central monitoring station, and enables instead multiple mobile monitoring stations to access the sensors in their proximity and share the collected data through wireless links. This intrinsically context-aware setting is demanded by applications where the sensors are sparse and possibly isolated, and where on-site, location-dependent data collection is required. An extension of LIME, TinyLIME makes sensor data available through a tuple space interface, providing the illusion of shared memory between applications and sensors. Data aggregation capabilities and a power-savvy architecture complete the middleware features.

 Please refer to the official webpage for more details and to download the system. 

Under the guidance of Professor Carlo Zaniolo I'm currently work on schema  evolution and Temporal Databases. Every Information System (IS) is subject to an  uninterrupted evolution process aimed at adapting the system to changing requirements. One of the most critical portions (of the IS) to evolve is the data management core.

Often based on relational database technologies, the data  management core of a system needs to evolve whenever the revision process requires modifications in the set of data or in the way they are stored or maintained, e.g., to increase performance. Given its fundamental role, the evolution of the database underlying an IS has a very strong impact on (all) the application(s) accessing the data, and support for a graceful evolution is of paramount importance nowadays. The complexity of database and software maintenance, clearly, grows with the size and complexity of the system.

Furthermore,when moving from intra-company systems, typically managed by rather small and stable teams of developers/administrators, to collaboratively-developed and -maintained public systems, the need for a well-behaved evolution becomes indispensable. In this web-scale scenario, due to its collaborative nature and fast rate of growth, the forces driving a system to change become “wilder”, while stability, shared agreement, and evolution documentation become crucial. This part of the research is thus devoted to the effort of developing methodologies and tools to support seamless database evolution by means of query rewriting and migration support.

Within this context we developed two systems: PRISM, a system to support schema evolution in relational snapshot databases, and PRIMA:a system to support data archival and querying under schema evolution.