Research

 Data have been defined as the fuel of the 21st century.  We now are witnessing a revolution in the production of data, being gathered by ubiquitous information-sensing mobile devices, sensor networks, Web applications, software logs, resulting in a significant increase in data complexity, in terms of volume, heterogeneity, and distribution. Such a huge amount and variety of data, increasingly geo-referenced and dynamic, is a valuable source from which to extract information and knowledge. However, the high volumes and considerable heterogeneity require new management and analysis techniques, able to take into account the specificity of data, also in terms of data quality and semantics.

The DaMA research group faces the increasingly more relevant issues involved in processing and analyzing data, focusing on  how to efficiently and effectively manage data originating from various sources (sensors, services, users, social media, etc.), how to retrieve relevant information from them, also by means of source  interoperability and semantic data integration, and  how to analyze them to discovering new, non-obvious knowledge from these data.