We are interested in studying how to use the analysis of structured and unstructured data to address societal challenges such as energy efficiency, e-government, or public safety. More specifically, our research is related with in semantic and open data for smartcities and analysis of textual information.
Objectives
- Identifying the appropriate semantics which allows a good expressiveness / computability tradeoff, and parallelization of query execution over single computing resources.
- Massive distribution and parallellization schemas across resources, including indexing.
- To provide approximate and semantically similar answers to these questions rather than no answer, and compile a benchmark of representative queries over urban data; these can be used to quickly find out what data is not available and find alternative ways to work with the existent data that are still useful.
- Development of tools to extract the typical entities and to the identify explicit or hidden relations.