Because of the rapid growth of data sources, services and devices connected to the Internet, online available web content is getting more and more diverse and dynamic, having multiple dimensions. First, data has a temporal nature, each piece of information having associated a time instant (e.g., publication date). Furthermore, it has a social nature, being the result of a collaborative contribution of individuals or communities, it can be localized in a geographical space (e.g., POI) or have textual descriptions attached (e.g., keywords, tags).
In the first part, I address the particular issue of large-scale aggregation of highly dynamic information sources by focusing on the design of optimal refresh strategies for large collections of RSS feed documents.
In the second part, I introduce the problem of query answering on multidimensional (i.e., social, spatial, textual and temporal) data, discussing the context, the challenges and some research directions.
