The dQUOB system satis es client need for speci c information from high-volume data streams. The data streams we speak of are the ow of data existing during large-scale visualizations, video streaming to large numbers of distributed users, and high volume business transactions. We introduces the notion of conceptualizing a data stream as a set of relational database tables so that a scientist c...

Data-driven applications are becoming increasingly complex with support for processing events and data streams in a looselycoupled distributed environment, providing integrated access to heterogeneous structured data sources such as relational databases and XML data. This paper provides the foundation for defining a framework for materialized views over heterogeneous data sources in an event st...

In recent years, uncertain data has become ubiquitous because of new technologies for collecting data which can only measure and collect the data in an imprecise way. Furthermore, many technologies such as privacy-preserving data mining create data which is inherently uncertain in nature. As a result there is a need for tools and techniques for mining and managing uncertain data. This chapter d...

We introduce a query language over sensors, streams and relations and formally describe its semantics. Although the language was specifically designed for sensor network querying, where data is pulled into streams, the semantics contributed in the paper also encompasses the case in which data is pushed onto streams or else lies stored in classical relations. The approach taken is that continuou...

We address schema design in uncertain databases. Since uncertain data is relational in nature, decomposition becomes a key issue in design. Decomposition relies on dependency theory, and primarily on functional dependencies. We study the theory of functional dependencies (FDs) for uncertain relations. We define several kinds of horizontal FDs and vertical FDs, each of which is consistent with c...

In this paper we rst summarize t he more important aspects of a Logic Fuzzy Relational Database and w e s h ow h ow a fuzzy relational database can be representedand h andled using rst order logic. Given that t he results obtained for fuzzy databasesare satisfactory, we are tackling now t he problem of uncertain fuzzy databases considering that t he fuzzy values stored in the d a tabase are att...

Rational agents perceiving data from a dynamic environment and acting in it have to be equipped with capabilities such as decision making, planning etc. We assume that these capabilities are based on query answering with respect to (high-level) streams of symbolic descriptions, which are grounded in (low-level) data streams. Queries need to be answered w.r.t. an ontology. The central idea is to...