The collection of moving object data is becoming more and more common, and therefore there is an increasing need for the efficient analysis and knowledge extraction of these data in different application domains. Trajectory data are normally available as sample points, and do not carry semantic information, which is of fundamental importance for the comprehension of these data. Therefore, the analysis of trajectory data becomes expensive from a computational point of view and complex from a user's perspective. Enriching trajectories with semantic geographical information may simplify queries, analysis, and mining of moving object data. In this paper we propose a data preprocessing model to add semantic information to trajectories in order to facilitate trajectory data analysis in different application domains. The model is generic enough to represent the important parts of trajectories that are relevant to the application, not being restricted to one specific application. We present an algorithm to compute the important parts and show that the query complexity for the semantic analysis of trajectories will be significantly reduced with the proposed model.

The Resource Description Framework (RDF) is a metadata model and language recommended by the W3C. This paper presents a framework to incorporate temporal reasoning into RDF, yielding temporal RDF graphs. We present a semantics for these kinds of graphs which includes the notion of temporal entailment and a syntax to incorporate this framework into standard RDF graphs, using the RDF vocabulary plus temporal labels. We give a characterization of temporal entailment in terms of RDF entailment and show that the former does not yield extra asymptotic complexity with respect to nontemporal RDF graphs. We also discuss temporal RDF graphs with anonymous timestamps, providing a theoretical framework for the study of temporal anonymity. Finally, we sketch a temporal query language for RDF, along with complexity results for query evaluation that show that the time dimension preserves the tractability of answers.

Abstract. The Resource Description Framework (RDF) is a metadata model and language recommended by the W3C. This paper presents a framework to incorporate temporal reasoning into RDF, yielding temporal RDF graphs. We present a semantics for temporal RDF graphs, a syntax to incorporate temporality into standard RDF graphs, an inference system for temporal RDF graphs, complexity bounds showing that entailment in temporal RDF graphs does not yield extra asymptotic complexity with respect to standard RDF graphs and sketch a temporal query language for RDF.

OLAP systems support data analysis through a multidimensional data model, according to which data facts are viewed a s p oints in a space of application-related dimensions", organized into levels which conform a hierarchy. The usual assumption is that the data points re ect the dynamic aspect of the data warehouse, while dimensions are r elatively static. However, in practice, dimension updates are often necessary to adapt the multidimensional database to changing requirements. Structural updates can also take place, like addition of categories or modi cation of the hierarchical structure. When these updates are p erformed, the materialized aggregate views that are typically stored in OLAP systems must be e ciently maintained. These updates are p oorly supported or not supported at all in current commercial systems, and have received little attention in the research literature. We present a formal model of dimension updates in a multidimensional model, a collection of primitive operators to perform them, and a study of the e ect of these updates on a class of materialized views, giving an algorithm to e ciently maintain them.

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