This paper presents a proposal for a Data Warehouse Conceptual Data Model which allows for the description of both the relevant aggregated entities of the domain--- together with their properties and their relationships with other relevant entities---and the relevant dimensions involved in building the aggregated entities. The proposed Data Warehouse Conceptual Data Model is able to capture the database schemata expressed in the most interesting traditional Semantic Data Models and Object-Oriented Data Models; it is able to introduce complex descriptions of the structure of aggregated entities and multiply hierarchically organised dimensions; it is based on Description Logics, a class of formalisms for which it is possible to study the expressivity in relation with decidability of reasoning problems and completeness of algorithms; it supports the most important reasoning services for the basic Data Warehouse operations. 1 Introduction Data Warehouse---and especially OLAP---application...

In this paper a semantic approach for the specification and the management of databases with evolving schemata is introduced. It is shown how a general object-oriented model for schema versioning and evolution can be formalized; how the semantics of schema change operations can be defined; how interesting reasoning tasks can be supported, based on an encoding in description logics.

Abstract. Information integration is the problem of combining the data residing at different, heterogeneous sources, and providing the user with a unified view of these data, called mediated schema. The mediated schema is therefore a reconciled view of the information, which can be queried by the user. It is the task of the system to free the user from the knowledge on where data are, and how data are structured at the sources. In this chapter, we discuss data integration in general, and describe a logic-based approach to data integration. A logic of the Description Logics family is used to model the information managed by the integration system, to formulate queries posed to the system, and to perform several types of automated reasoning supporting both the modeling, and the query answering process. We focus, in particular, on a specific Description Logic, called DLR, specifically designed for database applications. In the chapter, we illustrate how DLR is used to model a mediated schema of an integration system, to specify the semantics of the data sources, and finally to support the query answering process by means of the associated reasoning methods. 1

Answering queries using views amounts to computing the answer to a query having information only on the extension of a set of views. This problem is relevant in several fields, such as information integration, data warehousing, query optimization, etc. In this paper we address the problem of query answering using views for nonrecursive datalog queries embedded in a Description Logics (equipped with n-ary relations) knowledge base. We present the following results. Query answering using views is decidable in all cases. Specifically, if the set of all objects in the knowledge base coincides with the set of objects stored in the views (closed domain assumption), the problem is coNP complete, whereas if the knowledge base may contain additional objects (open domain assumption) it is solvable in double exponential time. 1

Recent efforts in the Conceptual Modelling community have been devoted to properly capturing time-varying information. Various temporally enhanced Entity-Relationship (ER) models have been proposed that are intended to model the temporal aspects of database conceptual schemas. This work gives a logical formalisation of the various properties that characterise and extend different temporal ER models which are found in literature. The formalisation we propose is based on Description Logics (DL), which have been proved useful for a logical reconstruction of the most popular conceptual data modelling formalisms.

. We establish the equivalence of: (1) the logical implication problem for a description logic dialect called DLClass that includes a concept constructor for expressing uniqueness constraints, (2) the logical implication problem for path functional dependencies (PFDs), and (3) the problem of answering queries in deductive databases with limited use of successor functions. As a consequence, we settle an open problem concerning lower bounds for the PFD logical implication problem and show that a regularity condition for DLClass that ensures low order polynomial time decidability for its logical implication problem is tight.

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In this paper we study a DL rich enough to express UML class diagrams including ISA and disjointness between classes (but not covering constraints), typing of associations, and participation and functional cardinality constraints. For such a

This paper introduces a new logical formalism, intended for temporal conceptual modelling, as a natural combination of the well-known description logic DLR and point-based linear temporal logic with Since and Until. The expressive power of the resulting DLRUS logic is illustrated by providing a characterisation of the most important temporal conceptual modelling constructs appeared in the literature. We define a query language (where queries are non-recursive Datalog programs and atoms are complex DLRUS expressions) and investigate the problem of checking query containment under the constraints defined by DLRUS conceptual schemas---i.e., DLRUS knowledge bases---as well as the problems of schema satisfiability and logical implication.

. Aggregated objects play an important role in many knowledge representation applications. For the adequate representation of aggregated objects, it is crucial to represent part-whole relations. We discuss properties of part-whole relations and extend the description logic ALC with means for the adequate representation of part-whole relations and thus of aggregated objects. 1 Motivation Description logics are a family of knowledge representation formalisms well-suited for the representation of and reasoning about configurations [27, 21], ontologies [19], and database schemata, where they can support schema design, evolution, and query optimisation [4, 7], source integration in heterogeneous databases/data warehouses [5, 6], and conceptual modeling of multidimensional aggregation [11]. In all these applications, aggregated objects play a central role, that is, objects that are composed of various parts, which again can be composite, etc. It is natural to describe an aggregated object...