Fèlix Saltor

YAM 2 : a multidimensional conceptual model extending UML

This paper presents a multidimensional conceptual Object-Oriented model for Data Warehousing and OLAP tools, its structures, integrity constraints and query operations. It has been developed as an extension of UML core metaclasses to facilitate its usage, and try to fill the absence of a standard model. Being a UML extension allows reusing modeling constructs and techniques, and integrating multidimensional modeling in more general modeling processes. Moreover, while existing multidimensional models are restricted to the modeling of isolated stars, this paper investigates the representation of several semantically related star schemas. Summarizability and identification constraints can also be represented in the model, and a closed and complete set of algebraic operations has been defined in terms of functions (so that mathematical properties of functions can be smoothly applied).

Emergent semantics principles and issues

Information and communication infrastructures underwent a rapid and extreme decentralization process over the past decade: From a world of statically and partially connected central servers rose an intricate web of millions of information sources loosely connecting one to another. Today, we expect to witness the extension of this revolution with the wide adoption of meta-data standards like RDF or OWL underpinning the creation of a semantic web. Again, we hope for global properties to emerge from a multiplicity of pair-wise, local interactions, resulting eventually in a self-stabilizing semantic infrastructure. This paper represents an effort to summarize the conditions under which this revolution would take place as well as an attempt to underline its main properties, limitations and possible applications.

Suitability of datamodels as canonical models for federated databases

We develop a framework of characteristics, essential and recommended, that a data model should have to be suitable as canonical model for federated databases. This framework is based on the two factors of the representation ability of a model: expressiveness and semantic relativism. Several data models are analyzed with repect to the characteristics of the framework, to evaluate their adequacy as canonical models.

A Framework for the Classification and Description of Multidimensional Data Models

The words On-Line Analytical Processing bring together a set of tools, that use multidimensional modeling in the management of information to improve the decision making process. Lately, a lot of work has been devoted to modeling the multidimensional space. The aim of this paper is two fold. On one hand, it compiles and classifies some of that work, with regard to the design phase they are used in. On the other hand, it allows to compare the different terminology used by each author, by placing all the terms in a common framework.

Overcoming Schematic Discrepancies in Interoperable Databases

Abstract An important kind of semantic conflicts arising in database interoperability are schematic discrepancies, where data in one database correspond to metadata in another. We present a general solution to these discrepancies, based on a framework of two dimensions: generalization and aggregation. Operations to transform metadata into data and vice versa are defined, in the relational model and in an object-oriented model. These operations may be applied at different levels in a federated architecture.

Semantic enrichment of database schemes: an object oriented approach

When a database is to be interoperated with others, its scheme must first be converted to the canonical model of the federated system. This implies a knowledge acquisition process to upgrade the semantic level of the scheme. The authors present a methodology to convert relational schemas to a semantically rich object oriented model. It is based on inclusion dependencies, but also takes into account exclusion and complementariness dependencies.<<ETX>>

Database Architecture for Data Warehousing: An Evolutionary Approach

In recent years, data warehouses have reached a prominent position in the database field, especially in the database industry. There are many issues in common between data warehouses and other database fields such as federated databases; in our opinion this fact has not been explored in its entirety. In this paper, an integrated database architecture in which data warehouses are part of the database is put forward. Instead of having data warehouses built using a database, we propose to have data warehouses defined as part of the database architecture; this architecture is defined as an extension of a federated database architecture.

On relationships offering new drill-across possibilities

OLAP tools divide concepts based on whether they are used as analysis dimensions, or are the fact subject of analysis, which gives rise to star shape schemas. Operations are always provided to navigate inside such star schemas. However, the navigation among different stars is usually overlooked. This paper studies different kinds of Object-Oriented conceptual relationships (part of UML standard) between stars (namely Derivation, Generalization, Association, and Flow) that allow to drill across them.

Semantically Enriching Relational Databases into an Object Oriented Semantic Model

A method to convert relational schemas to an object oriented semantic model is presented. It makes explicit knowledge about the semantic of the database that was implicit in the schemas or in the extension, through a knowledge acquisition phase. The method is general, semiautomatic, and has a number of applications.

Discovering interdatabase resemblance of classes for interoperable databases

The integration of database schemas into a federated one involves a detection phase where the similarities that exist among the classes of the different databases must be discovered in order to determine their semantic relationships. This phase is typically characterized by the complexity of the comparison task and the deep knowledge about the semantics of the databases that is required to perform it. The authors present an approach to handle this problem by upgrading the semantic level of the local schemas and guiding the search of the comparison process by the structure of the generalization/specialization semilattices and aggregation graphs of the resulting rich schemas. Unnecessary as well as most promising comparisons are identified and a systematic procedure to analyze the rich component schemas in a meaningful way is given. A reduction of the complexity is achieved. The methodology serves as the basis for a tool that semiautomatizes the process. The expressiveness of the canonical model plays a central role.<<ETX>>