Carlo Dell'Aquila

Logic programming for data warehouse conceptual schema validation

The current lack of a standard methodology for data warehouse design has led to have many possible lifecycles. In some of them, the validation of the data warehouse conceptual schema is a specific process that precedes the translation of such a schema into a logical one. This activity must ensure that the data warehouse to be implemented effectively allows all the analytical queries to be executed correctly. To accomplish this, the validation process takes the preliminary workload into account, that is, a set of queries defined from user requirements to obtain the typical information the users are interested in. The methodologies that perform such a validation process define some guidelines that must be manually executed by an expert. In this paper, we introduce a logic program to automate this activity, by checking a set of predefined issues with an inferential engine.

Dimensional fact model extension via predicate calculus

The Dimensional Fact Model is a conceptual model that allows to design the multidimensional schema of a data warehouse. Its methodology is based on the (re)modelling of the schema of a relational database; such a schema is represented by a tree, and the (re)modelling consists of the traditional operations on graphs (as prune, graft, adding child, change parent, …). The tree is generated automatically by an algorithm, starting from the logical schema of a relational database. Nowadays, this algorithm is not able to manage many-to-many relationships, and then, it stops the tree creation when it meets this kind of relationships. In this work, we propose a novel methodology, able to overcome this algorithmic limit, via the declarative approach of the logical programming.

Architecture of a relational decision support system

Abstract The architecture of the POLD relational system for distributed data analysis is presented. POLD was designed as the kernel of a decision support information system. The peculiarity of POLD consists in allowing the user to view and analyze the data information as couple 〈data, semantics〉, the semantics being a users suitable classification of the data. This approach furnishes the user with a powerful tool for the semantic integration of data coming from different and/or distributed sources. Both semantics and user views are dynamically definable, that is, they may change with user, current time, and application. The POLD system supports an extended version of the relational operations in order to fit the proposed approach. Moreover, this system provides features for statistical analyses, reports and graphical representations.

A research activity support system for the Italian cultural heritage

The work describes a system built on an existing database supporting at high level both data analyses and decision making in a humanistic environment with particular reference to the Italian cultural heritage. The user, a researcher or a scholar, may formulate queries, no matter how complex they are, aided by a friendly windowing interface. To achieve this purpose, he is able to define an appropriate data classification developing an impossible-to-foresee research strategy. In order to analyse the data, the system provides a set of relational-like operations. A sample of the possible applications of our approach to problems such as research analyses and planning in the environment of cultural institutions (museums, art exhibitions, and so on) has been shown.