Guaranteeing no interaction between functional dependencies and tree-like inclusion dependencies

Functional dependencies (FDs) and inclusion dependencies (INDs) are the most fundamental integrity constraints that arise in practice in relational databases. A given set of FDs does not interact with a given set of INDs if logical implication of any FD can be determined solely by the given set of FDs, and logical implication of any IND can be determined solely by the given set of INDs. The set of tree-like INDs constitutes a useful subclass of INDs whose implication problem is polynomial time decidable. We exhibit a necessary and sufficient condition for a set of FDs and tree-like INDs not to interact; this condition can be tested in polynomial time

Spectra in taxonomic evidence in databases III : Application in celestial bodies. Asteroids families

Numerical Taxonomy aims to group in clusters, using so-called structure analysis of operational taxonomic units (OTUs or taxons or taxa) through numerical methods. These clusters constitute families. Structural analysis, based on their phenotypic characteristics, exhibits the relationships, in terms of degrees of similarity, between two or more OTUs. Entities formed by dynamic domains of attributes, change according to taxonomical requirements: Classification of objects to form families or clusters. Taxonomic objects are here represented by application of the semantics of the Dynamic Relational Database Model. Families of OTUs are obtained employing as tools i) the Euclidean distance and ii) nearest neighbor techniques. Thus taxonomic evidence is gathered so as to quantify the similarity for each pair of OTUs (pair-group method) obtained from the basic data matrix. The main contribution of the present work is to introduce the concept of spectrum of the OTUs, based in the states of their characters. The concept of families’ spectra emerges, if the superposition principle is applied to the spectra of the OTUs, and the groups are delimited through the maximum of the Bienaymé-Tchebycheff relation, that determines Invariants (centroid, variance and radius). Applying the integrated, independent domain technique dynamically to compute the Matrix of Similarity, and, by recourse to an iterative algorithm, families or clusters are obtained. A new taxonomic criterion is thereby formulated. An astronomic application is worked out. The result is a new criterion for the classification of asteroids in the hyperspace of orbital proper elements (the well-known Families of Hirayama). Using an updated database of asteroids we ascertain the robustness of the method. Thus, a new approach to Computational Taxonomy is presented, that has been already employed with reference to Data Mining. The Informatics (Data Mining and Computational Taxonomy), is always the original objective of our researches.Eje: Ingeniería de Software y Base de DatosRed de Universidades con Carreras en Informática (RedUNCI

A general treatment of dynamic constraints

This paper introduces a general, formal treatment of dynamic constraints, i.e., constraints on the state changes that are allowed in a given state space. Such dynamic constraints can be seen as representations of "real world" constraints in a managerial context. The notions of transition, reversible and irreversible transition, and transition relation will be introduced. The link with Kripke models (for modal logics) is also made explicit. Several (subtle) examples of dynamic constraints will be given. Some important classes of dynamic constraints in a database context will be identified, e.g. various forms of cumulativity, non-decreasing values, constraints on initial and final values, life cycles, changing life cycles, and transition and constant dependencies. Several properties of these dependencies will be treated. For instance, it turns out that functional dependencies can be considered as "degenerated" transition dependencies. Also, the distinction between primary keys and alternate keys is reexamined, from a dynamic point of view.

How can graph databases and reasoning be combined and integrated?

Nowadays the graph data model has been accepted as one of the most suitable data models to formalize relationships among entities of many domains. Deductive databases based on the Datalog language have been used to deduce new information from large amounts of data. Most of the attempts to combine logic and graph databases are based on translating knowledge in graph databases into Datalog and then use its inference engine. We aim to open the discussion about combining graph databases and a graph-oriented logic to define «native» deductive graph databases. This is, graph databases equipped with an inference mechanism based on graph based logic. To be concrete, we plan to use the recently introduced graph navigational logic.Peer ReviewedPostprint (published version

Justification for inclusion dependency normal form

Functional dependencies (FDs) and inclusion dependencies (INDs) are the most fundamental integrity constraints that arise in practice in relational databases. In this paper, we address the issue of normalization in the presence of FDs and INDs and, in particular, the semantic justification for Inclusion Dependency Normal Form (IDNF), a normal form which combines Boyce-Codd normal form with the restriction on the INDs that they be noncircular and key-based. We motivate and formalize three goals of database design in the presence of FDs and INDs: noninteraction between FDs and INDs, elimination of redundancy and update anomalies, and preservation of entity integrity. We show that, as for FDs, in the presence of INDs being free of redundancy is equivalent to being free of update anomalies. Then, for each of these properties, we derive equivalent syntactic conditions on the database design. Individually, each of these syntactic conditions is weaker than IDNF and the restriction that an FD not be embedded in the righthand side of an IND is common to three of the conditions. However, we also show that, for these three goals of database design to be satisfied simultaneously, IDNF is both a necessary and sufficient condition

Computer Aided Design for Soil Classification Relational Database and Retrieval Techniques

The paper focuses on the problems associated with classification, storage and retrieval of information on soil data, such as the incompatibility of soil data semantics; inadequate documentation, and lack of indexing; hence it is pretty difficult to efficiently access large database. Consequently, information on soil is very difficult to retrieve hence, modification and update of soil data become very difficult. The relations supported by the system for the purpose of storage and retrieval of soil classification are outlined and translated into graphical presentation. The paper also presents algorithms showing the procedure for generating various soil classifications, retrieval techniques for efficient and quick retrieval of information on soil data. African Research Review Vol. 1 (2) 2007: pp. 141-15

Philosophy of Data (PoD) and its Importance to the Discipline of Information Systems

In this document, we explore the Philosophy of Data (PoD) and its roots amongst other disciplines. The Philosophy of Data seeks to understand the nature of data through experimental philosophy. In order to understand the many different ontologies of data, information, and knowledge out there, this paper will describe part of the problem space in terms of other disciplines and make an argument for the establishment of this new philosophical field. Furthermore, we will show how the PoD is very important to IS scholars and practitioners

The archaeological database—New relations?

Over two decades have passed since the foundations of the relational data model were formalised (Codd 1970) and today a large number of Database Management Systems (DBMS) based on its principles are readily available. The better of these have attained a high degree of sophistication, running in a variety of environments — micros, workstations, minis and mainframes — and have achieved some standardisation through the adoption of Standard (or Structured) Query Language (SQL). As such, the user who invests much time in learning to use a DBMS and its development tools, for example INGRES, will have little problem when the present micro is dumped and a workstation appears on the desk. More importantly for archaeological information, the data, its structure, and application programs will also transfer with minimal upheaval. This is a salutary warning to those investing a great deal of resources in non-upwardly mobile micro-based DBMS and they are urged to consider employing either ORACLE or INGRES (the current flagships of the 4th generation language multi- environment relational DBMS) if they wish to ensure the longevity of their work. The reference to work rather than just to data is deliberate and the cornerstone of this paper, for information is not just data values; it is the context and meaning of those values that ultimately determine the usefulness of the data. Data structure, user interfaces, validation procedures, help systems and applications are inextricably linked with the raw data, giving it context and providing a crude but non-trivial 'knowledge base' without which data files may be useless, or even a negative resource, if misunderstood. Although high-quality relational DBMS did not come into general use as commercial products until the late 1980s, deficiencies in the relational model had already been noted in the previous decade. Important new products are likely to become generally available soon. Many of the major research areas of general DBMS have direct application in the management of archaeological data. The aim of this paper is to discuss some of the limitations and deficiencies of currently available relational DBMS, to review informally the most relevant areas of development (and one area which has yet to be developed), and to consider the implications for mainstream archaeology