Logical Database Research Articles

Algorithms and Support for Horizontal Class Partitioning in Object-Oriented Databases

Horizontal partitioning is a logical database design technique which facilitates efficient execution of queries by reducing the irrelevant objects accessed. Given a set of most frequently executed queries on a class, the horizontal partitioning generates horizontal class fragments (each of which is a subset of object instances of the class), that meet the queries requirements. There are two types of horizontal class partitioning, namely, primary and derived. Primary horizontal partitioning of a class is performed using predicates of queries accessing the class. Derived horizontal partitioning of a class is the partitioning of a class based on the horizontal partitioning of another class. We present algorithms for both primary and derived horizontal partitioning and discuss some issues in derived horizontal partitioning and present their solutions. There are two important aspects for supporting database operations on a partitioned database, namely, fragment localization for queries and object migration for updates. Fragment localization deals with identifying the horizontal fragments that contribute to the result of the query, and object migration deals with migrating objects from one class fragment to another due to updates. We provide novel solutions to these two problems, and finally we show the utility of horizontal partitioning for query processing.

Enhancing the ER Model with Integrity Methods

Entity Relationship (ER) schemas include cardinality constraints, that restrict the dependencies among entities within a relationship type. The cardinality constraints have direct impact on application transactions, since insertions or deletions of entities or relationships might affect related entities. Application transactions can be strengthened to preserve the consistency of a database with respect to the cardinality constraints in a schema. Yet, once an ER schema is translated into a logical database schema, the direct correlation between the cardinality constraints and application transaction is lost, since the components of the ER schema might be decomposed among those of the logical database schema. We suggest to extend the Enhanced ER (EER) data model with integrity methods that take the cardinality constraints into account. The integrity methods can be fully defined by the cardinality constraints, using a small number of primitive update methods, and are automatically created for a given EER diagram. A translation of an EER schema into a logical database schema can create integrity routines by translating the primitive update methods alone. These integrity routines may be implemented as database procedures, if a relational DBMS is utilized, or as class methods, if an objectoriented DBMS is utilized.

Handling complex and uncertain information in the ExIFO and NF/sup 2/ data models

Trends in databases leading to complex objects present opportunities for representing imprecision and uncertainty that were difficult to integrate cohesively in simpler database models. In fact, one can begin at the conceptual level with a model that allows uncertainty assumptions and then transform those assumptions into a logical model having the necessary semantic foundations upon which to base a meaningful query language. Here we provide such a constructive approach beginning with the ExIFO model for expression of the conceptual design then show how the conceptual design is transformed into the logical design (for which we utilize the extended NF/sup 2/ logical database model). The steps are straightforward, unambiguous, and preserve the relevant information, including information concerning uncertainty.

Uncertainty in a nested relational database model

Some database models have already been developed to deal with complex values but they have constrains that data stored is precise and queries are crisp. However, as many researchers have pointed out, there is a need to present, manipulate, and query complex and uncertain data of various non-traditional database applications such as oceanography, multimedia, meteorology, office automation systems, engineering designs, expert database systems and geographic information systems. In this paper, we present a logical database model, which is an extension of a nested relational data model (also known as an NF 2 data model), for representing and manipulating complex and uncertain data in databases. We also introduce a possible physical representation of such complex and uncertain values in databases and describe the query processing of the model that we discuss here.

Spirality and Optimal Orthogonal Drawings

We deal with the problem of constructing the orthogonal drawing of a graph with the minimum number of bends along the edges. The problem has been recently shown to be NP-complete in the general case. In this paper we introduce and study the new concept of spirality, which is a measure of how an orthogonal drawing is rolled up, and develop a theory on the interplay between spirality and number of bends of orthogonal drawings. We exploit this theory to present polynomial time algorithms for two significant classes of graphs: series-parallel graphs and 3-planar graphs. Series-parallel graphs arise in a variety of problems such as scheduling, electrical networks, data-flow analysis, database logic programs, and circuit layout. Also, they play a central role in planarity problems. Furthermore, drawings of 3-planar graphs are a classical field of investigation.

An architecture for a parallel disjunctive deductive database system

Parallel database systems are designed to handle data-intensive and logic-intensive queries. Disjunctive deductive databases (DDDB) — logic databases which allow for indefinite, or partial information - must handle such queries at the extreme. Therefore, a parallel architecture would be ideal for implementing a DDDB. This paper presents a brief description of a non-parallel DDDB, a prototype of which has been implemented at the University of Maryland, along with its query processing algorithm. The main design issues in parallel relational database architectures that are applicable to disjunctive databases are then reviewed. Finally, we investigate the sources of parallelism in DDDB and present a potential architecture for a parallel DDDB system.

Datalog with non-deterministic choice computes NDB-PTIME

This paper addresses the issue of non-deterministic extensions of logic database languages. After providing a brief overview of the main proposals in the literature, we concentrate on the analysis of the dynamic choice construct from the point of view of the expressive power. We show how such construct is capable of expressing several interesting deterministic problems, such as computing the complement of a relation, and non-deterministic ones, such as computing an ordering of a relation. We then prove that Datalog augmented with the dynamic choice expresses exactly the non-deterministic time-polynomial queries. We thus obtain a complete characterization of the expressiveness of the dynamic choice, and conversely achieve a characterization of the class of non-deterministic time-polynomial queries (NDB-PTIME) by means of a simple, declarative, and efficiently implementable language.

A visual object-relationship query language for user–database interaction

User–database interaction has a direct and immediate effect on the effectiveness and efficiency of database end users. Traditional query languages like SQL and QBE require end users to understand the underlying data structure in the database. This is a burden on end users, especially novice end users who have little technical knowledge or understanding of database. To alleviate the need for end users to know the logical database organization, this paper proposes the use of an object–relationship (OR) model and a formal high-level visual query language as the interface. Using this interface, end users communicate only domain knowledge with the system without the need to specify the storage structure or search strategies. The end users deal only with the conceptual model of the database and not the actual physical implementation of the database. To demonstrate the expressive power of the visual query language, this paper also provides a proof to show that it is relationally complete and hence is as powerful as traditional languages such as SQL.

Verification and Transformation of Complex and Uncertain Conceptual Schemas

In database environment, it is necessary to represent complex and uncertain information at conceptual level and then transform the conceptual schema into the logical one for ultimate implementation. It is also important to verify the conceptual schema with respect to the constraints imposed on the schema definition. In this paper we primarily focus on the verification and transformation of the conceptual schema. For the purpose of verification of the conceptual schema represented by the ExIFO data model (the extension of the IFO data model), we introduce a number of invariants. We also describe the transformation algorithm for mapping the conceptual specification into a logical database schema represented with the extended NF 2 database model. The system that we describe in this paper is implemented and it can test whether the given ExIFO specification is valid and transforms the conceptual specification into the logical schema. The transformation algorithm is computationally efficient and preserves the knowledge represented with verified conceptual schema.

A logical notion of conditional independence: properties and applications

We propose a notion of conditional independence with respect to prepositional logic and study some of its key properties. We present several equivalent formulations of the proposed notion, each oriented towards a specific application of logical reasoning such as abduction and diagnosis. We suggest a framework for utilizing logical independence computationally by structuring a propositional logic database around a directed acyclic graph. This structuring explicates many of the independences satisfied by the underlying database. Based on these structural independences, we develop an algorithm for a class of structured databases that is not necessarily Horn. The algorithm is linear in the size of a database structure and can be used for deciding entailment, computing abductions and diagnoses. The presented results are motivated by similar results in the literature on probabilistic and constraint-based reasoning.

On the expressive power of F-logic language

F-logic language is a logic database language based on frame logic. It is powerful in expressing object-oriented features. However, there was little work discussing its capability of manipulating complex objects. In this paper, the authors compare the capability of F-logic with that of logic database languages represented by COL. Through two pairs of semantic-preserving transformations, F-logic programs and their Herbrand interpretations can be transformed into COL programs and their corresponding Herbrand interpretations, and vice versa. Also, the effects of negation are discussed. The results of this paper indicate that, without consideration of the effects of OID generating, F-logic language has the same power in manipulating complex objects as COL, LDL1, and ELPS.

The Effect of User View Characteristics on Database Design Performance of Novices

Database design is a complex task for end users and novice designers. User views are an excellent input source for database design. This research investigates the effect of certain characteristics of user views on designer performance in the logical database design task. The study examines the extent to which performance of nonexpert designers engaged in normalizing user views and eliminating derived relationships can be predicted by examining the structure of user views. Two constructs that capture the complexity of a user view are defined - degree of nesting and derivation span. User views which varied on these parameters were included in a case. Subjects, who were enrolled in a database class and had learned the view decomposition approach, were asked to conduct logical database design of the case. Each view was graded using a predefined scheme. For each subject, there was a set of scores obtained for each user view. A multiple regression analysis using scores as the dependent variable indicated that both independent variables - degree of nesting and derivation span - significantly explained designer performance in normalizing the user views. Further, subjects had considerable difficulty in detecting derived relationships. The findings suggest that the degree of nesting and derivation distance cause complexity in database design tasks and lower designer performance.

Cultural development in La Florida

In contrast to the rather exciting and somewhat colorful exploits that took place during the ini tial period of colonization, the middle period of Spanish settlement was not a time of world changing events. The experimental and conquest phase of colonization had drawn to an end, ef fective adaptations had been worked out, and basic cultural patterns had already been estab lished. Consequently, Spanish America during the late 16th and 17th centuries has often been characterized as an "inwardly pulsating" time of relative stability and embellishment of preexist ing patterns (Leonard 1959:viii). A general con sensus exists among historians that this period of Spanish-American cultural development was one in which the basic framework or pattern estab lished during the initial years of settlement was expanded and became more elaborate. What remains unclear, however, are the pro cesses and their associated archaeological pat terns which characterized that stage of Spanish colonial cultural development between initial settlement and established society. The archaeo logical characterization and synthesis of 17th century St. Augustine provides the material ba sis for considering the forces that influenced the development of a colonial tradition in Spanish Florida during this post-contact phase (Hoffman 1994). In the case of St. Augustine, the multidisciplinary perspective of historical archae ology assumes a particularly significant role in this study because of the unexplored and, at times, "lost" nature of the 17th-century docu mentary record in St. Augustine, and because of its access to a comparatively sizeable archaeo logical database (Figure 1). Perhaps more impor tantly though, historical archaeology also pro vides a glimpse into "everyday life" and the behavior and lives of the common people who represented an essential component of colonial society.

The Complexity of Querying Indefinite Data about Linearly Ordered Domains

In applications dealing with ordered domains, the available data is frequently indefinite. While the domain is actually linearly ordered, only some of the order relations holding between points in the data are known. Thus, the data provides only a partial order, and query answering involves determining what holds under all the compatible linear orders. In this paper we study the complexity of evaluating queries in logical databases containing such indefinite information. We show that in this context queries are intractable even under the data complexity measure, but identify a number of PTIME subproblems. Data complexity in the case of monadic predicates is one of these PTIME cases, but for disjunctive queries the proof is nonconstructive, using well-quasi-order techniques. We also show that the query problem we study is equivalent to the problem of containment of conjunctive relational database queries containing inequalities. One of our result implies that the latter isΠp2-complete, solving an open problem of Klug (J. Assoc. Comput. Mach.35, No. 1 (1988), 146–160).

Verifying local stratifiability of logic programs and databases II

We continue investigating ways of verifying local stratifiability of logic programs and databases. In a previous paper, we established a necessary and sufficient condition for local stratifiability of logic programs and databases and proposed an interactive procedure for performing the verification. In this paper, we extend our earlier work. We present a characterization of an infinite extending path and develop a non-interactive procedure for testing for local stratifiability of logic programs and databases. Although the unerlying problem is undecidable in general, our method proves to be powerful to treat a majority of logic programs and databases.

Automatic Processes in Database Building and Subsequent Automatic Abstractions

One of the difficulties in building an effective system for spatial and attribute generalization is the predominance of the conventionally based generalization paradigm. This is exemplified by numerous attempts at reproducing rules derived from manual environments and re-building them in a GIS or CIS. What is often lacking is an understanding of what generalization achieves in its various forms. There is no doubt that the representation issue in generalization is of critical importance, since it is through the representation that we communicate visually. However, with access to databases and high-level programming tools, the quality, consistency, and reliability of the information warrants far greater emphasis than has been given in the past. Re-addressing generalization from a database perspective shifts the focus in model development from cartographic representation issues to geographic information. However, doing so places demands on operational mapping organizations for database building, data classification, and subsequent feature coding. Recently, techniques have been developed to automatically classify, code, and build databases. Since the impediment to generalization has rested partially in establishing a logical database, the approach discussed in this chapter is to identify techniques that allow users to create the database automatically, without having to code the features interactively. Three different data sets being used for experimentation include hydrography, transportation networks, and land-cover. The models differ somewhat, given the nature of the object categories. Hydrographic and transportation-network features can be classified and coded using a rule base and graph theory, while land cover can be handled using classification and aggregation hierarchies. The objective of this research is to load unclassified categories of features, derive a series of classifications automatically, build a database automatically, and subsequently generalize the data using the derived database to any smaller scale of representation. The objective of this chapter is to present the methodologies required to achieve the research goals and to illustrate the results.

Logical data modelling for geographical applications

Abstract. A formal, yet practical, GeoRelational Data Model (GRDM) is presented for the logical database design phase of the development of spatial information systems. Geographic applications are viewed in the context of information systems development. The generic needs of modelling spatial data are analyzed; it is concluded that they are not served satisfactorily by existing data models, so specifications of modelling tools for spatial application design are given. GRDM provides a set of representational constructs (relations and layers for the logical schema; virtual layers, object classes and spatial constraints for the user views) on top of well-established models. It constitutes part of a full, easily automated application design methodology. Extensive examples demonstrate the relevance, and ease-of-use of the platform-independent GRDM.

Computer support for protocol-based treatment of cancer

Cancer treatment is often carried out within protocol-based clinical trials. An oncology clinic may take part in many trials each of which requires data to be collected for monitoring efficacy and toxicity of treatment. Subsequently, these data are analyzed statistically to evaluate clinical objectives of the trial. To be scientifically valid, such analysis must be based on data that are both complete and correct. This is one motivating factor for introducing computer support for trial management. Further motivation is provided by concern that treatment is consistent with the protocl and the well-being of the patient. The complexity of many protocols, the life-threatening nature of cancer, and the toxicity of treatment side effects emphasize the safety-critical nature of oncology. The OaSiS system provides decision support for the protocol- based treatment of cancer patients with emphasis on the safety aspects of the advice it gives. It offers a graphical and spreadsheet-style interface, employs integrity constraint checking techniques from logic database to monitor compliance with a protocol, and is implemented in PROLOG. This paper describes the main features of OaSiS and indeicates work in progress and planned research.

Undecidable boundedness problems for datalog programs

A given Datalog program is bounded if its depth of recursion is independent of the input database. Deciding boundedness is a basic task for the analysis of database logic programs. The undecidability of Datalog boundedness was first demonstrated by Gaifman et al. [7]. We introduce new techniques for proving the undecidability of (various kinds of) boundedness, which allow us to considerably strengthen the results of Gaifman et al. [7]. In particular, (1) we use a new generic reduction technique to show that program boundedness is undecidable for arity 2 predicates, even with linear rules; (2) we use the mortality problem of Turing machines to show that uniform boundedness is undecidable for arity 3 predicates and for arity 1 predicates when ≠ is also allowed; (3) by encoding all possible transitions of a two-counter machine in a single rule, we show that program (resp., predicate) boundedness is undecidable for two linear rules (resp., one rule and a projection) and one initialization rule, where all predicates have small arities (6 or 7).

Extending Datalog with arrays

In this paper the problem of extending the logic database language Datalog with primitives to support array definitions and manipulations is addressed. The syntax and the semantics of this language, called Datalog A , are given by showing that model theoretic properties of ordinary Datalog extend to Datalog A . Datalog A fixpoint semantics and its implementation are also studied and presented. Sufficient conditions assuring program evaluation convergence when manipulating real-valued arrays are finally discussed.