Association-Oriented Database Model — n-ary Associations

Cybernetics and Systems Analysis, 1996

The present article discusses the foundations of the relational approach to database models, which goes back to Codd's work [1-6] (see also surveys [i-9] and monographs [10-16]). The state of the art in this area of research is characterized by a large number of scattered results. Further progress is constrained by three missing components: a unified methodological and conceptual base, formalization of the main paradigms, and an understanding of the interrelationships between the corresponding formalizations. The next stage in the development of relational databases thus should involve a shift of emphasis from extensional to intensional approach to the subject. Certain steps in this direction are presented in our paper, whose goal can be summarized as follows: use the principles of programmology developed in the framework of composition programming [ 17-20] to provide adequate formalizations of the main paradigms for the construction of a substantive theory of relational databases while remaining on a sufficiently high level of abstraction. Database models, and in particular relational models, have at least two major aspects: the information aspect associated with formalization of data structures, and the manipulation aspect, associated with formalization of operations on these structures. Joint formalization of these aspects reduces to the construction of a corresponding algebra of data structures. Relation is the key concept of the relational approach to databases, and it is therefore the first that must be formalized. Like any natural intuitive concept, the database relation potentially admits a variety of different formalizations. The first formalization of database relation, following Codd, was the classical view of a finite-place logical relation as a subset of the Cartesian product of sets taken in a certain order (in other words, a relation is a set of ordered n-tuples of fixed length, n = I, 2 ....). This formalization was in fact responsible for the initial success and popularity of the relational approach to databases. Indeed, informal concepts could be formalized and analyzed using a well-developed formal apparatus (theory of logical relations, fragments of languages of first-order predicate logic, etc.). Yet even this traditionally established formalization of the concept of database relation is not free from weaknesses, which lead to a number of irrelevancies. These irrelevancies include the following: first, the information content of a database relation is usually independent of the order of the components, whereas for logical relations this order is essential (thus, for instance, it is not always meaningful to consider the inverse of a given database relation, by analogy with the concept of symmetry); second, the use of standard names l, 2 .... to access the components of a database relation (tuples in this case) is quite burdensome and leads to certain complications, such as the appearance in the metalanguage, but not in the object language, of arbitrary ("mnemonic") names denoting the standard names; moreover, with the exception of set-theoretical operations, the only natural many-place operation on database relations under this formalization is the so-called Cartesian product (not to be confused with the eponymous set-theoretical operatioi,), and all other natural operations (for instance, 0-join) are introduced as parametric operations on the standard names of the components. Also note the following typical twist: the operation of multiplication of (binary) logical relations, which is the core of relational algebra (see, for instance, [21-23]), does not play the same role for the general case of database relations, but it is of course simulated by the 0-join with ordinary equality acting as the parameter 0. No less important is the fact that the common database management systems (DBMS) are not strictly relational in the sense of the above formalization, because they admit arbitrary component names (see, e.g., [24]).

Information and Software Technology, 1996

Object Relationship Notation (ORN) allows relationship semantics to be specified to an object database management system (ODBMS) when relationships are represented as object-valued class attributes, both singly and multiply valued. Other declarative schemes have been proposed or developed to define semantics for such relationships when they are represented as foreign keys in a relational database or as relations in an extended object data model. In this paper we give an overview of ORN and compare it to these other schemes as well as to the declarative capabilities that currently exist for defining relationships in commercial ODBMSs. The purpose of our comparison is to permit the relative merits of ORN to be appreciated and to underscore the need for such a notation in ODBMSs.

Encyclopedia of Database Technologies and Applications, 2005

The relational data model is the dominant paradigm in the commercial database market today, and it has been for several years. However, there have been challenges to the model over the years, and they have influenced its evolution and that of database technology. The object-oriented revolution that got started in programming languages arrived to the database area in the form of a brand new data model. The relational model managed not only to survive the newcomer but to continue becoming a dominant force, transformed into the object-relational model (also called extended relational, or universal) and relegating object-oriented databases to a niche product. Although this market has many nontechnical aspects, there are certainly important technical differences among the mentioned data models. In this article I describe the basic components of the relational, object-oriented, and object-relational data models. I do not, however, discuss query language, implementation, or system issues. ...

The present development in the database area is highly influenced by the object-oriented principles of data modeling. On the contrary to the previously successful relational approach, it lacks rigorous theoretical support. This problem is mainly due to the fact that the semantics description of such features as generalization, specialization, encapsulation, and inheritance is not trivial by using just the means of the set theory. Therefore, many researchers focused on finding suitable theoretical means for the modeling of complex objects. This paper is concerned with the comparison of categorical modeling in the database area and proposes a limit data model that enables to represent the objects, relationships, multiple inheritance, class polymorphism and virtual methods in the categorical setting. The aim to formalize these notions arose from the actual need. We would like to use it to support the development of an object-oriented database model closely following the standard ODMG&#...

2014

The concepts of object oriented data models aim towards modeling of application objects close to the user's view. Yet developers of applications relying on object oriented database management systems are facing problems resulting from the limitations of object oriented data models to describe adequately the full range of possible associations between objects and between processes. This paper focuses on the conceptual data modeling needs of object oriented database applications, and proposes an object+relationship model, ERC+, which meets database application requirements by merging traditional semantic data models features with object oriented capabilities such as structural object orientation, inheritance, and object identity. It is an extended entity-relationship model specifically designed to support complex object description and to allow multiple perceptions of objects. The ERC+ model provides the foundations for an integrated environment of tools called SUPER that has bee...

Iberamia, 2002

Semantic relations between concepts or data are common modelling devices in various knowledge representation approaches. Fuzzy relations can be defined as fuzzy subsets of the cartesian product of a number of domains, extending the notion of crisp relation. Associations in object-oriented modelling -and more specifically in the Unified Modelling Language -can be interpreted as crisp relations on the classifiers they connect, and thus the concept of association can be extended to its fuzzy counterpart by representing a fuzzy relation on the classes involved in the association. In this paper, the resolution form of a fuzzy relation is described as a convenient way to represent fuzzy associations in objectoriented programming languages, thus enabling an efficient practical representation mechanism for them. Specific cases of fuzzy relations can also be dealt with by adding semantic constraints to fuzzy associations. One of the most interesting cases is that of similarity relations, which essentially generalize the notion of object equality to the fuzzy case. Fuzzy relations can be stored in orthogonally persistent object databases by using the described fuzzy association design, as illustrated in this paper with a case study that uses the db4o persistence engine.

Concurrency and Computation: Practice and Experience, 2003

A semantic relationship is a data modeling construct that connects a pair of classes or categories and has inherent constraints and other functionalities that precisely reflect the characteristics of the specific relationship in an application domain. Examples of semantic relationships include part-whole, ownership, materialization, and role-of. Such relationships are important in the construction of information models for advanced applications, whether one is employing traditional data modeling techniques, knowledge-representation languages, or object-oriented modeling methodologies. This paper focuses on the issue of providing built-in support for such constructs in the context of object-oriented database (OODB) systems. Most of the popular object-oriented modeling approaches include some semantic relationships in their repertoire of data modeling primitives. However, commercial OODB systems, which are frequently used as implementation vehicles, tend not to do the same. We will present two frameworks by which a semantic relationship can be incorporated into an existing OODB system. The first only requires that the OODB system support manifest type with respect to its instances. The second assumes that the OODB system has a special kind of metaclass facility. The two frameworks are compared and contrasted. In order to ground our work in existing systems, we show the addition of a part-whole semantic relationship both to the ONTOS DB/Explorer OODB system and the VODAK Model Language (VML).

Journal of Database Management, 1993

Deep Science Research, 2025

When implemented according to the model proposed by E. F. Codd in 1970, databases and their management systems are said to be relational, hence the term relational model. Codd showed that relational databases have significant advantages over previous hierarchical and network models. Relational modelling is the foundation of relational databases. It provides the basis for a high-level data language that can be used both by end users and by application developers and also supports the design of user views.

The object relational data model [1,2,3] takes advantage of Codd's relational calculus power [5] and the object concept characteristics [6,7,11]. In fact, two major approaches have been adopted to satisfy the designers and users of the advanced databases. A revolutionary approach [3,7,13,15] which integrates the object characteristics into the new data models and where the specification of data constraints and the definition of interrogation language are considered as important research problems. The second one [2,22,24,48], called evolutionary approach, consists in preserving Codd's data model when being enriched by adequate concepts for the coverage of current applications in database. In this approach and compared with studies presented by Melton [18] and quoted by Gardarin [4], Date and Darwen have proposed in [1,2] the foundations of the object relational model. So, an algebra A consisted of first order logic operators has been defined to express various classes of querys in object relational database. This paper presents an extension of object relational model [1,2] to new types generated by operators.These operators, called Op, offer a means to specify domains as functions and allow consequently the increasing of data model expressivness. Concerning data query language, or more precisely the logical data calculation, the algebra A [1] is adapted and extended, giving A*, to support this extension of object relational model. Algebra A* contains algebraic operators which are able to support this new extension. Furthermore, to enhance the object relational model, the query language ERA* that implements A*, consists essentially in both logical calculation operators and new algebraic operators.