A data model, called the entity-relationship model, is proposed. This model incorporates some of the important semantic information about the real world. A special diagrammatic technique is introduced as a tool for database design. An example of database design and description using the model and the diagrammatic technique is given. Some implications for data integrity, infor-mation retrieval, and data manipulation are discussed. The entity-relationship model can be used as a basis for unification of different views of data: t,he network model, the relational model, and the entity set model. Semantic ambiguities in these models are analyzed. Possible ways to derive their views of data from the entity-relationship model are presented. Key Words and Phrases: database design, logical view of data, semantics of data, data models, entity-relationship model, relational model, Data Base Task Group, network model, entity set

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Terminological Knowledge Representation Systems (TKRSs) are tools for designing and using knowledge bases that make use of terminological languages (or concept languages). The TKRS we consider in this paper is of practical interest since it goes beyond the capabilities of presently available TKRSs. First, our TKRS is equipped with a highly expressive concept, language, called ALCNR, including general complements of concepts, number restrictions and role conjunction. Second, it allows one to express inclusion statements between general concepts, in particular to express terminological cycles. We provide a sound, complete and terminating calculus for reasoning in ALCNR-knowledge bases based on the general technique of constraint systems.

SDM is a high-level semantics-based database description and structuring formalism (database model) for databases. This database model is designed to capture more of the meaning of an application environment than is possible with contemporary database models. An SDM specification describes a database in terms of the kinds of entities that exist in the application environment, the classifications and groupings of those entities, and the structural interconnections among them. SDM provides a collection of high-level modeling primitives to capture the semantics of an application environment. By accommodating derived information in a database structural specification, SDM allows the same information to be viewed in several ways; this makes it possible to directly accommodate the variety of needs and processing requirements typically present in database applications. The design of the present SDM is based on our experience in using a preliminary version of it. SDM is designed to enhance the effectiveness and usability of database systems. An SDM database description can serve as a formal specification and documentation tool for a database; it can provide a basis for supporting a variety of powerful user interface facilities, it can serve as a conceptual database model in the database design process; and, it can be used as the database model for a new kind of database management system.

A database design methodology is defined for the design of large relational databases. First, the data requirements are conceptualized using an extended entity-relationship model, with the extensions being additional semantics such as ternary relationships, optional relationships, and the generalization abstraction. The extended entity-relationship model is then decomposed according to a set of basic entity-relationship constructs, and these are transformed into candidate relations. A set of basic transformations has been developed for the three types of relations: entity relations, extended entity relations, and relationship relations. Candidate relations are further analyzed and modified to attain the highest degree of normalization desired. The methodology produces database designs that are not only accurate representations of reality, but flexible enough to accommodate future processing requirements. It also reduces the number of data dependencies that must be analyzed, using the extended ER model conceptualization, and maintains data integrity through normalization. This approach can be implemented manually or in a simple software package as long as a “good ” solution is acceptable and absolute optimality is not required.

The article aims at establishing a logical approach to class-based data modeling. After a discussion on class-based formalisms for data modeling, we introduce a family of logics, called Description Logics, which stem from research on Knowledge Representation in Arti cial Intelligence. The logics of this family are particularly well suited for specifying data classes and relationships among classes, and are equipped with both formal semantics and inference mechanisms. We demonstrate that several popular data modeling formalisms, including the Entity-Relationship Model, and the most common variants of object-oriented data models, can be expressed in terms of speci c logics of the family. For this purpose we use a unifying Description Logic, which incorporates all the features needed for the logical reformulation of the data models used in the various contexts. We also discuss the problem of devising reasoning procedures for the unifying formalism, and show that they provide valuable supports for several important data modeling activities.

The notion of class is ubiquitous in computer science and is central in many formalisms for the representation of structured knowledge used both in knowledge representation and in databases. In this paper we study the basic issues underlying such representation formalisms and single out both their common characteristics and their distinguishing features. Such investigation leads us to propose a unifying framework in which we are able to capture the fundamental aspects of several representation languages used in different contexts. The proposed formalism is expressed in the style of description logics, which have been introduced in knowledge representation as a means to provide a semantically well-founded basis for the structural aspects of knowledge representation systems. The description logic considered in this paper is a subset of first order logic with nice computational characteristics. It is quite expressive and features a novel combination of constructs that has not been studied before. The distinguishing constructs are number restrictions, which generalize existence and functional dependencies, inverse roles, which allow one to refer to the inverse of a relationship, and possibly cyclic assertions, which are necessary for capturing real world

ion/Subsumption, has been broadly exploited in actual systems (see Kindermann 1990, Quantz and Kindermann 1990, Nebel 1990a). The Abstraction/Subsumption idea is applicable to a number of languages. However, there are cases where, in order to check whether \Sigma j= D(a), it is necessary to consider assertions about other objects in the knowledge base different from a, and the above method is no longer applicable. We discuss these cases in Sections 4.2 and 4.3. Subsequently, we show in Section 4.4 how to enrich concept languages with an epistemic operator, so as to distinguish the knowledge about the world and knowledge about the state of the knowledge base. In particular, we demonstrate that the epistemic operator introduces a sophisticated query mechanism that can be used to decrease the complexity of Instance Checking. 4.1 Complexity Measures The complexity of a problem is generally measured with respect to the size of its whole input. For instance, in Section 3 the complexity of...

The set-height of a complex object type is defined to be its level of nesting of the set construct. In a query of the complex object calculus which maps a database D to an output type T,anintermediate type is a type which is used by some variable of the query, but which is not present in D or T.Foreachk, i ≥ 0 we define CALCk,i to be the family of calculus queries mapping from and to types with set-height ≤ k and using intermediate types with set-height ≤ i. In particular, CALC0,0 is the classical relational calculus, and CALC0,1 is equivalent to the family of secondorder (relational) queries. Several results concerning these families of languages are obtained. A primary focus is on the families CALC0,i, which map relations to relations. Upper and lower bounds in terms of hyper-exponential time and space on the complexity of these families are provided. The CALC0,i hierarchy does not collapse with respect to expressive power. The union ∪0≤iCALC0,i is exactly the family of elementary queries, i.e., queries with hyper-exponential complexity. The expressive power of queries from the complex object calculus interpreted using semantics based on the use of arbitrarily large finite or infinite set of invented values is studied. Under these semantics, the expressive power of the relational calculus is not increased, and the CALC0,i hierarchy collapses at CALC0,1. In general, queries with these semantics may not be computable. We also consider an alternative semantics which yields a family of queries equivalent to the computable queries. 1

We review basic premises underlying the application of conceptual modelling to the development of information systems and point out a fundamental problem arising from the broad range of concepts that need to be modelled. We then argue that conventional conceptual models are weak for such broad domains of discourse because they come with built-in collections of primitive notions in terms of which conceptual modelling is to be done. Telos is then introduced as a conceptual modelling language designed for capturing knowledge about information systems and it is argued that, unlike its peers, it offers facilities not only for modelling an application but also the notions used to model an application. The presentation of features of the language is eclectic and generally non-technical. Details about Telos can be found in [Mylopoulos90] and [Koubarakis89].