Specific Data Model Research Articles

Modélisation logique des données dans les systèmes multidimensionnels d'aide à la décision: la méthode MAP

ABSTRACT Among the tools available to the designers of Decision Support Systems (DSS) and Executive Information Systems (EIS), there are generators, ad—hoc systems, groupware and end—user products based on fourth—generation languages. Most of these tools are characterized by a logical structure based on the use of multidimensional tables. These DSS and EIS softwares permit to define the structure of the database and to manipulate it in a user—friendly fashion with an exceptionally short response time. They are based on a specific logical data model, consisting of dimension, variable and relationship concepts. Based on the OLAP technology (One Line Analytical Processing), these tools allow to express multidimensional views using the client—server architecture. Starting from a real situation, the designers of DSS and EIS often have difficulty in defining directly the dimensions, variables and relationships. To solve this problem, we suggest to proceed in two steps. The first step consists in modelling at the conceptual level, using the extended entity—relationship approach. The second step aims at moving to the logical level, by means of transformation rules. To this end, we present an algorithm which transforms a conceptual schema into a logical schema based on the objects of the multidimensional model. We illustrate the use of the transformation rules by means of an example and present the tool associated with the method.

Extending existing dependency theory to temporal databases

Normal forms play a central role in the design of relational databases. Several normal forms for temporal relational databases have been proposed. These definitions are particular to specific temporal data models, which are numerous and incompatible. The paper attempts to rectify this situation. We define a consistent framework of temporal equivalents of the important conventional database design concepts: functional dependencies, primary keys, and third and Boyce-Codd normal forms. This framework is enabled by making a clear distinction between the logical concept of a temporal relation and its physical representation. As a result, the role played by temporal normal forms during temporal database design closely parallels that of normal forms during conventional database design. These new normal forms apply equally well to all temporal data models that have timeslice operators, including those employing tuple timestamping, backlogs, and attribute value timestamping. As a basis for our research, we conduct a thorough examination of existing proposals for temporal dependencies, keys, and normal forms. To demonstrate the generality of our approach, we outline how normal forms and dependency theory can also be applied to spatial and spatiotemporal databases.

Foreign direct investment and income inequality: Further evidence

This paper examines the relationship between foreign direct investment (FDI) and income inequality. Special attention has been paid to data comparability and model specification. By comparing models with and without geographical dummies, this study shows that: the statistically significant correlation between FDI and income inequality widely obtained in earlier studies might capture more of the geographical difference in inequality than the deleterious influence of FDI, and to the extent that FDI does give rise to more unequal income distribution in the host less-developed countries (LDCs), only East/Southeast Asia, LDCs appear to have been harmed by the inflow of FDI during the 1970s. It should be noted, however, that the second result refers only to the marginal impact, not the total impact. Apart from FDI, our empirical evidence suggests that the level of economic development, the direct role of government and, to a smaller degree, the significance of the agriculture sector in an LDC are crucial determinants of income inequality.

OO and EER Conceptual Schemas

A database conceptual schema serves as a communication medium between professional analysts/designers and users who wish to comprehend and validate the conceptual schema. The conceptual schema is usually presented in a diagrammatic form that follows a specific semantic data model. The extended entity-relationship (EER) model is one of the most commonly used models, but being “threatened†by the objectoriented (OO) approach, which penetrates into the areas of systems analysis and design, as well as data modeling. The issue of which of the two data models is better for modeling reality and is easier to comprehend is still an open question. Our response to this question was to conduct a controlled experiment in which two groups of users, each trained to use one of the models, were tested for the comprehension of equivalent schema diagrams. Comprehension was measured by the number of correct answers to questions that addressed different constructs of the models. The results of the experiment reveal that there is no significant difference in comprehension of facts dealing with attributes of entities or objects, binary-relationships and two relationships, but those dealing with ternary-relationships are significantly easier to comprehend with the EER model. Comprehension of other, unclassified facts, however, is easier with the OO model. We propose a special symbol for objects representing ternary and higher order relationships in order to overcome the weakness of OO diagrams.

User interfaces and discrete event simulation models

This paper examines features of user interfaces present in current discrete event simulation systems. A particular emphasis is placed on their data input capabilities and the presentation of simulation statistics. There has been a lot of work on developing visual simulation and animation. Little effort appears to have been invested in data input facilities. There has been considerable effort invested in the presentation of simulation results. This paper shows that this distribution of effort into the various interfaces lacks proper insight into the particular needs of simulation systems. A list of features to improve data input and model specification for existing simulation systems is derived. A list of issues that need to be tackled to make the presentation of simulation statistics more appropriate for the specifics of the simulation is given. The paper concludes with general comments concerning future research issues to be addressed.

Integrating fuzzy queries into an existing database management system: An example

In traditional database management systems, queries are intended to retrieve data which satisfy crisp criteria. In some cases, this lack of flexibility leads to empty answers. That is one of the reasons why we have been investigating the extension of these systems so that they become able to support imprecise querying capabilities. In this article, the introduction of imprecise queries in a particular nonrelational system (Information Warehouse) is presented. One of the main interesting aspects of this work resides in the specific data model for which the semantics of fuzzy queries firstly has to be defined. © 1994 John Wiley & Sons, Inc.

Consumer Reaction to Measures of Poor Quality: Evidence from the Mutual Fund Industry

U NLESS quality is apparent at the point of sale, the market must find ways to ensure the delivery of high-quality products; otherwise, producers have incentives to sell low-quality goods at high-quality prices, thereby assuring a degenerate equilibrium.1 Various solutions to this problem have been proposed, most revolving around bonding mechanisms.2 For bonds to work, however, consumers must react to the delivery of less-than-promised quality.3 In general, the faster consumers detect and react to delivery of low-quality products, the more efficient the market is in delivering high-quality products.4 Despite its prominence in the theoretical literature, direct evidence of consumer response to less-than-promised quality is rarely measured. This is a shortcoming presumably attributable to the difficulty of measuring both the difference between expected and actual product quality and

Reciprocity in Superpower Relations: An Empirical Analysis

Past empirical studies of superpower reciprocity have produced inconsistent results that may be traced to several recurrent methodological problems. Correcting these problems, I analyzed statistically the responses of the United States and the Soviet Union to each other's actions over the past forty years. Results were replicated across quasi-experiments using different data sources, time periods, and model specifications. Both superpowers reciprocate each other's actions within a short time frame of up to about two months. Neither responds inversely (for example, by becoming more cooperative following hostile actions by the other). In the 1950s and 1960s U.S. reciprocity following Soviet actions was much more consistent than Soviet reciprocity following U.S. actions, but in the 1970s and 1980s Soviet reciprocity was more consistent than U.S. reciprocity.

Representation of object-oriented data models

Database design tools have been introduced as a means of reducing the expertise required of the designer, to free him or her from the implementation details and to aid in managing the complexity of the design task. However, one of the common shortcomings of database design tools is that they are closely tied to specific data models, thus limiting the applicability of their underlaying concepts and restricting the reusability of the design software. SeaWeed, a component of the Data Model Compiler (DMC) project, proposes a solution by automatically generating database design software from data model specifications. In this paradigm, a data model specification model, or metamodel of data models, is introduced for specifying particular object-oriented data models. Using the knowledge in the specification, conceptual database design software is automatically generated for the given data model. This paper presents a metamodel for object-oriented data models and offers a technique for expressing the semantics of an object-oriented data model in terms of the metaobject types, which consist of attributes, operations, constraints and graphical representations.

Object-oriented data modelling for spatial databases

Data modelling is a critical stage of database design. Recent research has focused upon object-oriented data models, which appear more appropriate for certain applications than either the traditional relational model or the entity-relationship approach. The object-oriented approach has proved to be especially fruitful in application areas, such as the design of geographical information systems which have a richly structured knowledge domain and are associated with multimedia databases. This article discusses the key concepts in object-oriented modelling and demonstrates the applicability of an object-oriented design methodology to the design of geographical information systems. In order to show more clearly how this methodology may be applied, the paper considers the specific object-oriented data model IFO. Standard cartographic primitives are represented using IFO, which are then used in the modelling of some standard administrative units in the United Kingdom. The paper concludes by discussing current r...

Using logic programming for formal specification and validation of data models

Mathematical specifications of data models provide formal means to prove the correctness of the models. Such specifications may be used as prototypes to determined the result of transactions on a database. This paper describes the use of logic programming to mechanize the axiomatization of a proposed extension to the relational data model. The extended model is defined using a many-sorted algebra termed DRE-algebra. The DRE-algebra is then directly implemented in PROLOG. The implementation helps in verifying the correctness of the DRE-algebra and is used as an early prototype to investigate design decisions.

Econometric modelling on microcomputers: A review of major software packages

AbstractIn their present state, both in terms of price and power, microcomputers are taking over applied econometics. Now even model simulation is feasible. This paper tries to help the model‐builder in determining which of the following modelling software is appropriate to his/her specific needs: AREMOS, ESP, Micro‐TSP, MODLER and SORITEC. Tables devoted to data management, estimation, model specification, simulation, and presentation of results, detail the availability of desirable features. Finally, individual short reviews stress the best and worst points of each software.

Disaggregation of the demand for hospital care

textabstractIn this article we want to confront some of the results of the theoretical literature on aggregation with the empirical consequences of aggregation in the context of the analysis of demand for hospital care. There has been an evolution in the estimation of hospital demand functions from macro to micro studies which has resulted in diverging findings. Most studies of aggregate demand at the regional level estimated extremely large effects of hospital bed supply whereas studies based on individual data typically found health status to have a dominant influence on hospital utilization. Very often, comparison of these studies is difficult because different data sources and model specifications have been used. In this article, we will estimate the same demand functions on both the macro and micro level using one data base in order to facilitate comparison. For this purpose, we use data on some 230 000 individuals who are insured with a private health insurance company in the Netherlands. The empirical analysis presented in Section IV is preceded by a discussion of the peculiarities of hospital demand functions (Section II), and by a theoretical examination of the consequences of aggregation (Section III).

Information system analysis and conceptual database design in production environments with M ∗

A methodology, called M ∗, for information system analysis and database design of production environments is presented in detail. The originality of M ∗ is to recognize the importance of integrating factory analysis methods for data and user requirements definition with logical database design methods for database specification. M ∗ is a pragmatic, complete, manual methodology involving three major phases: Enterprise Modelling and Analysis which is the phase devoted to accurate analysis of the structure of the enterprise and precise definition of the scope of the future database application; Conceptual Design which is the phase concerned with data modelling of both static and dynamic properties of the enterprise; and Implementation Design which is the phase dealing with adaptation of the conceptual schema to the data model specifications of the physical database system used for application development and tuning performances of the physical system. The methodology is explained and illustrated by means of an example related to a Flexible Manufacturing System for mechanical parts.

Comparison of four relational data model specifications

This paper reviews four different approaches to specifying the relational data model which are written at about the same time:1. the 'Definition and Formalization of the Relational Data Model' as provided as part of the final ANSI/X3/SPARC/DBSSG Relational Database Task Group Report,2. the 'Relational Database Model Specifications' as submitted to the National Bureau of Standards by the Computer Corporation of America as a draft report in October 1981,3. the 'Formal Definition of the Relational Model' as specified by C. Date of IBM, San Jose, and4. the specification of the relational data model which is expressed in terms of the 'Positional Set Notation' as given in the 'Abstract Database Model' project of the National Bureau of Standards in October 1981.The paper points out some of the differences between the four approaches to specifying the RDM semantics.

Diffusional and compartmental models for tracer washout records of Na in dog carotid

This paper re-examines studies of Na kinetics in canine carotid arterial wall previously reported by three groups of investigators. The similarities and differences in experimental and analytical approaches for Na arterial wall washout therein are reviewed. Major conclusions are: (1) A three-compartment model in series is adequate for all short and long (after subtracting the small slow exponential) records. (2) Values for the diffusion coefficient, however, varied markedly among the different groups. (3) A continuous sampling method as opposed to an intermittent one measures better the kinetics of a rapidly exchanging ion as Na +. (4) Models based on individual washout records are better than those based on ensemble averaging. Characterization of sets of results in terms of mean values for comparing parameters provides significant potential for distinguishing quantitative features between control and treated sets despite inadequacies in data sampling or model specifications.

Male-Female Earnings Differentials and the Role of Language in Canada, Ontario, and Quebec, 1970

Recent studies by Robb (1978) and Gunderson (1979a) have analysed malefemale earnings differentials in Ontario and Canada, respectively. Both authors first estimated sex-specific earnings functions, and then employed the estimated coefficients to decompose the observed or gross earnings differential into a portion attributable to differences in mean characteristics or endowments and a portion attributable to discrimination. I Discrimination is measured both by differential returns to the same productivity generating characteristics (the estimated coefficients of the characteristics) and by other forms of discrimination which do not appear explicitly in the earnings equation (the estimated intercepts). The purpose of this note is to report the results obtained from performing a similar decomposition analysis for Quebec, and to compare our results with those of Robb and Gunderson. Given the comparative nature of our study, we have chosen to use the same data base, sample characteristics, model specifications, and control variables as did Robb and Gunderson.2 The major difference between our study and those of Robb and Gunderson is the treatment of language. Robb did not include language variables in her earnings functions for Ontario, while Gunderson employed what we term a 'narrow' definition of language for Canada. In his earnings equations Gunderson measured language skills by the ability to communicate in Canada's official

The use of data type information in an interactive database environment

Despite the enormous advances that have been made in the specification of data types and data models in the fields of programming languages, databases and artificial intelligence; there remain a number of problems in attempting to unify the various approaches to the formal description of data. The purpose of this brief paper is to examine these problems from the point (or points) of view of those people—designers, administrators, applications programmers, and end-users—whose main interest is with databases. In particular, we hope to display special concern for the tools provided for the end-user, who should be the final beneficiary of whatever advances are made. In order to pin down some of these problems, it is worthwhile to attempt a definition of certain terms used in databases: 1. A data model (or database management system if one is describing an implementation) is a set of parameterized or “generic” data types. 2. A database schema is a set of data types that result from instantiating the generic types of the data model to produce a set of data types that describe the data to be stored. 3. A database is an instantiation of those types defined by a schema.

The use of data type information in an interactive database environment

Despite the enormous advances that have been made in the specification of data types and data models in the fields of programming languages, databases and artificial intelligence; there remain a number of problems in attempting to unify the various approaches to the formal description of data. The purpose of this brief paper is to examine these problems from the point (or points) of view of those people—designers, administrators, applications programmers, and end-users—whose main interest is with databases. In particular, we hope to display special concern for the tools provided for the end-user, who should be the final beneficiary of whatever advances are made. In order to pin down some of these problems, it is worthwhile to attempt a definition of certain terms used in databases: 1. A data model (or database management system if one is describing an implementation) is a set of parameterized or “generic” data types. 2. A database schema is a set of data types that result from instantiating the generic types of the data model to produce a set of data types that describe the data to be stored. 3. A database is an instantiation of those types defined by a schema.

The use of data type information in an interactive database environment

Despite the enormous advances that have been made in the specification of data types and data models in the fields of programming languages, databases and artificial intelligence; there remain a number of problems in attempting to unify the various approaches to the formal description of data. The purpose of this brief paper is to examine these problems from the point (or points) of view of those people—designers, administrators, applications programmers, and end-users—whose main interest is with databases. In particular, we hope to display special concern for the tools provided for the end-user, who should be the final beneficiary of whatever advances are made. In order to pin down some of these problems, it is worthwhile to attempt a definition of certain terms used in databases: 1. A data model (or database management system if one is describing an implementation) is a set of parameterized or “generic” data types. 2. A database schema is a set of data types that result from instantiating the generic types of the data model to produce a set of data types that describe the data to be stored. 3. A database is an instantiation of those types defined by a schema.