A data dictionary system approach for database schema translation

When designing information processing systems, the key problem is to find what symbols and constructs (available in some given language) should be used so as to be able to answer the questions that the users want to ask and to perform the state transitions that the users have to perform in order to keep in step with some reality that is being modelled. If the language that is being used cannot be interpreted directly by the software of a computer (e.g. set theory, algebra, semantic networks), the resulting model is called an abstract model (e.g. a specification, a data base schema). If all of the symbols and constructs used to express the model can be interpreted by a computer, the model is a concrete implementation (e.g. a data base system). Both the abstract and concrete models capture some aspects of the reality that is modelled. They differ with respect to the languages in which they are expressed. The choice of the languages which are appropriate for writing such models is a subject of intensive debate. The recent workshop on Data Abstraction, Data Bases and Conceptual Modelling has shown that this debate is not likely to diminish in the near future. In the context of this debate, however, a common opinion was expressed several times by data base participants: the data models used to specify data base schemas are lacking to support the specification of operations tailored to particular application environments. It is therefore expected that in the context of data base modelling, the integration of operations (behaviour) with data (structure) will be one of the most fertile research areas for the next few years.

To deal with issues of data model transformation and to make combined use of different data models, this paper proposed a database reengineering scheme which includes schema translation and data conversion from object-oriented data model to flattened XML data model with is-a and cardinality data semantics preservation. In this paper, conceptual schema of object-oriented data model and flattened XML data model are elaborated by UML class diagram and XML Schema Definition(XSD) graph respectively. Logical schema is described by UNISQL class definition and XSD respectively. This paper firstly analyzes class definitions from OODB and sorts them from most independent classes to most dependent classes. Secondly schema translation is processed by mapping class to complexType and then creating element definitions in XSD file. Thirdly data conversion is processed automatically. Performance tests have shown that the proposed database reengineering scheme is reliable and efficient.

The development of an Electronic Health Record (EHR) system requires a well-defined data set and a robust data model to support complex clinical workflows, interoperability, and data quality. Many existing EHR implementations lack standardized and integrated data models, resulting in redundancy, semantic inconsistency, and limited support for secondary data use. This study aims to develop a comprehensive EHR data model based on a Minimum Data Set (MDS) that systematically represents medical service processes across emergency, outpatient, inpatient, and surgical care. The proposed approach involves the design of a conceptual, logical, and physical data model. Business processes were first analysed to identify relationships among clinical and administrative data classes, which were then transformed into a conceptual data model. The logical data model was developed through database normalization and schema definition, while the physical data model was constructed to represent the actual database structure for implementation. The results demonstrate a structured EHR data model comprising 21 interrelated data classes that reflect real-world medical service workflows. The conceptual data model establishes clear entity relationships, supporting data consistency and interoperability. The logical data model provides a normalized SQL-based schema that minimizes redundancy and enhances data integrity, while the physical data model enables efficient data storage and access. A prototype EHR system was implemented to evaluate the feasibility of the proposed data model, showing stable performance, usability, and alignment with functional requirements. This study concludes that a standardized EHR data model derived from an MDS can effectively support comprehensive clinical documentation, interoperability, and future scalability. The proposed model provides a strong foundation for developing national or institutional EHR systems and can serve as a reference for further EHR data standardization efforts.

A major problem with currently existing database systems is that there often does not exist a conceptual understanding of the data. Such an understanding can be obtained by describing the data using a semantic data model, such as the ER model. Consequently, there is a need for methods that translate a schema in a traditional data model into a conceptual schema. We present a method for translating a schema in the relational model into a schema in a conceptual model. We also show that the schema produced has the same information capacity as the original schema. The conceptual model used is a formalization of an extended ER model, which also includes the subtype concept. >

ORION-2 is a commercially available, federated, object-oriented database management system designed and implemented at MCC. One major architectural innovation in ORION-2 is the coexistence of a shared databese and a number of private databases. The shared database is accessible to all authorized users of the system, while each private database is accessible to only the user who owns it. A distributed database system with a shared database and private databases for individual users is a natural architecture for data-intensive application environments on a network of workstations, notably computer-aided design and engineering systems. This paper discusses the benefits and limitations of such a system and explores the impact of such an architecture on the semantics and implementation of some of the key functions of a database system, notably queries, database schema, and versions. Although the issues are discussed in the context of an object-oriented data model, the results (at least significant portions thereof) are applicable to database systems supporting other data models.

The current trend toward increasing database applications and end-user computing brings about the need for effective training and support tools that enable end users to perform logical database designs. This paper presents a unique comparison of a network-based data model (the extended entity relationship (EER)) and a hierarchical-based data model (the structured object model (SOM)) and their associated logical database design methods, LRDM (EER-based) and the SOM method, in end-user logical database design. The SOM method, based on an object-oriented knowledge representation scheme, is a new structured method designed to be less susceptible to designer errors and yet capable of maintaining ease of understanding and use. The Logical Relational Design Methodology (LRDM), based on the EER model, shares some common characteristics with the SOM method. In the analytic comparison the basic components and constructs of EER and SOM, as well as their use in the logical design process, are compared to derive a qualitative assessment of the two methods. Two experiments using novice database designers were conducted to examine the effectiveness of each method in leading to accurate logical designs, the time needed for task completion and the improvement in performance over a short training period. To confirm the findings from other studies on logical database design using non-graphic methods versus using graphic methods, the normalization method was included in one of the experiments. The results showed that end users performed better with graphic methods and also preferred them to the non-graphic (normalization) method. Furthermore, users learned and improved in a short period using LRDM (EER-based). However, users of the SOM method generated more accurate designs, were able to identify more complex relationships, and had more significant improvements during the training period than did users of LRDM (EER-based).

Fundamental notions of relative information capacity between database structures are studied in the context of the relational model. Four progressively less restrictive formal definitions of "dominance" between pairs of relational database schemata are given. Each of these is shown to capture intuitively appealing, semantically meaningful properties which are natural for measures of relative information capacity between schemata. Relational schemata, both with and without key dependencies, are studied using these notions. A significant intuitive conclusion concerns the informal notion of relative information capacity often suggested in the conceptual database literature, which is based on accessability of data via queries. Results here indicate that this notion is too general to accurately measure whether an underlying semantic connection exists between database schemata. Another important result of the paper shows that under any natural notion of information capacity equivalence, two relational schemata (with no dependencies) are equivalent if and only if they are identical (up to re-ordering of the attributes and relations). The approach and definitions used here can form part of the foundation for a rigorous investigation of a variety of important database problems involving data relativism, including those of schema integration and schema translation.

Database schemas evolve over time to satisfy changing application requirements. If this evolution is not performed correctly, some quality attributes are at risk such as data integrity, functional correctness, or maintainability. To help developer teams in the design of database schemas, several design methodologies for NoSQL databases have proposed to use conceptual models during this process. The use of an explicit conceptual model can also help developers in the tasks of schema evolution. In this work-in-progress paper, we propose a framework that, given a change in the conceptual model, identifies what must be modified in a NoSQL database schema and the underlying data. We researched several open source projects that use Apache Cassandra to study the benefits of using a conceptual model during the schema evolution process as well as to understand how these models evolve. In this first work, we have focused on studying seven types of conceptual model changes identified in these projects. For each change we describe the transformation required in the database schema to maintain the consistency between the schema and the model as well as the migration of data required to the new schema version.

Conceptual schemas are widely used in geospatial data modelling. This paper takes a close look at some schemas prevalent in the context of existing spatial data infrastructures as e.g. INSPIRE and identifies problems which occur when trying to apply the Model Driven Architecture (MDA) approach to these schemas. Applications of the MDA approach in the geospatial domain such as schema translation and automatic derivation of transfer formats from conceptual schemas are described. With these applications in mind, suggestions for enhancing existing schemas and for defining new schemas are made.

This research compares success in developing conceptual data models for the extended entity relationship (EER) model and Kroenke’s object oriented model. A laboratory study was used to evaluate model correctness for 38 subjects divided into two equally sized groups where each group was trained in one of the modeling methods. Modeling correctness is measured in terms of eight different facets of a conceptual data model: (1) entities/objects, (2) attribute/property identifiers, (3) categories, (4) unary one-one relationships, (5) binary one-many relationships, (6) binary many-many relationships, (7) ternary one-many-many relationships, and (8) ternary many-many-many relationships. The EER model provided significantly improved performance for the attribute/ property identifier, unary one-one relationship, and binary many-many relationship facets.

This book consists of 35 chapters presenting different theoretical and practical aspects of Intelligent Information and Database Systems. Nowadays both Intelligent and Database Systems are applied in most of the areas of human activities which necessitates further research in these areas. In this book various interesting issues related to the intelligent information models and methods as well as their advanced applications, database systems applications, data models and their analysis and digital multimedia methods and applications are presented and discussed both from the practical and theoretical points of view. The book is organized in four parts devoted to intelligent systems models and methods, intelligent systems advanced applications, database systems methods and applications and multimedia systems methods and applications. The book will be interesting forpractitioners and researchers, especially graduate and PhD students of information technology and computer science, as well more experienced academics and specialists interested in developing and verification of intelligent information, database and multimedia systems models, methods and applications. The readers of this volume are enabled to find many inspiring ideas and motivating practical examples that will help them in the current and future work.

The thesis examines issues of consistency maintenance in advanced database systems; primarily, multidatabase systems. A multidatabase system consists of a number of pre-existing local database systems. A local database system is unaware of its participation in the multidatabase system and, likewise, the multidatabase system has no knowledge of local transaction executions. Enforcing global constraints in such an environment is clearly a challenging task. A methodology for constraint enforcement is presented which utilises existing technology for the replication of data in an attempt to enforce global consistency. While it is shown to have limited applicability, it is nonetheless an interesting study and serves to qualify the limits of such a solution. An alternative method for global consistency maintenance, which relies on the existence of triggers at each of the participant local databases, is then discussed. This method is shown to be particularly suitable when the issue of local database autonomy is of concern. It is, however, only suited to systems where each of the local databases provides a capability for triggering external actions based on the occurrence of particular database events. As a result of this methodology, the requirement for identification of enforcement actions which access sites where the instigating transaction originated becomes apparent. Such enforcement actions can cause deadlock in certain circumstances when they are executed at the same site which initially triggered the global constraint. This issue is dealt with in a novel way by proposing a methodology for statically checking relations at each participant site with a view to determining their susceptibility to this form of deadlock. The method, a graphical representation of the constraint enforcement process in a distributed system, is also shown to have other desirable properties. Arising from the requirements of other work within the thesis, an algorithm for detecting all cycles in a given directed graph is presented. It is shown that, while the well-known adaptation of the Depth First Search algorithm to cycle detection in directed graphs can detect the existence of cycles, it cannot in all circumstances identify all cycles. An algorithm which performs this task is presented together with an analysis of its complexity and correctness. In a more general sense, the issue of deferred constraint enforcement is discussed. Several scenarios where deferred enforcement of constraints is required are presented, together with a method for detecting the presence of cyclic dependencies within a given database schema.

Many software engineering activities entail dealing with legacy information systems. When these systems become too costly to maintain, or when new technologies need to be incorporated, they need to be replaced or somehow reengineered. This can be done with significantly reduced amount of effort and cost if the conceptual models of these systems are available. Reverse engineering is the process of analyzing a subject system to create representations of the system at a higher level of abstraction. Relational databases are a common source of reverse engineering. Starting from a physical database schema, that is recorded into relational database schema data repository, the conceptual database schema or logical database schema could be extracted. The extraction process may be seen as a chain of model-to-model transformations that trace model elements from a model at the lower level of abstraction to a model at the higher level of abstraction, achieved through meta-modeling. In the paper we present generic and standard database constraint meta-models, focusing on multi-relational database constraints captured in a legacy database. These meta-models are aimed at support of model transformations to create conceptual models, as a useful source for the system reengineering process.

In this paper we define and formalize the model transformations that complete the methodological approach for the development of Object-Relational (OR) Databases (DB) proposed in MIDAS, a model driven methodology for the development of Web Information Systems. In this proposal the Platform Independent Model is the conceptual data model while the Platform Specific Model is the Object-Relational model that represents the OR DB schema. Since both of them will be represented in UML, we also summarize an UML profile for OR DB modeling. In this work we focus on the formalization of the mappings needed to get the OR DB schema from the conceptual data model. We have first specified them with natural language to later formalize them with graph transformation rules.

Information integration is vital for keeping manufacturing operations competitive. A case study approach has been adopted to better understand the role of informatio in integrated manufacturing. Information is now considered a corporate asset. The creation, processing, movement and security of information is therefore as important as the products/services of an enterprise. The case studies have helped in identifying the requirements and issues involved in developing an information system and supporting software framework for a manufacturing enterprise. This paper deseribes a case study dealing with the integrated manufacture of optical fiber products. A phased development and implementation approach was adopted where a small, manageable slice of the system is considered for the case study followed by functional modeling (IDEFO) and data flow modeling (data flow diagrams). This identifies the pieces of information of interest. The information relationships are modeled using extended entity relationship (EER) diagrams which are then mapped to a relational model. The relational tables thus obtained were implemented on a commercial Database Management System (DBMS). The functional constraints and application interfaces were then built using Structured Query Languages (SQL) and commercial application interface tools. Subsequent sections describe the functional models, data flow diagrams (DFDs), EER diagrams, relational database design and user/application interfaces developed for the system. Implementation experiences and observations are discussed along with the applications of the implemented system. The case study has helped in developing a preliminary data model (i.e., a model about data by which a reasonable interpretation of the data can be obtained) for material handling (MH) functions.