Essential information structure diagrams and database schema design
Abstract
An Information Structure Diagram (ISD) provides a detailed and exact description of the conceptual schema. It describes the semantics of a universe of discourse, such as the various object types, their associations and constraints. The ISD subsequently functions as an input to the design of the database schema, which is expressed in terms of record types, key fields and relationships. One limitation of a detailed ISD, such as the product of the Binary Relationship conceptualization model, is that in real situations it may become too complicated and difficult to understand, thus preventing users and designers of the system from “seeing the whole picture” of the information structure.
We address this problem by introducing the concept of “essential-ISD” which is a concise, abstract and easily “read” ISD, containing the most important elements of the conceptual schema. Later on that essential-ISD is used to produce a “skeleton” of the database schema, which outlines the normalized record types and their associations.
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1997, Data and Knowledge EngineeringIn an information system a key role is played by the underlying data schema. This article starts out from the view that the entire modelling process of an information system's data schema can be seen as a schema transformation process. A transformation process that starts out with an initial draft conceptual schema and ends with an internal database schema for some implementation platform. This allows us to describe the transformation process of a database design as an evolution of a schema through a universe of data schemas. Doing so allows a better understanding of the actual design process, countering the problem of ‘software development under the lamppost’. Even when the information system design is finalised, the data schema can evolve further due to changes in the requirements on the system. We present a universe of data schemas that allows us to describe the underlying data schemas at all stages of their development. This universe of data schemas is used as a case study on how to describe the complete evolution of a data schema with all its relevant aspects. The theory is general enough to cater for more modelling concepts, or different modelling approaches. To actually model the evolution of a data schema we present a versioning mechanism that allows us to model the evolutions of the elements of data schemas and their interactions, leading to a better understanding of the schema design process as a whole. Finally, we also discuss the relationship between this simple versioning mechanism and general-purpose version-management systems.
A generic model for 3-dimensional conceptual modelling
1996, Data and Knowledge EngineeringThis article discusses two highly intertwined issues. Firstly, we discuss the lack of top-down abstraction mechanisms in data modelling techniques; i.e. abstraction techniques that are fully integrated into the modelling technique and methodology and not just a ‘post-modelling process’ add on. Secondly, we are concerned with the integration of object-oriented modelling techniques and traditional data modelling techniques.
We start by discussing the pragmatics and motivations behind these issues. Then, a formalisation of (the syntax and semantics of) a data modelling technique is presented that is a generalisation of (E)ER and ORM, and also adheres to the requirements of an object-oriented technique as laid down in the object-oriented manifesto. The result of this exercise is the so-called CDM Kernel. Furthermore, we briefly show how (E)ER, ORM and object-oriented views can be derived from models in the CDM Kernel. This effectively means that the CDM Kernel equates (E)ER, ORM and (some) object-oriented models.
Finally, we briefly discuss some practical issues on the use of the facilities offered by the CDM Kernel in terms of modelling practice and tool support. A generalised conceptual modelling kernel will be very beneficial in the context of CASE Tool and in the context of federated database (information) systems.
Conceptual design of object-oriented database schemas using the binary-relationship model
1995, Data and Knowledge EngineeringWe describe an algorithmic method for transforming a binary-relationship (BR) conceptual schema to an object-oriented (OO) database schema. The BR schema is a semantically rich diagram that represents the reality being modeled in terms of objects, relationships and constraints. It is easy to understand and serves as a communication tool between users and designers. Therefore it can be created in the early stages of system development, and later on be transformed into a specific OO database schema. The transformation method employs a multi-stage algorithm, which first identifies the essential objects in the BR schema, together with their relationships and constraints. These are then mapped to object classes, attributes, and constraints, maintaining the semantics and all types of constraints present in the conceptual schema.
A methodology and tool for top-down relational database design
1993, Data and Knowledge EngineeringThis paper presents a methodology for logical design of relational schemas and integrity constraints using semantic binary schemas. This is a top-down methodology. In this methodology, a conceptual description of an enterprise is designed using a semantic binary model. Then, this description is converted into the relational database design.
The paper also describes a tool which automates all the busy work of the methodology and provides graphic output. With respect to the intelligent design decisions, the tool accepts instructions from its user, who is a database designer, or, when the user defaults, makes decisions itself based on ‘rule-of-thumb’ principles.
Database reverse engineering: From the relational to the binary relationship model
1993, Data and Knowledge EngineeringThis paper describes an algorithmic method for transforming a relational database schema to a binary-relationship one. The source schema may consist of relations that are at any level of normalization, and the designer may add semantic information on the source schema, such as the definition of candidate keys, foreign keys, functional dependencies of various types, multi-valued dependencies, many-to-many constraints, inclusion dependencies, and others. Based on this information, the multi-stage transformation algorithm applies mapping rules to generate object-types, binary-relationships and constraints in the target conceptual schema. The method is implemented as a PC-based tool, utilizing Ingres, SQL and C, and is part of a comprehensive database design tool for both forward and reverse engineering.
Binary-relationship integration methodology
1991, Data and Knowledge EngineeringBRIM is a view integration methodology which utilizes the binary-relationship data model and encompasses all stages of conceptual schema integration. In the pre-integration stage it assists the designer to prepare a binary-strategy integration plan. Then, in the stage of conflict resolution, it identifies and resolves all possible types of conflict between schemas, including naming conflicts (i.e. homonyms and synonyms) and structural conflicts (i.e. conflicts regarding differences between types, dependencies, keys, constraints, and hierarchies of objects). Once conflicts are resolved and the source schemas are in conformity, they are merged by superimposition, and inter-schema relationships are added to the integrated schema. The process is repeated for every two source schemas or intermediate results, until the target global schema is obtained.
BRIM is supported by an interactive software tool which is part of a PC-based system for automated database design. The tool leads the designer through all stages of the integration process, applying conflict resolution rules and schema merging algorithms, providing an integrated conceptual schema which can then be automatically tranformed into a normalized database schema.