During the last three or four years several investigators have been exploring “semantic models ” for formatted databases. The intent is to capture (in a more or less formal way) more of the meaning of the data so that database design can become more systematic and the database system itself can behave more intelligently. Two major thrusts are clear: (I) the search for meaningful units that are as small as possible--atomic semantics; (2) the search for meaningful units that are larger than the usual n-ary relation-molecular semantics. In this paper we propose extensions to the relational model to support certain atomic and molecular semantics. These extensions represent a synthesis of many ideas from the published work in semantic modeling plus the introduction of new rules for insertion, update, and deletion, as well as new algebraic operators.

Object-oriented databases (OODBs) are believed to more naturally reflect the behavior and organization of complex application domains. The schema consists of a collection of classes, organized into hierarchies which nicely organize abstractions over the domain. Objects are created as instances of classes, encapsulating data and interpretation of data together. An important characteristic is the support for evolutionary programming, and so that existing programs may be extended with new classes without affecting other parts of the system.

In Data Warehouse (DW) scenarios, ETL (Extraction, Transformation, Loading) processes are responsible for the extraction of data from heterogeneous operational data sources, their transformation (conversion, cleaning, normalization, etc.) and their loading into the DW. In this paper, we present a framework for the design of the DW back-stage (and the respective ETL processes) based on the key observation that this task fundamentally involves dealing with the specificities of information at very low levels of granularity including transformation rules at the attribute level. Specifically, we present a disciplined framework for the modeling of the relationships between sources and targets in di#erent levels of granularity (including coarse mappings at the database and table levels to detailed inter-attribute mappings at the attribute level).

Object-Role Modeling (ORM) is a method for modeling and querying an information system at the conceptual level, and mapping between conceptual and logical (e.g. relational) levels. ORM comes in various flavors, including NIAM (Natural language Information Analysis Method). This article provides an overview of ORM, and notes its advantages over Entity Relationship and traditional Object-Oriented modeling.

This paper presents a rigorous approach to the definition and the design of graphical schemata in the framework of the relational data model. This approach uses and applies various concepts and analytical tools which were presented in a companion paper [33]

For succesful information systems development, conceptual data modelling is essential. Nowadays many techniques for conceptual data modelling exist, examples are NIAM, FORM, PSM, many (E)ER variants, IFO, and FDM. In-depth comparisons of concepts of these techniques is very difficult as the mathematical formalisations of these techniques, if existing at all, are very different. As such there is a need for a unifying formal framework providing a sufficiently high level of abstraction. In this paper the use of category theory for this purpose is addressed. Well-known conceptual data modelling concepts are discussed from a category theoretic point of view. Advantages and disadvantages of the approach chosen will be outlined. Keywords: Conceptual Data Modelling, Category Theory, Meta Modelling Classification: 68P99 (AMS-1991), H.1.0. (CR-1991) 1 Introduction It seems an undisputed fact that, opposed to most mature scientific disciplines, the discipline of information systems does not hav...

A pattern identifies a problem and provides the specification of a generic solution to that problem. Conceptual modelling patterns are aimed at representing a specific structure of knowledge that appears in different domains. Roles are meant to capture dynamic and temporal aspects of realworld objects. This paper identifies common semantics of different role models found in the literature. Moreover, it presents a conceptual modelling pattern for the role concept that includes both the static and dynamic aspects of roles. In particular, we adapt the pattern to the UML. The use of this pattern eases the definition of roles in conceptual schemas. We also discuss the advantages of our approach over previous ones.

Software development is a complex and difficult task that requires the investment of significant resources and carries major risk of failure. According to its proponents, model-driven (MD) software development approaches are improving the way we build software. Model-driven approaches putatively

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