Integrating intelligent methodological and tutoring assistance in a CASE platform: The PANDORA experience

Database Design discipline involves so different aspects as conceptual and logical modelling knowledge or domain understanding. That implies a great effort to carry out the real world abstraction task and represent it through a data model. CASE tools emerge in order to automating the database development process. These platforms try to help to the database designer in different database design phases. Nevertheless, this tools are frequently mere diagrammers and do not carry completely out the design methodology that they are supposed to support; furthermore, they do not offer intelligent methodological advice to novice designers. This paper introduces the PANDORA tool (acronym of Platform for Database Development and Learning via Internet) that is being developed in a research project which tries to mitigate some of the deficiencies observed in several CASE tools, defining methods and techniques for database development which are useful for students and practitioners. Specifically, this work is focused on two PANDORA components: Conceptual Modelling and Learning Support subsystems

Applying a Fuzzy Approach to Relaxing Cardinality Constraints

9 pages, 3 figures.-- Contributed to: 15th International Conference on Database and Expert Systems Applications (DEXA 2004, Zaragoza, Spain, Aug 30 - Sep 3, 2004).In database applications the verification of cardinality constraints is a serious and complex problem that appears when the modifications operations are performed in a large cascade. Many efforts have been devoted to solve this problem, but some solutions lead to other problems such as the complex execution model or an impact on the database performance. In this paper a method to reducing and simplifying the complex verification of cardinality constraints by relaxing these constraints using fuzzy concepts is proposed.Publicad

Modeling views in the layered view model for XML using UML

In data engineering, view formalisms are used to provide flexibility to users and user applications by allowing them to extract and elaborate data from the stored data sources. Conversely, since the introduction of Extensible Markup Language (XML), it is fast emerging as the dominant standard for storing, describing, and interchanging data among various web and heterogeneous data sources. In combination with XML Schema, XML provides rich facilities for defining and constraining user-defined data semantics and properties, a feature that is unique to XML. In this context, it is interesting to investigate traditional database features, such as view models and view design techniques for XML. However, traditional view formalisms are strongly coupled to the data language and its syntax, thus it proves to be a difficult task to support views in the case of semi-structured data models. Therefore, in this paper we propose a Layered View Model (LVM) for XML with conceptual and schemata extensions. Here our work is three-fold; first we propose an approach to separate the implementation and conceptual aspects of the views that provides a clear separation of concerns, thus, allowing analysis and design of views to be separated from their implementation. Secondly, we define representations to express and construct these views at the conceptual level. Thirdly, we define a view transformation methodology for XML views in the LVM, which carries out automated transformation to a view schema and a view query expression in an appropriate query language. Also, to validate and apply the LVM concepts, methods and transformations developed, we propose a view-driven application development framework with the flexibility to develop web and database applications for XML, at varying levels of abstraction

Plugging active mechanisms to control dynamic aspects derived from the Multiplicity Constraint in UML

8 pages, 5 figures.-- Contributed to: 7th International Conference on the Unified Modeling Language (UML'2004, Lisbon, Portugal, Oct 11-15, 2004).Multiple efforts have been devoted to face the problem of database modelling. One of them is the automatization of database design process using CASE tools. Frequently, these tools do not completely support all phases of database analysis and the design methodology that they propose. Therefore, we propose to incorporate new features to these tools enhancing them and solving some of the modelling problems. In this paper we present an add-in module that aims to generate triggers for preserving the multiplicity constraints of a conceptual scheme in the transformation to a relational scheme. The module is integrated into the RATIONAL ROSE case tool.Publicad

Ontology mapping: the state of the art

Ontology mapping is seen as a solution provider in today's landscape of ontology research. As the number of ontologies that are made publicly available and accessible on the Web increases steadily, so does the need for applications to use them. A single ontology is no longer enough to support the tasks envisaged by a distributed environment like the Semantic Web. Multiple ontologies need to be accessed from several applications. Mapping could provide a common layer from which several ontologies could be accessed and hence could exchange information in semantically sound manners. Developing such mapping has beeb the focus of a variety of works originating from diverse communities over a number of years. In this article we comprehensively review and present these works. We also provide insights on the pragmatics of ontology mapping and elaborate on a theoretical approach for defining ontology mapping

Formal design of data warehouse and OLAP systems : a dissertation presented in partial fulfilment of the requirements for the degree of Doctor of Philosophy in Information Systems at Massey University, Palmerston North, New Zealand

A data warehouse is a single data store, where data from multiple data sources is integrated for online business analytical processing (OLAP) of an entire organisation. The rationale being single and integrated is to ensure a consistent view of the organisational business performance independent from different angels of business perspectives. Due to its wide coverage of subjects, data warehouse design is a highly complex, lengthy and error-prone process. Furthermore, the business analytical tasks change over time, which results in changes in the requirements for the OLAP systems. Thus, data warehouse and OLAP systems are rather dynamic and the design process is continuous. In this thesis, we propose a method that is integrated, formal and application-tailored to overcome the complexity problem, deal with the system dynamics, improve the quality of the system and the chance of success. Our method comprises three important parts: the general ASMs method with types, the application tailored design framework for data warehouse and OLAP, and the schema integration method with a set of provably correct refinement rules. By using the ASM method, we are able to model both data and operations in a uniform conceptual framework, which enables us to design an integrated approach for data warehouse and OLAP design. The freedom given by the ASM method allows us to model the system at an abstract level that is easy to understand for both users and designers. More specifically, the language allows us to use the terms from the user domain not biased by the terms used in computer systems. The pseudo-code like transition rules, which gives the simplest form of operational semantics in ASMs, give the closeness to programming languages for designers to understand. Furthermore, these rules are rooted in mathematics to assist in improving the quality of the system design. By extending the ASMs with types, the modelling language is tailored for data warehouse with the terms that are well developed for data-intensive applications, which makes it easy to model the schema evolution as refinements in the dynamic data warehouse design. By providing the application-tailored design framework, we break down the design complexity by business processes (also called subjects in data warehousing) and design concerns. By designing the data warehouse by subjects, our method resembles Kimball's "bottom-up" approach. However, with the schema integration method, our method resolves the stovepipe issue of the approach. By building up a data warehouse iteratively in an integrated framework, our method not only results in an integrated data warehouse, but also resolves the issues of complexity and delayed ROI (Return On Investment) in Inmon's "top-down" approach. By dealing with the user change requests in the same way as new subjects, and modelling data and operations explicitly in a three-tier architecture, namely the data sources, the data warehouse and the OLAP (online Analytical Processing), our method facilitates dynamic design with system integrity. By introducing a notion of refinement specific to schema evolution, namely schema refinement, for capturing the notion of schema dominance in schema integration, we are able to build a set of correctness-proven refinement rules. By providing the set of refinement rules, we simplify the designers's work in correctness design verification. Nevertheless, we do not aim for a complete set due to the fact that there are many different ways for schema integration, and neither a prescribed way of integration to allow designer favored design. Furthermore, given its °exibility in the process, our method can be extended for new emerging design issues easily