Isabelle Comyn-Wattiau

A UML-based data warehouse design method

Data warehouses are a major component of data-driven decision support systems (DSS). They rely on multidimensional models. The latter provide decision makers with a business-oriented view to data, thereby easing data navigation and analysis via On-Line Analytical Processing (OLAP) tools. They also determine how the data are stored in the data warehouse for subsequent use, not only by OLAP tools, but also by other decision support tools. Data warehouse design is a complex task, which requires a systematic method. Few such methods have been proposed to date. This paper presents a UML-based data warehouse design method that spans the three design phases (conceptual, logical and physical). Our method comprises a set of metamodels used at each phase, as well as a set of transformations that can be semi-automated. Following our object orientation, we represent all the metamodels using UML, and illustrate the formal specification of the transformations based on OMGs Object Constraint Language (OCL). Throughout the paper, we illustrate the application of our method to a case study.

Perspectives in Conceptual Modeling

First International Workshop on Best Practices of UML (BP-UML 2005).- Preface to BP-UML 2005.- Experience Reports and new Applications.- Current Practices in the Use of UML.- An Empirical Study of the Nesting Level of Composite States Within UML Statechart Diagrams.- Utilizing a Multimedia UML Framework for an Image Database Application.- Model Evaluation and Requirements Modeling.- Object Class or Association Class? Testing the User Effect on Cardinality Interpretation.- Organizing and Managing Use Cases.- A Comparative Analysis of Use Case Relationships.- Metamodeling and Model Driven Development.- Applying Transformations to Model Driven Development of Web Applications.- A Precise Approach for the Analysis of the UML Models Consistency.- A UML 2 Profile for Business Process Modelling.- Seventh International Bi-conference Workshop on Agent-Oriented Information Systems (AOIS-2005).- Preface to AOIS 2005.- Invited Talk.- Agent Oriented Data Integration.- Positions in Engineering Agent Oriented Systems.- AOSE and Organic Computing - How Can They Benefit from Each Other? Position Paper.- Modeling Dynamic Engineering Design Processes in PSI.- Agent Oriented Methodologies and Conceptual Modeling.- Preliminary Basis for an Ontology-Based Methodological Approach for Multi-agent Systems.- DDEMAS: A Domain Design Technique for Multi-agent Domain Engineering.- An Agent-Oriented Meta-model for Enterprise Modelling.- Agent Communication and Coordination.- An Approach to Broaden the Semantic Coverage of ACL Speech Acts.- Normative Pragmatics for Agent Communication Languages.- Experimental Comparison of Rational Choice Theory, Norm and Rights Based Multi Agent Systems.- Second International Workshop on Conceptual Modeling for Geographic Information Systems (CoMoGIS 2005).- Preface to CoMoGIS 2005.- Invited Talk.- Map Algebra Extended with Functors for Temporal Data.- Spatial and Spatio-temporal Data Representation.- A Formal Model for Representing Point Trajectories in Two-Dimensional Spaces.- A Logical Approach for Modeling Spatio-temporal Objects and Events.- Conceptual Neighbourhood Diagrams for Representing Moving Objects.- Spatial Relations.- A Refined Line-Line Spatial Relationship Model for Spatial Conflict Detection.- Assessing Topological Consistency for Collapse Operation in Generalization of Spatial Databases.- Spatial Relations for Semantic Similarity Measurement.- Spatial Queries, Analysis and Data Mining.- Approximate Continuous K Nearest Neighbor Queries for Continuous Moving Objects with Pre-defined Paths.- Spatio-temporal Similarity Analysis Between Trajectories on Road Networks.- Using Data Mining for Modeling Personalized Maps.- Data Modeling and Visualisation.- 3D Scene Modeling for Activity Detection.- SAMATS - Edge Highlighting and Intersection Rating Explained.- Applying Semantic Web Technologies for Geodata Integration and Visualization.- Sixth International Workshop on Conceptual Modeling Approaches for e-Business (eCOMO 2005).- Preface to eCOMO 2005.- Bargaining in E-Business Systems.- Conceptual Content Management for Enterprise Web Services.- Verifying Web Services Composition.- Towards Amplifying Business Process Reuse.- First International Workshop on Quality of Information Systems (QoIS 2005).- Preface to QoIS 2005.- Information System Models Quality.- Measuring the Perceived Semantic Quality of Information Models.- Situated Support for Choice of Representation for a Semantic Web Application.- Towards Systematic Model Assessment.- A Fuzzy Based Approach to Measure Completeness of an Entity-Relationship Model.- Quality Driven Processes.- Managing Information Quality in e-Science: A Case Study in Proteomics.- Tool Support and Specification Quality: Experimental Validation of an RE-Tool Evaluation Framework.- Improving Object-Oriented Micro Architectural Design Through Knowledge Systematization.- Tutorials.- Tutorial 1: eduWeaver - The Courseware Modeling Tool.- Tutorial 2: FOOM - Functional and Object Oriented Methodology: An Integrated Approach.- Tutorial 3: Domain Engineering - Using Domain Concepts to Guide Software Design.- Tutorial 4: Reasoning About Web Information Systems.- Tutorial 5: Schema and Data Translation.- Tutorial 6: Modeling and Simulation of Dynamic Engineering Design Processes.- Tutorial 7: Modeling Enterprise Applications.

Conceptual Modeling Quality - From EER to UML Schemas Evaluation

This exploratory research investigates the evaluation process of conceptual specifications developed using either Extended Entity-Relationship (EER) or Unified Modeling Language (UML) conceptual models. In this paper, we provide a comprehensive framework for evaluating EER and UML conceptual schemas. Furthermore, we define classes of metrics facilitating the evaluation process and leading to the choice of the appropriate representation among several schemas describing the same reality. Based on quality criteria proposed in the literature, we select a subset of criteria relevant to conceptual EER schema quality evaluation. For each criterion we define one or several metrics allowing the designer to measure the schema quality. We evaluate alternative EER conceptual schemas representing the same universe of discourse using the appropriate criteria and their associated metrics. Finally, we extrapolate this evaluation process to UML schemas. Following the development of our framework, we analyze a case study and provide evidence in the support of the usefulness of the framework.

Ontologies for Security Requirements: A Literature Survey and Classification

Despite existing methodologies in the field, most requirements engineers are poorly trained to define security requirements. This is due to a considerable lack of security knowledge. Some security ontologies have been proposed, but a gap still exists between the two fields of security requirement engineering and ontologies. This paper is a survey, it proposes an analysis and a typology of existing security ontologies and their use for requirements definition.

Entity-relationship and object-oriented model automatic clustering

Automatic clustering of semantic models allows a multilevel abstraction of the same reality and reduces design complexity. This paper is concerned with the development and application of automatic clustering of Entity-Relationship (E-R) diagrams and object models. This paper does not consider physical clustering which aims at improving performance of databases but deals with conceptual clustering whose objective is to facilitate the understanding of the database schema. We provide an automatization of conceptual schema clustering leading to a unification of past approaches. Automatization is achieved through the definition of semantic distances between concepts and the use of a clustering algorithm. For entity-relationship clustering, we define three different distances (visual, hierarchical and cohesive) depending on the semantic richness. Object model clustering is based on structural, semantic and communication characteristics of objects. Our approach has been implemented and applied to a great number of examples, leading to interesting results. Applications of automatic clustering in several areas and their potential as a communication, documentation and design tools for E-R diagrams and object oriented models are described and discussed.

Extracting generalization hierarchies from relational databases: A reverse engineering approach

Relational Data Base Management Systems (RDBMS) are currently the most popular database management systems. The relational model is a simple and powerful model for representing real world applications. However, it lacks the expressiveness of conceptual models. Unlike the latter, the relational model does not offer the generalization abstraction. Therefore, it does not allow the designer to represent directly a large variety of integrity constraints. Moreover, inclusion dependencies formalizing inter-relational constraints cannot directly be represented in the relational model, due to the fact that its basic construct, the relation, is the unique structure. Finally, relational databases do not enable a natural way to represent inheritances. In this paper we describe a reverse engineering method which particularly deals with the elicitation of inheritance links embedded in a relational database, combining heuristic and algorithmic approaches. We provide rules for detecting intersection constraints and inclusion dependencies. Heuristics are proposed for understanding null value semantics. Finally, we present decision rules for detecting existence dependencies and translating them into IS-A hierarchies among entities. An example is used to illustrate our approach.

Dimension Hierarchies Design from UML Generalizations and Aggregations

Data for decision-making applications are based on dimensions, such as time, customer, and product. These dimensions are naturally related by hierarchies. Hierarchies are crucial to multidimensional modeling. Defining hierarchies using star or snowflake schemas can be misleading, since they are not explicitly well-modeled. However, deriving them from conceptual UML or ER schemas is a non-trivial task since they have no direct equivalent in conceptual models. This paper focuses on the definition of multidimensional hierarchies. We present and illustrate rules for defining multidimensional hierarchies from UML schemas, especially based on aggregation and generalization hierarchies. The definition of hierarchies is part of a data warehouse design method based on the three usual modeling levels : conceptual, logical, and physical. The conceptual schema is based on the UML notation. The logical schema is represented using a unified pivot multidimensional model. The physical schema depends on the target ROLAP or MOLAP tool.

A Taxonomy of Evaluation Methods for Information Systems Artifacts

Abstract Artifacts, such as software systems, pervade organizations and society. In the field of information systems (IS) they form the core of research. The evaluation of IS artifacts thus represents a major issue. Although IS research paradigms are increasingly intertwined, building and evaluating artifacts has traditionally been the purview of design science research (DSR). DSR in IS has not reached maturity yet. This is particularly true of artifact evaluation. This paper investigates the “what” and the “how” of IS artifact evaluation: what are the objects and criteria of evaluation, the methods for evaluating the criteria, and the relationships between the “what” and the “how” of evaluation? To answer these questions, we develop a taxonomy of evaluation methods for IS artifacts. With this taxonomy, we analyze IS artifact evaluation practice, as reflected by ten years of DSR publications in the basket of journals of the Association for Information Systems (AIS). This research brings to light important relationships between the dimensions of IS artifact evaluation, and identifies seven typical evaluation patterns: demonstration; simulation- and metric-based benchmarking of artifacts; practice-based evaluation of effectiveness; simulation- and metric-based absolute evaluation of artifacts; practice-based evaluation of usefulness or ease of use; laboratory, student-based evaluation of usefulness; and algorithmic complexity analysis. This study also reveals a focus of artifact evaluation practice on a few criteria. Beyond immediate usefulness, IS researchers are urged to investigate ways of evaluating the long-term organizational impact and the societal impact of artifacts.

Reverse Engineering of Relational Database Physical Schema

This paper seeks to present and illustrate essential aspects of database physical de-optimisation within the context of a reverse engineering method, called MeRCI. The latter provides a framework allowing us to achieve a reverse engineering of a relational database into an Extended Entity-Relationship schema. In this paper we focus mainly on a critical step of MeRCI leading to schema de-optimization that removes the non-semantic aspects of the physical and logical schemas. To achieve such a result, we reverse engineer the physical structures obtained by a database designer when using restructuring operations. Removing optimization structures requires to reverse the effect of both relational operators (join, restrict, project, etc) and non-relational operators such as the flattening operator. The de-optimization process requires the analysis of both the Data Description Language (DDL) and the Data Manipulation Language (DML) specifications and to perform a data mining process, thus allowing us to recover the structure of a database conceptual schema. The paper illustrates the de-optimization process by applying it to various examples. Finally, we discuss implications for further research pertaining to the logic and development of an efficient and complete reverse engineering method eliciting the semantics of a relational database.

Constraint confrontation: An important step in view integration

This paper addresses the problem of constraint integration in database design. The approach is inserted in an incremental database design methodology supported by the design environment KHEOPS. The view integration step using semantic unification is followed by the initial constraint confrontation. The detection phase is a deductive process in which the contradictions and redundancies between constraints are exhibited. The following conflict resolution depends on the strategy initially chosen by the designer. Four strategies are presented and discussed. An example of use is given to illustrate the application of those strategies. This approach could be enlarged in an object oriented context where schemata would have not only constraints but also methods to compare.