Catálogo de publicaciones - libros

This paper discusses several research directions and challenges of a new frontier of research: active conceptual modeling. It suggests how the Entity-Relationship (ER) model may be extended to satisfy some of the needs of a new set of emerging user needs and applications.

A number of studies show [1][2][3][4] that systems fail due to an inadequate or insufficient understanding of the requirements they seek to address. Further, the amount of effort needed to fix these systems has been found to be very high [5]. To correct this situation, it is necessary to address the issue of requirements elicitation, validation, and specification in a relatively more focussed manner. The expectation is that as a result of this, more acceptable systems will be developed in the future. The field of requirements engineering has emerged to meet this expectation.

This paper presents a context-driven approach that aims at supporting semantic mediation between composed Web services. Despite the widespread adoption of Web services by the IT community, innovative solutions are needed in order to overcome the challenging issue that relates to the semantic disparity of exchanged data. Indeed, there is a lack of means for interpreting these data according to the contextual requirements of each Web service. The context-driven approach suggests two steps. The first step consists of developing a model for anchoring context to data flowing between Web services. In the second step, we use this model to support the semantic mediation between Web services engaged in a composition.

Service choreography has become an emerging and promising technology to design and build complex cross-enterprise business applications. Dynamic composition of services on the fly requires mechanisms for ensuring that the component services in the composition are compatible with each other. Current service composition languages provide notations for describing the interactions among component services. However, they focus only on the compatibility at the syntax and semantic level in an informal way, yet ignoring the dynamic behavior within services. This paper emphasizes the importance of the behavior in the compatibility verification between services and utilizes the -calculus to model the service behavior and the interaction in a formal way. Based on the formalization, it proposes a method based on the operational semantics of the -calculus to automate the verification of compatibility between two services and presents an algorithm to measure the compatibility degree quantitatively.

This paper introduces the DeltaGrid abstract execution model as a foundation for building a semantically robust execution environment for concurrent processes executing over Delta-Enabled Grid Services (DEGS). A DEGS is a Grid Service with an enhanced capability to capture incremental data changes, known as deltas, associated with service execution in the context of global processes. The abstract model contains a service composition model that provides multi-level protection against service execution failure, thus maximizing the forward recovery of a process. The model also contains a process recovery model to handle the possible impact caused by failure recovery of a process on other concurrently executing processes using data dependencies derived from a global execution history and using user-defined correctness criteria. This paper presents the abstract execution model and demonstrates its use. We also outline future directions for incorporating application exception handling and build a simulation framework for the DeltaGrid system.

This paper presents the development of a user evaluations based quality model for conceptual modeling applying the model of DeLone and McLean [6] for evaluating information systems in general. Given the growing awareness about the importance of high-quality conceptual models, it is surprising that there is no practical evaluation framework that considers the quality of conceptual models from a user’s perspective. Human factors research in conceptual modeling is still scarce and the perception of quality by model users has been largely ignored. A first research goal is therefore to determine what the appropriate dimensions are for evaluating conceptual models from a user’s perspective. Secondly, we investigate the relationships between these dimensions. Furthermore, we present the results of two experiments with 187 and 124 business students respectively, designed to test the proposed model and the generated hypotheses. The results largely support the developed model and have implications for both theory and practice of quality evaluation of conceptual models.

Selecting an appropriate process modeling language forms an important task within business process management projects. A wide range of process modeling languages has been developed over the last decades, leading to an obvious need for rigorous theory to assist in the evaluation and comparison of the capabilities of these languages. While academic progress in the area of process modeling language evaluation has been made on at least two premises, Representation Theory and Workflow Patterns, it remains unclear how these frameworks relate to each other. We use a generic framework for language evaluation to establish similarities and differences between these acknowledged reference frameworks and discuss how and to what extent they complement respectively substitute each other. Our line of investigation follows the case of the popular BPMN modeling language, whose evaluation from the perspectives of Representation Theory and Workflow Patterns is reconciled in this paper.

In this paper, we propose a quality-based use case refinement approach. It consists of a step by step refinement process that combines quality metrics with use case transformation rules. We propose several quality metrics, based on complexity concepts, aimed at measuring the complexity of use cases. Starting from an initial use case, we apply successively a set of transformation rules and measure the resulting use case based on the quality metrics. Our approach is embedded in a general framework allowing us to guide software designers by the mean of quality metrics.

Ontologies play an indispensable role in the Semantic Web by specifying the definitions of concepts and individual objects. However, most of the existing methods for constructing ontologies can only specify concepts as crisp sets. However, we cannot avoid encountering concepts that are without clear boundaries, or even vague in meanings. Therefore, existing ontology models are unable to cope with many real cases effectively. With respect to a certain category, certain objects are considered as more representative or typical. Cognitive psychologists explain this by the prototype theory of concepts. This notion should also be taken into account to improve conceptual modeling. While there has been different research attempting to handle vague concepts with fuzzy set theory, formal methods for measuring typicality of objects are still insufficient. We propose a cognitive model of concepts for ontologies, which handles both likeliness (fuzzy membership grade) and typicality of individuals. We also discuss the nature and differences between likeliness and typicality. This model not only enhances the effectiveness of conceptual modeling, but also brings the results of reasoning closer to human thinking. We believe that this research is beneficial to future research on ontological engineering in the Semantic Web.

In recent years, there has been a growing interest in approaches that employ foundational ontologies as theoretical tools for analyzing and improving conceptual modeling languages. However, some of these approaches do not always make explicit their ontological commitments. This leads to situations where criticisms resulting from the specific ontological choices made by a particular approach are generalized to the enterprise of ontology as a whole. In this paper we discuss an example of such a case involving the BWW approach. First, we make explicit the ontological commitments underlying that approach by relating it to other possible philosophical alternatives. Second, we construct an ontological theory which commits to a different philosophical position. Third, we show how the ontology proposed here can be used to provide real-world semantics and sound modeling guidelines for the modeling constructs of Attributes, Weak Entities and Datatypes. Finally, we compare the ontology proposed here with BWW, thus demonstrating its benefits.