Catálogo de publicaciones - libros

Agile software development methods are quickly being adopted by the software industry. Concerns have been raised whether agile methods are suitable for any given information systems development domain. Indeed, quite little is known empirically about the validity of agile methods in most of the industrial domains. Mobile information systems present no exception in this sense. Yet, they are subject to frequent requirements changes in terms of changing business needs and technology, and their market is highly competitive. Moreover, most of these systems are far away from so called agile home ground. This talk presents the need for agile methods in the focal domain, identifies their shortcomings on the basis of three large-scale case studies from industry. All of the cases deal with the development of mobile information system and come from Nokia, F-Secure and Philips. The talk also discusses the possible strategies for deploying agile solutions in practice.

In a series of publications, we have proposed a foundational system of ontological categories which has been used to evaluate and improve the quality of conceptual modeling languages and models. In this article, we continue this work by employing theories from Formal Ontology, Cognitive Psychology and Philosophical Logic to systematically investigate some important modal aspects of the ontological categories represented in structural conceptual models. In particular, we focus on and , formally characterizing some modal properties that motivate the proposal of a number of distinctions within these categories. In addition, we show how two types of modality known in philosophical logic ( modality) can be used to address some subtle issues that appear in conceptual diagrams when different sorts of object types and part-whole relations are combined.

Ontologies are shared conceptualizations of a domain. As this domain may change over the time, the ontology has to evolve as well. Additionally, for many applications, it is important to know which version of an ontology was valid at a certain point in time. Several ontology version management systems address this problem. If a user is confronted with different versions of an ontology it is often necessary to identify the changes. We present an efficient graph based approach for change detection between two versions of an ontology based on structural comparisons. The result is a change script transforming the old to the new version. Furthermore, we present an extensive evaluation of the prototype implementation of the change detection system.

The translation of information between heterogeneous representations is a long standing issue. With the large spreading of cooperative applications fostered by the advent of the Internet the problem has gained more and more attention but there are still few and partial solutions. In general, given an information source, different translations can be defined for the same target model. In this work, we first identify general properties that “good” translations should fulfill. We then propose novel techniques for the automatic generation of model translations. A translation is obtained by combining a set of basic transformations and the above properties are verified locally (at the transformation level) and globally (at the translation level) without resorting to an exhaustive search. These techniques have been implemented in a tool for the management of heterogeneous data models and some experimental results support the effectiveness and the efficiency of the approach.

As business collaboration involves multiple business processes from different participating organisations, it becomes a challenging issue to manage the complex correspondence between instances of these business processes. Yet very limited support has been provided by inter-organisational workflow research. In this paper, we develop a formal method to specify instance correspondence based on a novel correspondence Petri net model. In this method, cardinality parameters are defined to represent cardinality relationships between collaborating business processes at build time, while correlation structures are designed to characterise correspondence between collaborating business process instances at run time. Corresponding algorithms are also developed to generate the correspondence Petri nets for collaborative business processes, and to trace instance correlation on the fly using the generated Petri nets.

Innovative networked value constellations, such as Cisco or Dell, are often enabled by Information Technology (IT). The same holds for the Distributed Electricity Balancing Service (DBS), which we present in this case study. To explore of such constellations while designing them, we need at least to develop a and understanding of the constellation at hand. In this paper, we take a multiple perspective approach, by taking a perspective (using ) and an perspective (using UML-deployment diagrams) on the case at hand. We present a novel, structured approach to relate both perspectives, thus enabling a financial and technical feasibility assessment of the constellation, using a real-life case study in the field of electricity supply and consumption.

Interacting services are at the center of attention in business-to-business (B2B) process integration scenarios. Global interaction models specify the interaction behavior of each service and serve as contractual basis for the collaboration. Consequently, service implementations have to be consistent with the specifications. Consistency checking ensures that an implemented service is compatible with other services, i.e. that it can interact successfully with them. This is important in order to avoid deadlocks and guarantee proper termination of a collaboration. Different notions of compatibility between interacting services and consistency between specification and implementation are available but they are typically discussed independently from each other. This paper presents a unifying framework for compatibility and consistency and shows how these two notions relate to one another. Criteria for an optimal consistency relation with respect to a given compatibility relation are presented. Based on these criteria weak bi-simulation is evaluated.

Data cleaning is the process of correcting anomalies in a data source, that may for instance be due to typographical errors, or duplicate representations of an entity. It is a crucial task in customer relationship management, data mining, and data integration. With the growing amount of XML data, approaches to effectively and efficiently clean XML are needed, an issue not addressed by existing data cleaning systems that mostly specialize on relational data.

We present XClean, a data cleaning framework specifically geared towards cleaning XML data. XClean’s approach is based on a set of cleaning operators, whose semantics is well-defined in terms of XML algebraic operators. Users may specify cleaning programs by combining operators by means of a declarative XClean/PL program, which is then compiled into XQuery. We describe XClean’s operators, language, and compilation approach, and validate its effectiveness through a series of case studies.

In distributed work environments, where users are sharing and searching resources, ensuring an appropriate ranking at remote peers is a key problem. While this issue has been investigated for federated libraries, where the exchange of collection specific information suffices to enable homogeneous TFxIDF rankings across the participating collections, no solutions are known for PageRank-based ranking schemes, important for personalized retrieval on the desktop.

Connected users share fulltext resources and metadata expressing information about them and connecting them. Based on which information is shared or private, we propose several algorithms for computing personalized PageRank-based rankings for these connected peers. We discuss which information is needed for the ranking computation and how PageRank values can be estimated in case of incomplete information. We analyze the performance of our algorithms through a set of experiments, and conclude with suggestions for choosing among these algorithms.

Schema merging is the process of integrating several schemas into a common, unified schema. There have been various approaches to schema merging, focusing on particular modeling languages, or using a lightweight, abstract metamodel. Having a semantically rich representation of models and mappings is particularly important for merging as semantic information is required to resolve the conflicts encountered. Therefore, our approach to schema merging is based on the generic role-based metamodel and intensional mappings based on the real world states of model elements. We give a formal definition of the merged schema and present an algorithm implementing these formalizations.