Urban Digital Twins (UDT) represent a powerful tool to effectively make cities smart. Generally, UDTs are linked with other Digital Twins to build ecosystems where the citizen is at the heart of the ecosystem. This is why citizens should be considered first-class entities in the UDTs. At the same time, citizens’ privacy cannot be compromised. In this paper, we propose to integrate citizens’ digital twin in UDTs through their digital avatars (DAs). DAs allow exploiting citizens’ information, behavioral habits and personal preferences, while allowing them to have full control of their own data. We present our architecture that makes use of the Cloud-to-Thing Continuum to optimize available processing resources. We focus on a case study of the public transport service of the city of Malaga (Spain) and describe how we are approaching its implementation. Finally, we validate such UDT implementation through tests that evaluate its accuracy and the factors affecting its performance.

Mobile-based collaborative social computing applications represent an alternative to the server-centric models currently offered by major IT vendors, where users own the information they generate and take control over how other users access and exploit it. In this context, trust is fundamental for sharing information and making decisions based on the data collected from other users. This work develops a trust management system embedded in the Digital Avatars framework for collaborative social computing applications, using Subjective logic. It enables explicit representation and operation with trust information about both service providers (functional trust) and other users’ opinions about these providers (referral trust) in peer-to-peer environments. The proposal is specified using high- level models that can also be simulated and validated, and serve as a guide for the corresponding implementations in an existing social computing application platform. The proposed solution has been successfully applied in a collaborative carpooling system, where users need to trust other users with whom they share travels.

Abstract Data preprocessing is known to be essential to produce accurate data from which mining methods are able to extract valuable knowledge. When data constantly arrives from one or more sources, preprocessing techniques need to be adapted to efficiently handle these data streams. To help domain experts to define and execute preprocessing tasks for data streams, this paper proposes the use of active rule‐based systems and, more specifically, complex event processing (CEP) languages and engines. The main contribution of our approach is the formulation of preprocessing procedures as event detection rules, expressed in an SQL‐like language, that provide domain experts a simple way to manipulate temporal data. This idea is materialized into a publicly available solution that integrates a CEP engine with a library for online data mining. To evaluate our approach, we present three practical scenarios in which CEP rules preprocess data streams with the aim of adding temporal information, transforming features and handling missing values. Experiments show how CEP rules provide an effective language to express preprocessing tasks in a modular and high‐level manner, without significant time and memory overheads. The resulting data streams do not only help improving the predictive accuracy of classification algorithms, but also allow reducing the complexity of the decision models and the time needed for learning in some cases.

Population ageing, together with the desire to maintain an autonomous lifestyle, poses today’s societies with a challenge that technological advances can help considerably to cope with. The widespread use of smartphones and their increasing computing power and storage capacity make them the ideal tool to achieve this goal. In this paper, we present Digital Avatars, a software framework adapted to the needs of older adults who wish to preserve their lifestyle, but who require assistance through technology. Building on previous work on the People as a Service model, Digital Avatars takes advantage of a smartphone’s capabilities and services to collect information about the people who own them. To do this, it applies Complex Event Processing techniques extended with uncertainty to infer the habits, preferences, and needs of the device owner to build with them an enhanced virtual profile of the user. These virtual profiles are the mechanism for monitoring the quality of life of older adults: analyzing their patterns of activity, reminding them of medication schedules, or detecting risky situations that generate alerts to relatives, caregivers, or the community health system.

The expression and management of uncertainty, both in the information and in the operations that manipulate it, is a critical issue in those systems that work with physical environments. Measurement uncertainty can be due to several factors, such as unreliable data sources, tolerance in the measurements, or the inability to determine if a certain event has actually happened or not. In particular, this contribution focuses on the expression of one kind of uncertainty, namely the confidence on the model elements, i.e., the degree of belief that we have on their occurrence, and on how such an uncertainty can be managed and propagated through model transformations, whose rules can also be subject to uncertainty.

Distributed Software Engineering (DSE) concepts in Computer Science (or Engineering) Degrees are commonly introduced using a hands-on approach mainly consisting of teaching a particular distributed and component-based technology platform (such as Java Enterprise Edition or Microsoft .NET) and proposing the students to develop a small distributed software application with it. Though this approach provides the students with some relevant practical knowledge, we believe that it is not the most appropriate way of teaching all the concepts and particularities of DSE. Thus, in this paper we report on our experience of redesigning an initial DSE course following a model-based approach. By raising the level of abstraction we gained modularity, separation of concerns and technology independence, while making the course evolve according to the latest trends in software development methods.

Abstract Current model‐driven Web engineering approaches provide methods and compilers for the effective design and development of Web applications. However, these proposals also have some limitations, especially when it comes to exchanging model specifications or adding further concerns such as architectural styles, technology independence, or distribution. One solution to these issues is based on the possibility of making Web proposals interoperate, being able to complement each other, and to exchange models between their tools. We analyze how a common reference model shared by Web engineering proposals can be effectively used to achieve the desired interoperability. We also examine how such a common reference model can be used to combine models coming from different proposals, and discuss the problems that can occur when integrating these separate models. Finally, we show how high‐level model transformations allow to efficiently solving these problems.

Currently, Web-based applications are no longer monolithic and isolated systems but, rather, distributed applications that need to interoperate with third-party systems, such as external Web services, LDAP repositories or legacy applications. When one component provides a service that the Web application requires, it is often not possible to bind the two systems together if they were not programmed to have compatible collaboration specifications. Modeling the adaptation between a Web application and external assets becomes therefore an essential issue in any realistic model-driven development scenario. However, most of the existing Web Engineering proposals do not take this issue into account, or they simply address it at the implementation level (in a platform-specific way). In this work, we discuss the problems involved in dealing with component adaptation within the context of Model-Driven Web Engineering and show how design patterns can help addressing it. We first identify the major interoperability problems that can happen when integrating third-party application or legacy systems into our Web systems, and then propose the mechanisms that need to be put in place at the design level to generate the appropriate specification of adapters that compensate for the possible mismatches and differences. We base our proposal on well-known design patterns as they are established solutions to recurring problems, and the generation of code from them is normally straightforward.