ResumenAutomatic Verification and Diagnosis of Security Risk Assessments in Business Process ModelsVarela Vaca, Ángel Jesús; Parody, Luisa; Gasca, Rafael M.; Gómez-López, María Teresa. Actas de las XV Jornadas de Ingeniería de Ciencia e Ingeniería de Servicios (JCIS 2019), 2019-09-02.Organizations execute daily activities to meet their objectives. The performance of these activities can be fundamental for achieving a business objective, but they also imply the assumption of certain security risks that might go against a company's security policies. A risk may be defined as the effects of uncertainty on the achievement of the goals of a company, some of which can be associated with security aspects (e.g., data corruption or data leakage). The execution of the activities can be choreographed using business processes models, in which the risk of the entire business process model derives from a combination of the single activity risks (executed in an isolated manner). In this paper, the problem of automatic security risk management in the current BPMS is addresses. First, a formalization of the risk elements according to process models is included. These elements are supported as a BPMN 2.0 extension of risk information that is analyzed to determine nonconformance regarding risk goals. In addition, a diagnosis of the risk associated with the activity responsible for the nonconformance is also carried out. To this end, the proposal applies mechanisms based on the model-based diagnosis in which activities are in nonconformance with regard to the acceptable level of risk. The automation of diagnosis is carried out using artificial intelligence techniques based on constraint programming. The proposal is supported by the implementation of a plug-in that enables the graphical specification of the extension and the automation of the verification and diagnosis process. To the best of our knowledge, this is the first published work that addresses the risk-aware design of business processes with automatic techniques. ResumenTime Prediction on Multi-perspective Declarative Business ProcessesJiménez Ramírez, Andrés; Barba, Irene; Fernández-Olivares, Juan; del Valle, Carmelo; Weber, Barbara. Actas de las XV Jornadas de Ingeniería de Ciencia e Ingeniería de Servicios (JCIS 2019), 2019-09-02.Abstract. Process-aware information systems (PAISs) are increasingly used to provide flexible support for business processes. The support given through a PAIS is greatly enhanced when it is able to provide accurate time predictions which is typically a very challenging task. Predictions should be (1) multi-dimensional and (2) not based on a single process in- stance. Furthermore, the prediction system should be able to (3) adapt to changing circumstances, and (4) deal with multi-perspective declarative languages (e.g., models which consider time, resource, data and control flow perspectives). In this work, a novel approach for generating time predictions considering the aforementioned characteristics is proposed. For this, rst, a multi-perspective constraint-based language is used to model the scenario. Thereafter, an optimized enactment plan (represent- ing a potential execution alternative) is generated from such a model considering the current execution state of the process instances. Finally, predictions are performed by evaluating a desired function over this en- actment plan. To evaluate the applicability of our approach in practical settings we apply it to a real process scenario. Despite the high com- plexity of the considered problems, results indicate that our approach produces a satisfactory number of good predictions in a reasonable time. This research has been supported by the Spanish MINECO R&D Projects Pololas TIN2016-76956-C3-2-R and PLAN MINER TIN2015-71618-R. ArtículoRecomendación de actividades gamificadas basada en minería de procesosLama Penín, Manuel; Vidal Aguiar, Juan Carlos; Gallego Fontenla, Víctor José; Porto Ares, Álvaro. Actas de las XV Jornadas de Ingeniería de Ciencia e Ingeniería de Servicios (JCIS 2019), 2019-09-02.En la actualidad existe una enorme explosión en el conjunto de aplicaciones móviles cuyo fin es promover hábitos de vida saludables, y el ámbito de la salud cardiovascular no ha sido la excepción. Aunque un buen número de estas aplicaciones hacen uso de técnicas de gamificación, no hay actualmente ninguna propuesta que incluya varios juegos relacionados con los aspectos clave de la salud cardiovasular y, por lo tanto, tampoco hay ni en el ámbito académico ni el comercial ningún sistema de recomendación de actividades gamificadas para la promoción de los hábitos cardiosaludables. En este artículo, se presenta un sistema de recomendación basado en técnicas de minería de procesos que describen de forma muy precisa lo que está realizando el usuario, lo cual lleva a generar, a su vez, recomendaciones también muy precisas. ResumenOn the Relationships Between Decision Management and Performance MeasurementEstrada-Torres, Bedilia; Del Río Ortega, Adela; Resinas Arias de Reyna, Manuel; Ruiz Cortés, Antonio. Actas de las XV Jornadas de Ingeniería de Ciencia e Ingeniería de Servicios (JCIS 2019), 2019-09-02.Decisions are a key aspect of every business and its processes and their management is of utmost importance for the achievement of strategic and operational goals in any organisational context. Therefore, decisions should be considered as first-class citizens that need to be modelled, measured, analysed, monitored to track their performance, and redesigned if necessary. Existing literature studies the definition of decisions themselves in terms of accuracy, certainty, consistency, covering and correctness. However, to the best of our knowledge, no prior work exists that analyses the relationship between decisions and process performance. In this paper, we seek to improve the understanding of the relationship between decision management and process performance measurement by means of the analysis of the relationship between these two concepts in three ways. First, by analysing the impact of decisions related to business processes on process performance indicators (PPIs), and using guidelines in the form of a set of steps that can be used to identify decisions that affect the process performance. Second, by defining decision performance indicators (DPIs) to measure performance of decisions related to business processes. And third, by using process performance information in the definition of decisions. Some advantages of explicitly defining these relationships have been encountered, such as the provision of important insights regarding possible dysfunctional decisions from a performance point of view or the identification of possible actions to be taken to improve the performance. We also outline how these relationships can be modelled and supported by extending and integrating PPINOT, a metamodel for the definition and modelling of PPIs, with DMN, a standard that provides constructs to model and decouple decisions from process models.