Artículos (Lenguajes y Sistemas Informáticos)
URI permanente para esta colecciónhttps://hdl.handle.net/11441/11392
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Artículo Técnicas Big Data para la predicción de la demanda y precio eléctrico(Ministerio de Industria, Turismo y Comercio, 2024) Melgar García, Laura; Torres Maldonado, José Francisco; Troncoso, Alicia; Riquelme Santos, José Cristóbal; Universidad de Sevilla. Departamento de Lenguajes y Sistemas InformáticosEn la actualidad, la electricidad es un pilar indispensable en el día a día de la sociedad. De hecho, es calificada como uno de los indicadores más importantes para medir el nivel tecnológico e industrial de desarrollo de un país [1]. La concienciación sobre su uso de forma sostenible y responsable está siendo uno de los retos más importantes de las últimas décadas. Concretamente, en términos de energía, en [2] se describe la eficiencia energética como el factor de mitigación principal para rebajar el crecimiento del consumo energético, siendo éste crucial para el desarrollo sostenible.Artículo Benchmarking machine learning approaches to predict radiation-induced toxicities in lung cancer patients(Elsevier Ireland, 2023-07) Núñez-Benjumea, F.J.; González-García, Sara; Moreno-Conde, A.; Riquelme Santos, José Cristóbal; López-Guerra, J.L.; Universidad de Sevilla. Departamento de Lenguajes y Sistemas Informáticos; Unión Europea; Conserjería de Salud Junta de AndalucíaBackground and purpose: Radiation-induced toxicities are common adverse events in lung cancer (LC) patients undergoing radiotherapy (RT). An accurate prediction of these adverse events might facilitate an informed and shared decision-making process between patient and radiation oncologist with a clearer view of life-balance implications in treatment choices. This work provides a benchmark of machine learning (ML) approaches to predict radiation-induced toxicities in LC patients built upon a real-world health dataset based on a generalizable methodology for their implementation and external validation. Materials and Methods: Ten feature selection (FS) methods were combined with five ML-based classifiers to predict six RT-induced toxicities (acute esophagitis, acute cough, acute dyspnea, acute pneumonitis, chronic dyspnea, and chronic pneumonitis). A real-world health dataset (RWHD) built from 875 consecutive LC patients was used to train and validate the resulting 300 predictive models. Internal and external accuracy was calculated in terms of AUC per clinical endpoint, FS method, and ML-based classifier under analysis. Results: Best performing predictive models obtained per clinical endpoint achieved comparable performances to methods from state-of-the-art at internal validation (AUC ≥ 0.81 in all cases) and at external validation (AUC ≥ 0.73 in 5 out of 6 cases). Conclusion: A benchmark of 300 different ML-based approaches has been tested against a RWHD achieving satisfactory results following a generalizable methodology. The outcomes suggest potential relationships between underrecognized clinical factors and the onset of acute esophagitis or chronic dyspnea, thus demonstrating the potential that ML-based approaches have to generate novel data-driven hypotheses in the field.Artículo E-SCORE: A web-based tool for security requirements engineering(Elsevier, 2024-05) Hnaini, Hiba; Mazo, Raúl; Champeau, Joël; Vallejo, Paola; Galindo Duarte, José Ángel; Universidad de Sevilla. Departamento de Lenguajes y Sistemas InformáticosAs digital systems continue to grow in popularity, they also become more vulnerable to various forms of attacks with various motives, including financial gain and political influence. In response, engineers must consider system security from the design phase. However, defining security requirements at this stage can be challenging. To address this challenge, we propose E-SCORE, a web-based tool that streamlines the security requirements engineering process. E-SCORE implements the SCORE (Security Criteria Ontology for security Requirements Engineering) (i) to suggest security mechanisms and additional criteria to enhance security coverage and (ii) to facilitate security analysis of the system. An example of banking system usage is provided. Through our approach, we could define ten additional security requirements for a single requirement. Therefore, E-SCORE offers a valuable resource for engineers to ensure the security of digital systems across various domainsPonencia Evaluation of synthetically generated traces towards a data-centre digital twin(European Council for Modelling and Simulation, 2023) Fernández Montes González, Alejandro; Fernández Cerero, Damián; Jakóbik, Agnieszka; Bermejo, Belén; Juiz, Carlos; Universidad de Sevilla. Departamento de Lenguajes y Sistemas InformáticosSeveral approaches exist to generate synthetic data centre traces for various purposes: from augmenting operational traces for data centre simulators and digital twins to forecasting incoming workload to improve data centre behaviour. The evaluation of the quality of synthetically generated multivariate time-series datasets, such as those related to data-centre traces, is not a trivial task, since complex patterns and correlation between variables may be present. This paper proposes a new multivariate time-series evaluation framework that computes a set of metrics and figures that can be used to measure the quality of synthetically generated data-centre traces. We then employ the proposed tool to compare two synthetic data centre traces with the original trace and assess their quality. These synthetic traces have been generated by means of Generative Adversarial Networks (GAN). In this work, we employ TimeGAN, a GAN model focused on the generation of multivariate time series traces. We finally show how the proposed framework provides us with a set of metrics consistent with the observable behaviour and numerical insights on the quality of the generated data centre traces, which are hard to acquire otherwise.Artículo On the design of an advanced business rule engine(John Wiley & Sons, 2022) Jiménez Aguirre, Patricia; Corchuelo Gil, Rafael; Universidad de Sevilla. Departamento de Lenguajes y Sistemas InformáticosBusiness rules govern how well-managed companies perform every day. They are expected to be written in natural language because they are devised by business people. That makes it difficult to translate them automatically into executable rules that can be integrated into typical information systems. Our industrial and academic research concludes that the current tools have a number of problems, namely: many of them do not pay any attention to the SBVR standard; some of them are not multi- language; most of them cannot achieve perfect parsing accuracy; some of them are not domain agnostic; some of them use proprietary technologies; some of them do not produce executable rules; and none supports exploratory what-if analyses natively. In this article, we present Tier-Rules, which is a system that overcomes the previous problems.We also report on an industrial case study that helps illustrate it in practice.Artículo Special issue on advanced practices in web engineering 2021(Rinton Press, 2021) Olivero González, Miguel Ángel; González Enríquez, José; Jiménez Ramírez, Andrés; Universidad de Sevilla. Departamento de Lenguajes y Sistemas InformáticosNovelty in Web Engineering arises when this area is jointly applied with other emerging and innovative ones. The transference of Web Engineering research results to industrial applications is quick due to the extensive domains of applications that this area of knowledge has. Each year there are more and more users appealing for it. Consequently, the users’ expectations and demands on this area are higher and higher. Thus, the ability of researchers and developers to adopt advanced practices and adapt to innovative approaches within Web Engineering has a tremendous and direct impact on society. This special issue contains a selection of advanced practices on Web Engineering, according to their relevance and novelty. Six studies have been considered as highly relevant for the convenient development of actual webbased applications. Such selection has been organized into three main areas based on the focus of each study. These areas are: Software Development, Applied Technologies, and Linguistic Approaches.Artículo Development of a liver graft assessment expert machine-learning system: when the artificial intelligence helps liver transplant surgeons(Frontiers Media, 2024) Pontes Balanza, Beatriz; Castillo Tuñón, Juan M.; Mateos García, Daniel; Padillo Ruiz, Francisco Javier; Riquelme Santos, José Cristóbal; Álamo Martínez, José María; Bernal Bellido, Carmen; Suárez Artacho, Gonzalo; Cepeda Franco, Carmen; Gómez Bravo, Miguel Ángel; Marín Gómez, Luis Miguel; Universidad de Sevilla. Departamento de Lenguajes y Sistemas Informáticos; Universidad de Sevilla. Departamento de CirugíaThe complex process of liver graft assessment is one point for improvement in liver transplantation. The main objective of this study is to develop a tool that supports the surgeon who is responsible for liver donation in the decisionmaking processwhether to accept a graft or not using the initial variables available to it. Material andmethod: Liver graft samples candidate for liver transplantation after donor brain death were studied. All of them were evaluated “in situ” for transplantation, and those discarded after the “in situ” evaluation were considered as no transplantable liver grafts, while those grafts transplanted after “in situ” evaluation were considered as transplantable liver grafts. First, a single-center, retrospective and cohort study identifying the risk factors associated with the no transplantable group was performed. Then, a prediction model decision support system based on machine learning, and using a tree ensemble boosting classifier that is capable of helping to decide whether to accept or decline a donor liver graft, was developed. Results: A total of 350 liver grafts that were evaluated for liver transplantation were studied. Steatosis was the most frequent reason for classifying grafts as no transplantable, and the main risk factors identified in the univariant study were age, dyslipidemia, personal medical history, personal surgical history, bilirubinemia, and the result of previous liver ultrasound (p < 0.05). When studying the developed model, we observe that the best performance reordering in terms of accuracy corresponds to 76.29% with an area under the curve of 0.79. Furthermore, the model provides a classification together with a confidence index of reliability, for most cases in our data, with the probability of success in the prediction being above 0.85. Conclusion: The tool presented in this study obtains a high accuracy in predicting whether a liver graft will be transplanted or deemed non-transplantable based on the initial variables assigned to it. The inherent capacity for improvement in the system causes the rate of correct predictions to increase as new data are entered. Therefore, we believe it is a tool that can help optimize the graft pool for liver transplantation.Artículo UVLHub: A feature model data repository using UVL and open science principles(Elsevier, 2024-10) Romero Organvidez, David; Galindo Duarte, José Ángel; Sundermann, Chico; Horcas Aguilera, José Miguel; Benavides Cuevas, David Felipe; Universidad de Sevilla. Departamento de Lenguajes y Sistemas InformáticosFeature models are the de facto standard for modelling variabilities and commonalities in features and relationships in software product lines. They are the base artefacts in many engineering activities, such as product configuration, derivation, or testing. Concrete models in different domains exist; however, many are in private or sparse repositories or belong to discontinued projects. The dispersion of knowledge of feature models hinders the study and reuse of these artefacts in different studies. The Universal Variability Language (UVL) is a community effort textual feature model language that promotes a common way of serializing feature models independently of concrete tools. Open science principles promote transparency, accessibility, and collaboration in scientific research. Although some attempts exist to promote feature model sharing, the existing solutions lack open science principles by design. In addition, existing and public feature models are described using formats not always supported by current tools. This paper presents UVLHub, a repository of feature models in UVL format. UVLHub provides a front end that facilitates the search, upload, storage, and management of feature model datasets, improving the capabilities of discontinued proposals. Furthermore, the tool communicates with Zenodo – one of the most well-known open science repositories – providing a permanent save of datasets and following open science principles. UVLHub includes existing datasets and is readily available to include new data and functionalities in the future. It is maintained by three active universities in variability modelling.Artículo PDSS: A pharmacological decision support system for diabetics patients with COVID-19(IO Press, 2023) Amaya-Rodríguez, Isabel; Larburu, Nekane; Martinez-Herrera, María Rollán; Rebescher, Kristin; Macia, Iván; Armengol de la Hoz, Miguel Ángel; Rubio Escudero, Cristina; Garín-Muga, Alba; Universidad de Sevilla. Departamento de Lenguajes y Sistemas InformáticosWith the advent of SARS-CoV-2, several studies have shown that there is a higher mortality rate in patients with diabetes and, in some cases, it is one of the side effects of overcoming the disease. However, there is no clinical decision support tool or specific treatment protocols for these patients. To tackle this issue, in this paper we present a Pharmacological Decision Support System (PDSS) providing intelligent decision support for COVID-19 diabetic patient treatment selection, based on an analysis of risk factors with data from electronic medical records using Cox regression. The goal of the system is to create real world evidence including the ability to continuously learn to improve clinical practice and outcomes of diabetic patients with COVID-19.Artículo Introducing Joint Modeling Techniques for Personalized Predictions in Celiac Disease(Elsevier INC, 2022) Serrano, Lidia; Rodriguez-Herrera, Alfonso; Serrat, Carles; Rubio Escudero, Cristina; Universidad de Sevilla. Departamento de Lenguajes y Sistemas InformáticosIf following a strict gluten-free diet in newly Celiac Disease (CD) antibodies titers are not declining, it may mean an active disease ongoing. As per guidelines additional invasive and costly tests use to be requested then. Disease progression, however, differs among patients, changing dynamically over time for the same individual. Current followup guidelines are in fashion of “one size fits all” and do not consider individual variations in the antibodies profile. We aim to tailored follow up interventions by identification of personalized predictive profiles.Artículo Semi-real-time decision tree ensemble algorithms for very short-term solar irradiance forecasting(Elsevier, 2024) Sánchez López, José Enrique; Solís García, Javier; Riquelme Santos, José Cristóbal; Universidad de Sevilla. Departamento de Lenguajes y Sistemas Informáticos; MCIU/AEI/10.13039/501100011033Industrial activities are transitioning towards decarbonization, focusing on renewable energy sources, particularly photovoltaic solar energy. However, the inherent high variability of photovoltaic energy poses challenges. Some of them can be partially addressed by predicting electricity production, which in the case of photovoltaic solar energy is heavily based on solar irradiance prediction. Although extensive research has been conducted in this field, there is a noticeable gap in research regarding very short-term (intra-minute) forecasting under high-variability scenarios. In this proposal, real data from a photovoltaic solar plant in Alderville (Canada) were used to predict irradiance with a horizon of 15 and 30 s. The objective is to make this prediction in near-real time. To achieve this, we propose the use of machine learning algorithms based on decision tree ensembles, due to their low computational training cost and known effectiveness. On the other hand, we propose preprocessing the data through a temporal and spatial correlation analysis between measurements from different sensors. Feature selection analysis allows us to determine the direction of the wind and consequently identify the most relevant panels for model training. This preprocessing enhances the model retraining without the need for external information such as sky images or wind speed and direction on days with highly variable cloud cover. The presented methodology offers promising results with significantly reduced training times, demonstrating the suitability of this semi-online training approach for highly variable time series forecasting.Artículo Análisis de la tasa de abandono en un Centro con varios Grados en Ingeniería Informática(2017) Ruiz Cortés, David; Gómez Rodríguez, Francisco de Asís; Ruiz Reina, José Luis; Universidad de Sevilla. Departamento de Lenguajes y Sistemas Informáticos; Universidad de Sevilla. Departamento de Arquitectura y Tecnología de Computadores; Universidad de Sevilla. Departamento de Ciencias de la Computación e Inteligencia ArtificialEn este trabajo se muestra el análisis realizado del impacto que sobre la tasa de abandono tiene el cambio de estudios entre los tres Grados en Ingeniería Informática que se imparten en un Centro concreto. Dicho análisis ha sido llevado a cabo por el Equipo de Dirección del Centro a instancia de los informes realizados tras las visitas para la renovación de la acreditación de dichos títulos. Las principales conclusiones a las que hemos llegado son: i) el cambio de estudios entre Grados en Informática siempre tiene un efecto negativo sobre la tasa de abandono, oscilando este entre el 3% y el 20 %; ii) dicho cambio de estudios puede responder a cuestiones académicas en algunos casos, pero también se apuntan cuestiones económicas por el ahorro que puede llegar a suponer; iii) aproximadamente un tercio de nuestros estudiantes abandona los estudios en Ingeniería Informática; iv) la tasa de abandono a lo largo de los últimos 5 años se ha mantenido acorde con lo establecido en las memorias de verificación y conforme a la media nacional en la rama de conocimiento de Ingeniería y Arquitectura; v) los sistemas de indicadores definidos por los distintos sistemas de garantía de calidad de los Títulos en ocasiones no son homogéneos, lo que dificulta realizar cualquier tipo de análisis.Artículo Variability management and software product line knowledge in software companies(Elsevier, 2024) Gutiérrez Fernández, Antonio Manuel; Chacón Luna, Ana Eva; Benavides Cuevas, David Felipe; Fuentes, Lidia; Rabiser, Rick; Universidad de Sevilla. Departamento de Lenguajes y Sistemas InformáticosSoftware product line engineering aims to systematically generate similar products or services within a given domain to reduce cost and time to market while increasing reuse. Various studies recognize the success of product line engineering in different domains. Software variability have increased over the years in many different domains such as mobile applications, cyber–physical systems or car control systems to just mention a few. However, software product line engineering is not as widely adopted as other software development technologies. In this paper, we present an empirical study conducted through a survey distributed to many software development companies. Our goal is to understand their need of software variability management and the level of knowledge the companies have regarding software product line engineering. The survey was answered by 127 participants from more than a hundred of different software development companies. Our study reveals that most of companies manage a catalog of similar products in a way or another (e.g. cloneand- own, common modules that are statically imported,etc.), they mostly document the features of products using text or spreed sheet based documents and more than 66% of companies identify a base product from which they derive other similar products. We also found a correlation between the lack of Software Product Line (SPL) knowledge and the absence of reuse practices. Notably, this is the first study that explore software variability needs regardless of a company’s prior knowledge of SPL. The results encourages further research to understand the reason for the limited knowledge and application of software product line engineering practices, despite the growing demand of variability management.Artículo Testing of highly configurable cyber-physical systems-Results from a two-phase multiple case study(Elsevier, 2023) Fischer, Stephan; Gutiérrez Fernández, Antonio Manuel; Gutiérrez Fernández, Antonio Manuel; Rabiser, R.; Ramler, R.; Universidad de Sevilla. Departamento de Lenguajes y Sistemas InformáticosCyber–physical systems are commonly highly configurable. Testing such systems is particularly challenging because they comprise numerous heterogeneous components that can be configured and combined in different ways. Despite a plethora of work investigating software testing in general and software product line testing in particular, variability in tests and how it is applied in industry with cyber–physical systems is not well understood. In this paper, we report on a multiple case study with four companies maintaining highly configurable cyber–physical systems focusing on their testing practices, with a particular focus on variability. Based on the results of the multiple case study, we conducted an interactive survey with experienced engineers from eight companies, including the initial four. We reflect on the lessons learned from the multiple case study. We conclude that experiencebased selection of configurations for testing is currently predominant. We learned that variability modeling techniques and tools are not utilized and the dependencies between configuration options are only partially modeled at best using custom artifacts such as spreadsheets or configuration files. Another finding is that companies have the need and desire to cover more configuration combinations by automated tests. Our findings raise many questions interesting to the scientific community and motivating future research.Ponencia Dynamic Product Configuration User Interface: A Vision Motivated by the Cyber-Physical Production Systems Domain(Association for Computing Machinery, 2023) Fadhlillah, Hafiyyan Sayyid; Feichtinger, Kevin; Gutiérrez Fernández, Antonio Manuel; Rabiser, Rick; Universidad de Sevilla. Departamento de Lenguajes y Sistemas InformáticosCyber-Physical Production Systems (CPPSs) are large-scale industrial systems in which hardware and software are deeply intertwined. CPPS software has to be highly variable to support frequently changing customer and hardware requirements. Managing the overall variability of such large-scale industrial software is challenging. Knowledge from diverse engineering disciplines, e.g., mechatronics, process, electrical, and control software engineering, is required to support product configuration. These disciplines use diverse artifacts and tools. It is infeasible to have one common variability model or one common configuration user interface representing variability knowledge from diverse disciplines in CPPSs. Therefore, in this paper, we propose the idea of a dynamic product configuration user interface, which decouples the product configuration process from the user interface based on an existing multidisciplinary variability management approach for CPPSs. We describe the next steps toward implementing and evaluating our idea.Artículo Bad Smells in Steuerungssoftware für automatisierte Produktionssysteme(2023) Sonnleithner, Lisa; Gutiérrez Fernández, Antonio Manuel; Rabiser, Rick; Zoitl, Alois; Universidad de Sevilla. Departamento de Lenguajes y Sistemas InformáticosBad Smells sind suboptimale Strukturen oder Muster in Software, die zu einer Verschlechterung der Softwarequalität führen können, da sie unter anderem Wartungsprobleme verursachen und die Verständlichkeit erschweren können. Um das Auftreten dieser Probleme zu vermeiden, ist es deshalb wichtig, Bad Smells in Software erkennen und beheben zu können. Im Software Engineering ist das Thema Bad Smells bereits gut erforscht. Für IEC 61499-basierte Steuerungsoftware, die in automatisierten Produktionssystemen verwendet wird, gibt es jedoch erst wenige Arbeiten zu diesem wichtigen Thema.Artículo Ayuda para enseñar "Scrum" con o sin programar(2022) Gutiérrez Rodríguez, Javier Jesús; Gracia Ahufinger, Francisco; Universidad de Sevilla. Departamento de Lenguajes y Sistemas Informáticos; Agencia Estatal de Investigación (AEI)Scrum es una de las propuestas más utilizadas en el desarrollo de software y forma parte de la mayoría de los temarios de carreras relacionadas con las tecnologías de la información. En el 2020 realizamos un estudio sobre cómo se enseñaba Scrum en las universidades a partir de artículos publicados en JENUI. Las conclusiones nos motivaron a presentar las principales dificultades a la hora de enseñar Scrum, y un conjunto de puntos y sugerencias para enseñar Scrum al alumnado completamente alineada con la documentación oficial de Scrum. Además, compartimos nuestras propias experiencias enseñando Scrum en más de una década. Los resultados sirven de guía para la preparación de la docencia de Scrum en asignaturas que impliquen actividades de programación y en las que no tengan estas actividades.Artículo A Gamification Method for Improving the Onboarding Process of Software Engineers(IEEE, 2024) Ruiz, Mercedes; Orta, Elena; Gutiérrez Rodríguez, Javier Jesús; Universidad de Sevilla. Departamento de Lenguajes y Sistemas Informáticos; European Regional DevelopmentIn software engineering, the onboarding process of new software engineers is crucial. The primary goal of this process is to ensure that professionals gain the necessary knowledge and skills to comprehend the company’s culture, integrate into the organization, and perform their activities effectively. Enhancing corporate learning processes and addressing human aspects, such as motivation, engagement, and commitment, are among the key factors influencing the success of the onboarding process. Gamification—the use of game elements in nongame contexts—has been widely employed in different contexts to promote positive changes in people’s behavior and increase their engagement and performance. We consider the integration of gamification into the onboarding process an interesting field of study and research. In this work, we propose a novel method for gamifying the onboarding process and introduce an application case within an organizational context.Artículo Validating Force Sensitive Resistor Strip Sensors for Cardiorespiratory Measurement during Sleep: A Preliminary Study(MDPI, 2023-04-13) Haghi, Mostafa; Asadov, Akhmadbek; Boiko, Andrei; Ortega Ramírez, Juan Antonio; Martínez Madrid, Natividad; Seepold, Ralf; Universidad de Sevilla. Departamento de Lenguajes y Sistemas InformáticosSleep disorders can impact daily life, affecting physical, emotional, and cognitive well-being. Due to the time-consuming, highly obtrusive, and expensive nature of using the standard approaches such as polysomnography, it is of great interest to develop a noninvasive and unobtrusive in-home sleep monitoring system that can reliably and accurately measure cardiorespiratory parameters while causing minimal discomfort to the user’s sleep. We developed a low-cost Out of Center Sleep Testing (OCST) system with low complexity to measure cardiorespiratory parameters. We tested and validated two force-sensitive resistor strip sensors under the bed mattress covering the thoracic and abdominal regions. Twenty subjects were recruited, including 12 males and 8 females. The ballistocardiogram signal was processed using the 4th smooth level of the discrete wavelet transform and the 2nd order of the Butterworth bandpass filter to measure the heart rate and respiration rate, respectively. We reached a total error (concerning the reference sensors) of 3.24 beats per minute and 2.32 rates for heart rate and respiration rate, respectively. For males and females, heart rate errors were 3.47 and 2.68, and respiration rate errors were 2.32 and 2.33, respectively. We developed and verified the reliability and applicability of the system. It showed a minor dependency on sleeping positions, one of the major cumbersome sleep measurements. We identified the sensor under the thoracic region as the optimal configuration for cardiorespiratory measurement. Although testing the system with healthy subjects and regular patterns of cardiorespiratory parameters showed promising results, further investigation is required with the bandwidth frequency and validation of the system with larger groups of subjects, including patients.Artículo La COVID-19 y los desafíos de la vigilancia digital para los derechos humanos: a propósito de la app DataCOVID prevista en la Orden Ministerial SND/29/2020, de 27 de marzo(Observatori de Bioètica i Dret - Cátedra UNESCO de Bioética, 2020) Márquez Carrasco, María del Carmen; Ortega Ramírez, Juan Antonio; Universidad de Sevilla. Departamento de Lenguajes y Sistemas Informáticos; Universidad de Sevilla. Departamento de Derecho Internacional Público y Relaciones InternacionalesLa pandemia de la COVID-19 ha demostrado la fragilidad del mundo globalizado y se está combatiendo mediante una combinación de técnicas y herramientas de ámbitos muy diferentes, desde clínico hasta tecnológico. La aplicación de las nuevas tecnologías ha suscitado el actual gran debate europeo sobre la privacidad. Una de sus manifestaciones es la Orden SND/29/2020, de 27 de marzo, del Ministerio de Sanidad, en la que se prevé el desarrollo de la app DataCOVID de seguimiento digital. Este trabajo tiene por objeto examinar la legalidad y alcance de estas medidas desde la perspectiva del respeto al derecho a la privacidad en el marco de las garantías para los derechos humanos y la protección de datos.