Integración de SSN con una ontología de servicios

Los servicios en red que conocemos actualmente están basados en documentos y enlaces de hipertexto que los relacionan entre sí sin aportar verdadera información acerca de los contenidos que representan. Podría decirse que se trata de “una red diseñada por personas para ser interpretada por personas”. El objetivo principal de los últimos años es encaminar esta red hacia una web de conocimiento, en la que la información pueda ser interpretada por agentes computerizados de manera automática. Para llevar a cabo esta transformación es necesaria la utilización de nuevas tecnologías especialmente diseñadas para la descripción de contenidos como son las ontologías. Si bien las redes convencionales están evolucionando, no son las únicas que lo están haciendo. El rápido crecimiento de las redes de sensores y el importante aumento en el número de dispositivos conectados a internet, hace necesaria la incorporación de tecnologías de la web semántica a este tipo de redes. Para la realización de este Proyecto de Fin de Carrera se utilizará la ontología SSN, diseñada para la descripción semántica de sensores y las redes de las que forman parte con el fin de permitir una mejor interacción entre los dispositivos y los sistemas que hacen uso de ellos. El trabajo desarrollado a lo largo de este Proyecto de Fin de Carrera gira en torno a esta ontología, siendo el principal objetivo la generación semiautomática de código a partir de un modelo de sistemas descrito en función de las clases y propiedades proporcionadas por SSN. Para alcanzar este fin se dividirá el proyecto en varias partes. Primero se realizará un análisis de la ontología mencionada. A continuación se describirá un sistema simulado de sensores y por último se implementarán las aplicaciones para la generación automática de interfaces y la representación gráfica de los dispositivos del sistema a partir de la representación del éste en un fichero de tipo OWL. ABSTRACT. The web we know today is based on documents and hypertext links that relate these documents with each another, without providing consistent information about the contents they represent. It could be said that its a network designed by people to be used by people. The main goal of the last couple of years is to guide this network into a web of knowledge, where information can be automatically processed by machines. This transformation, requires the use of new technologies specially designed for content description such as ontologies. Nowadays, conventional networks are not the only type of networks evolving. The use of sensor networks and the number of sensor devices connected to the Internet is rapidly increasing, making the use the integration of semantic web technologies to this kind of networks completely necessary. The SSN ontology will be used for the development of this Final Degree Dissertation. This ontology was design to semantically describe sensors and the networks theyre part of, allowing a better interaction between devices and the systems that use them. The development carried through this Final Degree Dissertation revolves around this ontology and aims to achieve semiautomatic code generation starting from a system model described based on classes and properties provided by SSN. To reach this goal, de Dissertation will be divided in several parts. First, an analysis about the mentioned ontology will be made. Following this, a simulated sensor system will be described, and finally, the implementation of the applications will take place. One of these applications will automatically generate de interfaces and the other one will graphically represents the devices in the sensor system, making use of the system representation in an OWL file

Implementation of a mindfulness-based crisis intervention for frontline healthcare workers during the COVID-19 outbreak in a public general hospital in Madrid, Spain

Introduction: The COVID-19 outbreak is having an impact on the well-being of healthcare workers. Mindfulness-based interventions have shown effectiveness in reducing stress and fostering resilience and recovery in healthcare workers. There are no studies examining the feasibility of brief mindfulness-based interventions during the COVID-19 outbreak. Materials and Methods: This is an exploratory study with a post intervention assessment. We describe an on-site brief mindfulness intervention and evaluate its helpfulness, safety, and feasibility. Results: One thousand out of 7,000 (14%) healthcare workers from La Paz University Hospital in Madrid (Spain) participated in at least one session. One hundred and fifty out of 1,000 (15%) participants filled out a self-report questionnaire evaluating the helpfulness of the intervention for on-site stress reduction. Ninety two subjects (61%) participated in more than one session. Most of the participants were women (80%) with a mean age of 38.6 years. Almost half of the sample were nurses (46%). Sessions were perceived as being helpful with a mean rating of 8.4 on a scale from 0 to 10. Only 3 people (2%) reported a minor adverse effect (increased anxiety or dizziness). Discussion: Our data supports the utility, safety and feasibility of an on-site, brief mindfulness-based intervention designed to reduce stress for frontline health workers during a crisis. There is a need to continue testing this type of interventions, and to integrate emotion regulation strategies as an essential part of health workers' general training. Clinical Trial Registration number: NCT04555005