Creation of a consulting tool and implementation of an ontology for a Master’s Degree Program in Computer Sciences

In this paper, a manual ontology for a Computer Sciences Master program constructed, that uses some elements from the METHONTOLOGY, Grüninger and Fox, and Bravo’s methodologies, is presented. A series of steps to identify and represent the Master’s Degree program’s knowledge base has been followed. Afterwards, first order logic axioms and competency questions to evaluate the ontology are used. The development of a module written in Python language is used for evaluating the ontology through competency questions defined during design phase. This module is flexible enough to present predefined or defined questions by the user in running time and to obtain results to the queries representing the competency questions. Elements as a hierarchy class diagram and a description of the relations and attributes are used in this ontology’s construction

Implementación de una Ontología y herramienta de consulta para un programa de Maestría en Ciencias de la Computación

In this paper, a manual ontology for a Computer Sciences Master program constructed, that uses some elements from the METHONTOLOGY, Grüninger and Fox, and Bravo’s methodologies, is presented. A series of steps to identify and represent the Master’s Degree program’s knowledge base has been followed. Afterwards, first order logic axioms and competency questions to evaluate the ontology are used. The development of a module written in Python language is used for evaluating the ontology through competency questions defined during design phase. This module is flexible enough to present predefined or defined questions by the user in running time and to obtain results to the queries representing the competency questions. Elements as a hierarchy class diagram and a description of the relations and attributes are used in this ontology’s construction.En este artículo, es representada una ontología manual para un programa de Maestría en Ciencias de la Computación construida con algunos elementos de las metodologías METHONTOLOGY, Grüninger y Fox, y Bravo. Se ha seguido un conjunto de pasos para identificar y representar la base del conocimiento del programa de Maestría, posteriormente son utilizados axiomas lógicos de primer orden y preguntas de competencia para evaluar la ontología. El desarrollo de un módulo en lenguaje Python es utilizado para la evaluación de la ontología a través de las preguntas de competencia definidas en la fase de diseño. Este módulo es lo suficientemente flexible para presentar preguntas predefinidas o definidas por el usuario en tiempo de ejecución y obtener resultados a las consultas que representan las preguntas de competencia. Elementos como el diagrama de jerarquía de clases y descripción de las relaciones y atributos son utilizados en la construcción de la ontología

Aprendizaje ontológico para el dominio de desórdenes del habla

“El presente proyecto consiste en la realización de una Ontología que representa el dominio de los desórdenes del habla en niños con la finalidad de ser una herramienta de soporte a los terapeutas para el diagnóstico y posible tratamiento de los desórdenes antes mencionados. Los desórdenes del habla serán clasificados utilizando una taxonomía obtenida de un corpus de desórdenes del habla previamente conformado utilizando técnicas de Procesamiento de Lenguaje Natural (PLN) y Recuperación de Información (RI). Basada en esta taxonomía, la ontología, la cual estructura y formaliza conceptos definidos por los principales autores del tema, es desarrollada. Las clases principales de la ontología representan la clasificación taxonómica de los desórdenes del habla, su origen etiológico, síntomas y signos de cada desorden, y estrategias de evaluación e intervención; también están representados los pacientes y terapeutas como instancias. La importancia de una detección y diagnóstico temprano de un desorden del habla -que puede tener un impacto social, económico y educativo, radica en que el pronóstico del tratamiento depende de la causa del trastorno y de un tratamiento oportuno.”

Creation of a consulting tool and implementation of an ontology for a Master’s Degree Program in Computer Sciences

In this paper, a manual ontology for a Computer Sciences Master program constructed, that uses some elements from the METHONTOLOGY, Grüninger and Fox, and Bravo’s methodologies, is presented. A series of steps to identify and represent the Master’s Degree program’s knowledge base has been followed. Afterwards, first order logic axioms and competency questions to evaluate the ontology are used. The development of a module written in Python language is used for evaluating the ontology through competency questions defined during design phase. This module is flexible enough to present predefined or defined questions by the user in running time and to obtain results to the queries representing the competency questions. Elements as a hierarchy class diagram and a description of the relations and attributes are used in this ontology’s construction.En este artículo, es representada una ontología manual para un programa de Maestría en Ciencias de la Computación construida con algunos elementos de las metodologías METHONTOLOGY, Grüninger y Fox, y Bravo. Se ha seguido un conjunto de pasos para identificar y representar la base del conocimiento del programa de Maestría, posteriormente son utilizados axiomas lógicos de primer orden y preguntas de competencia para evaluar la ontología. El desarrollo de un módulo en lenguaje Python es utilizado para la evaluación de la ontología a través de las preguntas de competencia definidas en la fase de diseño. Este módulo es lo suficientemente flexible para presentar preguntas predefinidas o definidas por el usuario en tiempo de ejecución y obtener resultados a las consultas que representan las preguntas de competencia. Elementos como el diagrama de jerarquía de clases y descripción de las relaciones y atributos son utilizados en la construcción de la ontología

Una arquitectura para la búsqueda facetada del compendio de actividad física

The implementation of a faceted search system of the Official Compendium of Physical Activities is presented. The compendium of physical activity is a tool widely used in population studies on sedentary lifestyle and physical activity since it offers a classification of physical activities by type of activity, intensity and corresponding energy expenditure in MET. The proposed strategy improves the search for activities in the compendium and with this facilitates its use by physical trainers, treating physicians and users in general.Se presenta la implementación de un sistema de búsqueda facetada del Compendio Oficial de Actividades Físicas. El compendio de actividad física es una herramienta muy utilizada en los estudios poblacionales sobre sedentarismo y actividad física ya que ofrece una clasificación de las actividades físicas por tipo de actividad, intensidad y el gasto energético correspondiente en MET. La estrategia propuesta mejora la búsqueda de actividades en el compendio y con esto facilita su uso por entrenadores físicos, médicos tratantes y usuarios en general

Use of Different Food Classification Systems to Assess the Association between Ultra-Processed Food Consumption and Cardiometabolic Health in an Elderly Population with Metabolic Syndrome (PREDIMED-Plus Cohort)

The PREDIMED-Plus trial was supported by the European Research Council (Advanced Research grant 2014–2019; agreement #340918; granted to M.Á.M.-G.); the official Spanish institutions for funding scientific biomedical research, CIBER Fisiopatología de la Obesidad y Nutrición (CIBEROBN) and Instituto de Salud Carlos III (ISCIII) through the Fondo de Investigación para la Salud (FIS) which is co-funded by the European Regional Development Fund (coordinated FIS projects led by J.S-S. and J.V., including the following projects: PI13/00673, PI13/00492, PI13/00272, PI13/01123, PI13/00462, PI13/00233, PI13/02184, PI13/00728, PI13/01090, PI13/01056, PI14/01722, PI14/00636, PI14/00618, PI14/00696, PI14/01206, PI14/01919, PI14/00853, PI14/01374, PI14/00972, PI14/00728, PI14/01471, PI16/00473, PI16/00662, PI16/01873, PI16/01094, PI16/00501, PI16/00533, PI16/00381, PI16/00366, PI16/01522, PI16/01120, PI17/00764, PI17/01183, PI17/00855, PI17/01347, PI17/00525, PI17/01827, PI17/00532, PI17/00215, PI17/01441, PI17/00508, PI17/01732, PI17/00926, PI19/00957, PI19/00386, PI19/00309, PI19/01032, PI19/00576, PI19/00017, PI19/01226, PI19/00781, PI19/01560, PI19/01332), and the Especial Action Project “Implementación y evaluación de una intervención intensiva sobre la actividad física Cohorte PREDIMED-Plus” (J.S.-S.); the Recercaixa (grant number 2013ACUP00194) (J.S.-S.). Moreover, J.S-S. gratefully acknowledges the financial support by ICREA under the ICREA Academia program; the SEMERGEN grant; Department of Health of the Government of Navarra (61/2015), the Fundació La Marató de TV (Ref. 201630.10); the AstraZeneca Young Investigators Award in Category of Obesity and T2D 2017 (D.R.); grants from the Consejería de Salud de la Junta de Andalucía (PI0458/2013; PS0358/2016; PI0137/2018), the PROMETEO/2017/017 grant from the Generalitat Valenciana, the SEMERGEN grant; grant of support to research groups 35/2011 (Balearic Islands Government; FEDER funds) (J.A.T.). R.S.-C. acknowledges financial support from the Juan de la Cierva Program Training Grants of the Spanish State Research Agency of the Spanish Ministerio de Ciencia e Innovación y Ministerio de Universidades (FJC2018-038168- I). N.B.-T. acknowledges financial support from the Juan de la Cierva Formación Program Training Grants of the Spanish State Research Agency of the Spanish Ministerio de Ciencia e Innovación y Ministerio de Universidades (FJC2018-036016-I). M.R.B.-L. was supported by “Miguel Servet Type I” program (CP15/00028) from the ISCIII-Madrid (Spain), cofinanced by the Fondo Europeo de Desarrollo Regional-FEDER. S.K.N. acknowledges financial support from the Canadian Institute for Health Research, CIHR Fellowship. J.K. was supported by the ‘FOLIUM’ programme within the FUTURMed project from the Fundación Instituto de Investigación Sanitaria Illes Balears (financed by 2017 annual plan of the sustainable tourism tax and at 50% with charge to the ESF Operational Program 2014–2020 of the Balearic Islands. C.M.-P. was financially supported by a joint grant from the Community of Madrid and the European Social Fund (grant PEJD-2019- POST/SAL-15892). The METHYL-UP project was supported by the Spanish Ministry of Science and Innovation (RTI2018-095569-B-I00, Programa de Proyectos Orientados a los Retos de la Sociedad “Projects Toward Society Challenges Program”).The association between ultra-processed food (UPF) and risk of cardiometabolic disorders is an ongoing concern. Different food processing-based classification systems have originated discrepancies in the conclusions among studies. To test whether the association between UPF consumption and cardiometabolic markers changes with the classification system, we used baseline data from 5636 participants (48.5% female and 51.5% male, mean age 65.1 4.9) of the PREDIMEDPlus (“PREvention with MEDiterranean DIet”) trial. Subjects presented with overweight or obesity and met at least three metabolic syndrome (MetS) criteria. Food consumption was classified using a 143-item food frequency questionnaire according to four food processing-based classifications: NOVA, International Agency for Research on Cancer (IARC), International Food Information Council (IFIC) and University of North Carolina (UNC). Mean changes in nutritional and cardiometabolic markers were assessed according to quintiles of UPF consumption for each system. The association between UPF consumption and cardiometabolic markers was assessed using linear regression analysis. The concordance of the different classifications was assessed with intra-class correlation coefficients (ICC3, overall = 0.51). The highest UPF consumption was obtained with the IARC classification (45.9%) and the lowest with NOVA (7.9%). Subjects with high UPF consumption showed a poor dietary profile. We detected a direct association between UPF consumption and BMI (p = 0.001) when using the NOVA system, and with systolic (p = 0.018) and diastolic (p = 0.042) blood pressure when using the UNC system. Food classification methodologies markedly influenced the association between UPF consumption and cardiometabolic risk markers.European Research Council (ERC) European Commission #340918Centro de Investigacion Biomedica en Red-Fisiopatologia de la Obesidad y Nutricion PI16/00473, PI16/00662, PI16/01873, PI16/01094, PI16/00501, PI16/00533, PI16/00381, PI16/00366, PI16/01522, PI16/01120, PI17/00764, PI17/01183, PI17/00855, PI17/01347, PI17/00525, PI17/01827, PI17/00532, PI17/00215, PI17/01441 PI13/00673, PI13/00492, PI13/00272, PI13/01123, PI13/00462, PI13/00233, PI13/02184, PI13/00728, PI13/01090, PI13/01056, PI14/01722, PI14/00636, PI14/00618, PI14/00696, PI14/01206, PI14/01919, PI14/00853, PI14/01374, PI14/00972, PI14/00728, PI14/01471 PI17/00508, PI17/01732, PI17/00926, PI19/00957, PI19/00386, PI19/00309, PI19/01032, PI19/00576, PI19/00017, PI19/01226, PI19/00781, PI19/01560, PI19/0133