A Semantic-Based Approach to Attain Reproducibility of Computational Environments in Scientic Work ows: A Case Study

Reproducible research in scientic work ows is often addressed by tracking the provenance of the produced results. While this approach allows inspecting intermediate and nal results, improves understanding, and permits replaying a work ow execution, it does not ensure that the computational environment is available for subsequent executions to reproduce the experiment. In this work, we propose describing the resources involved in the execution of an experiment using a set of semantic vocabularies, so as to conserve the computational environment. We dene a process for documenting the work ow application, management system, and their dependencies based on 4 domain ontologies. We then conduct an experimental evaluation sing a real work ow application on an academic and a public Cloud platform. Results show that our approach can reproduce an equivalent execution environment of a predened virtual machine image on both computing platforms.

A sharing-based approach to supporting adaptation in service compositions

Data-related properties of the activities involved in a service composition can be used to facilitate several design-time and run-time adaptation tasks, such as service evolution, distributed enactment, and instance-level adaptation. A number of these properties can be expressed using a notion of sharing. We present an approach for automated inference of data properties based on sharing analysis, which is able to handle service compositions with complex control structures, involving loops and sub-workflows. The properties inferred can include data dependencies, information content, domain-defined attributes, privacy or confidentiality levels, among others. The analysis produces characterizations of the data and the activities in the composition in terms of minimal and maximal sharing, which can then be used to verify compliance of potential adaptation actions, or as supporting information in their generation. This sharing analysis approach can be used both at design time and at run time. In the latter case, the results of analysis can be refined using the composition traces (execution logs) at the point of execution, in order to support run-time adaptation.

A component- and connector-based approach for end-user composite web applications development

Enabling real end-user development is the next logical stage in the evolution of Internet-wide service-based applications. Successful composite applications rely on heavyweight service orchestration technologies that raise the bar far above end-user skills. This weakness can be attributed to the fact that the composition model does not satisfy end-user needs rather than to the actual infrastructure technologies. In our opinion, the best way to overcome this weakness is to offer end-to-end composition from the user interface to service invocation, plus an understandable abstraction of building blocks and a visual composition technique empowering end users to develop their own applications. In this paper, we present a visual framework for end users, called FAST, which fulfils this objective. FAST implements a novel composition model designed to empower non-programmer end users to create and share their own self-service composite applications in a fully visual fashion. We projected the development environment implementing this model as part of the European FP7 FAST Project, which was used to validate the rationale behind our approach.

A semantic-based approach to attain reproducibility of computational environments in scientific workflows: a case study

Reproducible research in scientific workflows is often addressed by tracking the provenance of the produced results. While this approach allows inspecting intermediate and final results, improves understanding, and permits replaying a workflow execution, it does not ensure that the computational environment is available for subsequent executions to reproduce the experiment. In this work, we propose describing the resources involved in the execution of an experiment using a set of semantic vocabularies, so as to conserve the computational environment. We define a process for documenting the workflow application, management system, and their dependencies based on 4 domain ontologies. We then conduct an experimental evaluation using a real workflow application on an academic and a public Cloud platform. Results show that our approach can reproduce an equivalent execution environment of a predefined virtual machine image on both computing platforms.

A proposal for a model-based approach for adapting software configuration to runtime environments

Las metodologías de desarrollo ágiles han sufrido un gran auge en entornos industriales durante los últimos años debido a la rapidez y fiabilidad de los procesos de desarrollo que proponen. La filosofía DevOps y específicamente las metodologías derivadas de ella como Continuous Delivery o Continuous Deployment promueven la gestión completamente automatizada del ciclo de vida de las aplicaciones, desde el código fuente a las aplicaciones ejecutándose en entornos de producción. La automatización se ve como un medio para producir procesos repetibles, fiables y rápidos. Sin embargo, no todas las partes de las metodologías Continuous están completamente automatizadas. En particular, la gestión de la configuración de los parámetros de ejecución es un problema que ha sido acrecentado por la elasticidad y escalabilidad que proporcionan las tecnologías de computación en la nube. La mayoría de las herramientas de despliegue actuales pueden automatizar el despliegue de la configuración de parámetros de ejecución, pero no ofrecen soporte a la hora de fijar esos parámetros o de validar los ficheros que despliegan, principalmente debido al gran abanico de opciones de configuración y el hecho de que el valor de muchos de esos parámetros es fijado en base a preferencias expresadas por el usuario. Esto hecho hace que pueda parecer que cualquier solución al problema debe estar ajustada a una aplicación específica en lugar de ofrecer una solución general. Con el objetivo de solucionar este problema, propongo un modelo de configuración que puede ser inferido a partir de instancias de configuración existentes y que puede reflejar las preferencias de los usuarios para ser usado para facilitar los procesos de configuración. El modelo de configuración puede ser usado como la base de un proceso de configuración interactivo capaz de guiar a un operador humano a través de la configuración de una aplicación para su despliegue en un entorno determinado o para detectar cambios de configuración automáticamente y producir una configuración válida que se ajuste a esos cambios. Además, el modelo de configuración debería ser gestionado como si se tratase de cualquier otro artefacto software y debería ser incorporado a las prácticas de gestión habituales. Por eso también propongo un modelo de gestión de servicios que incluya información relativa a la configuración de parámetros de ejecución y que además es capaz de describir y gestionar propuestas arquitectónicas actuales tales como los arquitecturas de microservicios. ABSTRACT Agile development methodologies have risen in popularity within the industry in recent years due to the speed and reliability of the processes they propose. The DevOps philosophy and specifically the methodologies derived from it such as Continuous Delivery and Continuous Deployment push for a totally automated management of the application lifecycle, from the source code to the software running in production environment. Automation in this regard is used as a means to produce repeatable, reliable and fast processes. However, not all parts of the Continuous methodologies are completely automatized. In particular, management of runtime parameter configuration is a problem that has increased its impact in deployment process due to the scalability and elasticity provided by cloud technologies. Most deployment tools nowadays can automate the deployment of runtime parameter configuration, but they offer no support for parameter setting o configuration validation, as the range of different configuration options and the fact that the value of many of those parameters is based on user preference seems to imply that any solution to the problem will have to be tailored to a specific application. With the aim to solve this problem I propose a configuration model that can be inferred from existing configurations and reflect user preferences in order to ease the configuration process. The configuration model can be used as the base of an interactive configuration process capable of guiding a human operator through the configuration of an application for its deployment in a specific environment or to automatically detect configuration changes and produce valid runtime parameter configurations that take into account those changes. Additionally, the configuration model should be managed as any other software artefact and should be incorporated into current management practices. I also propose a service management model that includes the configuration information and that is able to describe and manage current architectural practices such as the microservices architecture.

Ontology Evaluation: a pitfall-based approach to ontology diagnosis

La evaluación de ontologías, incluyendo diagnóstico y reparación de las mismas, es una compleja actividad que debe llevarse a cabo en cualquier proyecto de desarrollo ontológico para comprobar la calidad técnica de las ontologías. Sin embargo, existe una gran brecha entre los enfoques metodológicos sobre la evaluación de ontologías y las herramientas que le dan soporte. En particular, no existen enfoques que proporcionen guías concretas sobre cómo diagnosticar y, en consecuencia, reparar ontologías. Esta tesis pretende avanzar en el área de la evaluación de ontologías, concretamente en la actividad de diagnóstico. Los principales objetivos de esta tesis son (a) ayudar a los desarrolladores en el diagnóstico de ontologías para encontrar errores comunes y (b) facilitar dicho diagnóstico reduciendo el esfuerzo empleado proporcionando el soporte tecnológico adecuado. Esta tesis presenta las siguientes contribuciones: • Catálogo de 41 errores comunes que los ingenieros ontológicos pueden cometer durante el desarrollo de ontologías. • Modelo de calidad para el diagnóstico de ontologías alineando el catálogo de errores comunes con modelos de calidad existentes. • Diseño e implementación de 48 métodos para detectar 33 de los 41 errores comunes en el catálogo. • Soporte tecnológico OOPS!, que permite el diagnstico de ontologías de forma (semi)automática. De acuerdo con los comentarios recibidos y los resultados de los test de satisfacción realizados, se puede afirmar que el enfoque desarrollado y presentado en esta tesis ayuda de forma efectiva a los usuarios a mejorar la calidad de sus ontologías. OOPS! ha sido ampliamente aceptado por un gran número de usuarios de formal global y ha sido utilizado alrededor de 3000 veces desde 60 países diferentes. OOPS! se ha integrado en software desarrollado por terceros y ha sido instalado en empresas para ser utilizado tanto durante el desarrollo de ontologías como en actividades de formación. Abstract Ontology evaluation, which includes ontology diagnosis and repair, is a complex activity that should be carried out in every ontology development project, because it checks for the technical quality of the ontology. However, there is an important gap between the methodological work about ontology evaluation and the tools that support such an activity. More precisely, not many approaches provide clear guidance about how to diagnose ontologies and how to repair them accordingly. This thesis aims to advance the current state of the art of ontology evaluation, specifically in the ontology diagnosis activity. The main goals of this thesis are (a) to help ontology engineers to diagnose their ontologies in order to find common pitfalls and (b) to lessen the effort required from them by providing the suitable technological support. This thesis presents the following main contributions: • A catalogue that describes 41 pitfalls that ontology developers might include in their ontologies. • A quality model for ontology diagnose that aligns the pitfall catalogue to existing quality models for semantic technologies. • The design and implementation of 48 methods for detecting 33 out of the 41 pitfalls defined in the catalogue. • A system called OOPS! (OntOlogy Pitfall Scanner!) that allows ontology engineers to (semi)automatically diagnose their ontologies. According to the feedback gathered and satisfaction tests carried out, the approach developed and presented in this thesis effectively helps users to increase the quality of their ontologies. At the time of writing this thesis, OOPS! has been broadly accepted by a high number of users worldwide and has been used around 3000 times from 60 different countries. OOPS! is integrated with third-party software and is locally installed in private enterprises being used both for ontology development activities and training courses.

Pedestrian Motion Prediction: A Graph Based Approach

A novel pedestrian motion prediction technique is presented in this paper. Its main achievement regards to none previous observation, any knowledge of pedestrian trajectories nor the existence of possible destinations is required; hence making it useful for autonomous surveillance applications. Prediction only requires initial position of the pedestrian and a 2D representation of the scenario as occupancy grid. First, it uses the Fast Marching Method (FMM) to calculate the pedestrian arrival time for each position in the map and then, the likelihood that the pedestrian reaches those positions is estimated. The technique has been tested with synthetic and real scenarios. In all cases, accurate probability maps as well as their representative graphs were obtained with low computational cost.