Conservation of Computational Scientific Execution Environments for Workflow-based Experiments Using Ontologies

La reproducibilidad de estudios y resultados científicos es una meta a tener en cuenta por cualquier científico a la hora de publicar el producto de una investigación. El auge de la ciencia computacional, como una forma de llevar a cabo estudios empíricos haciendo uso de modelos matemáticos y simulaciones, ha derivado en una serie de nuevos retos con respecto a la reproducibilidad de dichos experimentos. La adopción de los flujos de trabajo como método para especificar el procedimiento científico de estos experimentos, así como las iniciativas orientadas a la conservación de los datos experimentales desarrolladas en las últimas décadas, han solucionado parcialmente este problema. Sin embargo, para afrontarlo de forma completa, la conservación y reproducibilidad del equipamiento computacional asociado a los flujos de trabajo científicos deben ser tenidas en cuenta. La amplia gama de recursos hardware y software necesarios para ejecutar un flujo de trabajo científico hace que sea necesario aportar una descripción completa detallando que recursos son necesarios y como estos deben de ser configurados. En esta tesis abordamos la reproducibilidad de los entornos de ejecución para flujos de trabajo científicos, mediante su documentación usando un modelo formal que puede ser usado para obtener un entorno equivalente. Para ello, se ha propuesto un conjunto de modelos para representar y relacionar los conceptos relevantes de dichos entornos, así como un conjunto de herramientas que hacen uso de dichos módulos para generar una descripción de la infraestructura, y un algoritmo capaz de generar una nueva especificación de entorno de ejecución a partir de dicha descripción, la cual puede ser usada para recrearlo usando técnicas de virtualización. Estas contribuciones han sido aplicadas a un conjunto representativo de experimentos científicos pertenecientes a diferentes dominios de la ciencia, exponiendo cada uno de ellos diferentes requisitos hardware y software. Los resultados obtenidos muestran la viabilidad de propuesta desarrollada, reproduciendo de forma satisfactoria los experimentos estudiados en diferentes entornos de virtualización. ABSTRACT Reproducibility of scientific studies and results is a goal that every scientist must pursuit when announcing research outcomes. The rise of computational science, as a way of conducting empirical studies by using mathematical models and simulations, have opened a new range of challenges in this context. The adoption of workflows as a way of detailing the scientific procedure of these experiments, along with the experimental data conservation initiatives that have been undertaken during last decades, have partially eased this problem. However, in order to fully address it, the conservation and reproducibility of the computational equipment related to them must be also considered. The wide range of software and hardware resources required to execute a scientific workflow implies that a comprehensive description detailing what those resources are and how they are arranged is necessary. In this thesis we address the issue of reproducibility of execution environments for scientific workflows, by documenting them in a formalized way, which can be later used to obtain and equivalent one. In order to do so, we propose a set of semantic models for representing and relating the relevant information of those environments, as well as a set of tools that uses these models for generating a description of the infrastructure, and an algorithmic process that consumes these descriptions for deriving a new execution environment specification, which can be enacted into a new equivalent one using virtualization solutions. We apply these three contributions to a set of representative scientific experiments, belonging to different scientific domains, and exposing different software and hardware requirements. The obtained results prove the feasibility of the proposed approach, by successfully reproducing the target experiments under different virtualization environments.

OSIRIS – The scientific camera system onboard Rosetta

The Optical, Spectroscopic, and Infrared Remote Imaging System OSIRIS is the scientific camera system onboard the Rosetta spacecraft (Figure 1). The advanced high performance imaging system will be pivotal for the success of the Rosetta mission. OSIRIS will detect 67P/Churyumov-Gerasimenko from a distance of more than 106 km, characterise the comet shape and volume, its rotational state and find a suitable landing spot for Philae, the Rosetta lander. OSIRIS will observe the nucleus, its activity and surroundings down to a scale of ~2 cm px−1. The observations will begin well before the onset of cometary activity and will extend over months until the comet reaches perihelion. During the rendezvous episode of the Rosetta mission, OSIRIS will provide key information about the nature of cometary nuclei and reveal the physics of cometary activity that leads to the gas and dust coma. OSIRIS comprises a high resolution Narrow Angle Camera (NAC) unit and a Wide Angle Camera (WAC) unit accompanied by three electronics boxes. The NAC is designed to obtain high resolution images of the surface of comet 7P/Churyumov-Gerasimenko through 12 discrete filters over the wavelength range 250–1000 nm at an angular resolution of 18.6 μrad px−1. The WAC is optimised to provide images of the near-nucleus environment in 14 discrete filters at an angular resolution of 101 μrad px−1. The two units use identical shutter, filter wheel, front door, and detector systems. They are operated by a common Data Processing Unit. The OSIRIS instrument has a total mass of 35 kg and is provided by institutes from six European countries