Workflow-centric research objects: First class citizens in scholarly discourse.

A workflow-centric research object bundles a workflow, the provenance of the results obtained by its enactment, other digital objects that are relevant for the experiment (papers, datasets, etc.), and annotations that semantically describe all these objects. In this paper, we propose a model to specify workflow-centric research objects, and show how the model can be grounded using semantic technologies and existing vocabularies, in particular the Object Reuse and Exchange (ORE) model and the Annotation Ontology (AO).We describe the life-cycle of a research object, which resembles the life-cycle of a scienti?c experiment.

A workflow PROV-corpus based on taverna and wings

We describe a corpus of provenance traces that we have collected by executing 120 real world scientific workflows. The workflows are from two different workflow systems: Taverna [5] and Wings [3], and 12 different application domains (see Figure 1). Table 1 provides a summary of this PROV-corpus.

A Compact Formula for the Derivative of a 3-D Rotation in Exponential Coordinates

We present a compact formula for the derivative of a 3-D rotation matrix with respect to its exponential coordinates. A geometric interpretation of the resulting expression is provided, as well as its agreement with other less-compact but better-known formulas. To the best of our knowledge, this simpler formula does not appear anywhere in the literature. We hope by providing this more compact expression to alleviate the common pressure to reluctantly resort to alternative representations in various computational applications simply as a means to avoid the complexity of differential analysis in exponential coordinates.

Towards workflow ecosystems through standard representations

Workflows are increasingly used to manage and share scientific computations and methods. Workflow tools can be used to design, validate, execute and visualize scientific workflows and their execution results. Other tools manage workflow libraries or mine their contents. There has been a lot of recent work on workflow system integration as well as common workflow interlinguas, but the interoperability among workflow systems remains a challenge. Ideally, these tools would form a workflow ecosystem such that it should be possible to create a workflow with a tool, execute it with another, visualize it with another, and use yet another tool to mine a repository of such workflows or their executions. In this paper, we describe our approach to create a workflow ecosystem through the use of standard models for provenance (OPM and W3C PROV) and extensions (P-PLAN and OPMW) to represent workflows. The ecosystem integrates different workflow tools with diverse functions (workflow generation, execution, browsing, mining, and visualization) created by a variety of research groups. This is, to our knowledge, the first time that such a variety of workflow systems and functions are integrated.

Workflow reuse in practice: a study of neuroimaging pipeline users

Workflow reuse is a major benefit of workflow systems and shared workflow repositories, but there are barely any studies that quantify the degree of reuse of workflows or the practical barriers that may stand in the way of successful reuse. In our own work, we hypothesize that defining workflow fragments improves reuse, since end-to-end workflows may be very specific and only partially reusable by others. This paper reports on a study of the current use of workflows and workflow fragments in labs that use the LONI Pipeline, a popular workflow system used mainly for neuroimaging research that enables users to define and reuse workflow fragments. We present an overview of the benefits of workflows and workflow fragments reported by users in informal discussions. We also report on a survey of researchers in a lab that has the LONI Pipeline installed, asking them about their experiences with reuse of workflow fragments and the actual benefits they perceive. This leads to quantifiable indicators of the reuse of workflows and workflow fragments in practice. Finally, we discuss barriers to further adoption of workflow fragments and workflow reuse that motivate further work.

INSTRUCCIO y formula per a la bona execucio de la pragmatica dels processos de absencia [Texto impreso]

Port. con esc. real xil

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.

A Semantic Workflow Mechanism to Realize Experimental Goals and Constraints

Postprint

Tunnel magnetoresistance in GaMnAs: going beyond Jullière formula

The relation between tunnel magnetoresistance (TMR) and spin polarization is explored for GaMnAs∕GaAlAs∕GaMnAs structures where the carriers experience strong spin–orbit interactions. TMR is calculated using the Landauer approach. The materials are described in the 6 band k⋅p model which includes spin–orbit interaction. Ferromagnetism is described in the virtual crystal mean field approximations. Our results indicate that TMR is a function of spin polarization and barrier thickness. As a result of the stong spin–orbit interactions, TMR also depends on the the angle between current flow direction and the electrode magnetization. These results compromise the validity of Julliere formula.

Measuring color differences in automotive samples with lightness flop: a test of the AUDI2000 color-difference formula

From a set of gonioapparent automotive samples from different manufacturers we selected 28 low-chroma color pairs with relatively small color differences predominantly in lightness. These color pairs were visually assessed with a gray scale at six different viewing angles by a panel of 10 observers. Using the Standardized Residual Sum of Squares (STRESS) index, the results of our visual experiment were tested against predictions made by 12 modern color-difference formulas. From a weighted STRESS index accounting for the uncertainty in visual assessments, the best prediction of our whole experiment was achieved using AUDI2000, CAM02-SCD, CAM02-UCS and OSA-GP-Euclidean color-difference formulas, which were no statistically significant different among them. A two-step optimization of the original AUDI2000 color-difference formula resulted in a modified AUDI2000 formula which performed both, significantly better than the original formula and below the experimental inter-observer variability. Nevertheless the proposal of a new revised AUDI2000 color-difference formula requires additional experimental data.

A partial success of trade cooperation within the ‘16+1’ formula: the case of food exports to China. OSW COMMENTARY #189, 2015-10-29

When in 2012 China approached the countries of Central and Eastern Europe (CEE) with a proposal of cooperation in the ‘16+1’ formula, it declared it was willing to meet the needs of CEE countries. Beijing had been aware of the political importance of the problem of trade deficit (which has been ongoing for years) and launched cooperation with the governments of 16 CEE countries to boost imports from these states. The years 2011–2014 brought an improvement in the balance of trade between China and: Hungary, Latvia, the Czech Republic, Romania, Bulgaria and Croatia. The remaining ten CEE countries recorded an increase in their trade deficits. Changes in CEE countries’ balance of trade with China resulted only slightly from political actions. Instead, they were due to the macroeconomic situation and to a deterioration of the debt crisis in the EU which, for example, caused a decline in the import of Chinese goods in some of these countries. Multilateral trade cooperation was successfully developed in the entire region only in the agricultural and food production sector – the area of greatest interest to China. The pace of bilateral cooperation with specific countries varied, with the fastest being Poland, Latvia, Romania, Hungary and Bulgaria. Actions by governments of CEE countries resulted in Chinese market opening up to hundreds of local companies which, in turn, translated into an increase in the volume of foodstuffs sold by ‘the 16’ to China from US$ 137 million in 2011 to US$ 400 million in 2014. The success achieved in the agricultural and food production sector has demonstrated the effectiveness of trade cooperation in the ‘16+1’ formula. It is, however, insufficient to generate a significant improvement of the trade balance. At present, the sector’s share in the total volume of goods sold to China by CEE states is a mere 3.7%, and any reduction of the trade deficit would require long-term and more comprehensive solutions still to be implemented by the governments of individual CEE states.