OJS Implementation and development of the Scientific Journals Site of the School of Humanities and Education Sciences at the Universidad Nacional de La Plata

Este trabajo tiene como objetivo describir la experiencia de implementación y desarrollo del Portal de revistas de la Facultad de Humanidades y Ciencias de Educación de la Universidad Nacional de La Plata a fin de que pueda ser aprovechada por todos aquellos que emprendan iniciativas de características similares. Para ello, se realiza en primer lugar un repaso por la trayectoria de la Facultad respecto a la edición de revistas científicas y la labor bibliotecaria para contribuir a su visualización. En segundo orden, se exponen las tareas llevadas adelante por la Prosecretaría de Gestión Editorial y Difusión (PGEyD) de la Facultad para concretar la puesta en marcha del portal. Se hace especial referencia a la personalización del software, a la metodología utilizada para la carga masiva de información en el sistema (usuarios y números retrospectivos) y a los procedimientos que permiten la inclusión en repositorio institucional y en el catálogo web de todos los contenidos del portal de manera semi-automática. Luego, se hace alusión al trabajo que se está realizando en relación al soporte y a la capacitación de los editores. Se exponen, después, los resultados conseguidos hasta el momento en un año de trabajo: creación de 10 revistas, migración de 4 títulos completos e inclusión del 25de las contribuciones publicadas en las revistas editadas por la FaHCE. A modo de cierre se enuncian una serie de desafíos que la Prosecretaría se ha propuesto para mejorar el Portal y optimizar los flujos de trabajo intra e interinstitucionales

Semantic scheduling of virtualized infrastructures for scientific workflows

Virtualized Infrastructures are a promising way for providing flexible and dynamic computing solutions for resourceconsuming tasks. Scientific Workflows are one of these kind of tasks, as they need a large amount of computational resources during certain periods of time. To provide the best infrastructure configuration for a workflow it is necessary to explore as many providers as possible taking into account different criteria like Quality of Service, pricing, response time, network latency, etc. Moreover, each one of these new resources must be tuned to provide the tools and dependencies required by each of the steps of the workflow. Working with different infrastructure providers, either public or private using their own concepts and terms, and with a set of heterogeneous applications requires a framework for integrating all the information about these elements. This work proposes semantic technologies for describing and integrating all the information about the different components of the overall system and a set of policies created by the user. Based on this information a scheduling process will be performed to generate an infrastructure configuration defining the set of virtual machines that must be run and the tools that must be deployed on them.

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.

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.

FragFlow: automated fragment detection in scientific workflows

Scientific workflows provide the means to define, execute and reproduce computational experiments. However, reusing existing workflows still poses challenges for workflow designers. Workflows are often too large and too specific to reuse in their entirety, so reuse is more likely to happen for fragments of workflows. These fragments may be identified manually by users as sub-workflows, or detected automatically. In this paper we present the FragFlow approach, which detects workflow fragments automatically by analyzing existing workflow corpora with graph mining algorithms. FragFlow detects the most common workflow fragments, links them to the original workflows and visualizes them. We evaluate our approach by comparing FragFlow results against user-defined sub-workflows from three different corpora of the LONI Pipeline system. Based on this evaluation, we discuss how automated workflow fragment detection could facilitate workflow reuse.

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.

Mining Abstractions in Scientific Workows

Los flujos de trabajo científicos han sido adoptados durante la última década para representar los métodos computacionales utilizados en experimentos in silico, así como para dar soporte a sus publicaciones asociadas. Dichos flujos de trabajo han demostrado ser útiles para compartir y reproducir experimentos científicos, permitiendo a investigadores visualizar, depurar y ahorrar tiempo a la hora de re-ejecutar un trabajo realizado con anterioridad. Sin embargo, los flujos de trabajo científicos pueden ser en ocasiones difíciles de entender y reutilizar. Esto es debido a impedimentos como el gran número de flujos de trabajo existentes en repositorios, su heterogeneidad o la falta generalizada de documentación y ejemplos de uso. Además, dado que normalmente es posible implementar un mismo método utilizando algoritmos o técnicas distintas, flujos de trabajo aparentemente distintos pueden estar relacionados a un determinado nivel de abstracción, basándose, por ejemplo, en su funcionalidad común. Esta tesis se centra en la reutilización de flujos de trabajo y su abstracción mediante la exploración de relaciones entre los flujos de trabajo de un repositorio y la extracción de abstracciones que podrían ayudar a la hora de reutilizar otros flujos de trabajo existentes. Para ello, se propone un modelo simple de representación de flujos de trabajo y sus ejecuciones, se analizan las abstracciones típicas que se pueden encontrar en los repositorios de flujos de trabajo, se exploran las prácticas habituales de los usuarios a la hora de reutilizar flujos de trabajo existentes y se describe un método para descubrir abstracciones útiles para usuarios, basadas en técnicas existentes de teoría de grafos. Los resultados obtenidos exponen las abstracciones y prácticas comunes de usuarios en términos de reutilización de flujos de trabajo, y muestran cómo las abstracciones que se extraen automáticamente tienen potencial para ser reutilizadas por usuarios que buscan diseñar nuevos flujos de trabajo. Abstract Scientific workflows have been adopted in the last decade to represent the computational methods used in in silico scientific experiments and their associated research products. Scientific workflows have demonstrated to be useful for sharing and reproducing scientific experiments, allowing scientists to visualize, debug and save time when re-executing previous work. However, scientific workflows may be difficult to understand and reuse. The large amount of available workflows in repositories, together with their heterogeneity and lack of documentation and usage examples may become an obstacle for a scientist aiming to reuse the work from other scientists. Furthermore, given that it is often possible to implement a method using different algorithms or techniques, seemingly disparate workflows may be related at a higher level of abstraction, based on their common functionality. In this thesis we address the issue of reusability and abstraction by exploring how workflows relate to one another in a workflow repository, mining abstractions that may be helpful for workflow reuse. In order to do so, we propose a simple model for representing and relating workflows and their executions, we analyze the typical common abstractions that can be found in workflow repositories, we explore the current practices of users regarding workflow reuse and we describe a method for discovering useful abstractions for workflows based on existing graph mining techniques. Our results expose the common abstractions and practices of users in terms of workflow reuse, and show how our proposed abstractions have potential to become useful for users designing new workflows.

Managing change and time in dynamic workflow processes

Business environments have become exceedingly dynamic and competitive in recent times. This dynamism is manifested in the form of changing process requirements and time constraints. Workflow technology is currently one of the most promising fields of research in business process automation. However, workflow systems to date do not provide the flexibility necessary to support the dynamic nature of business processes. In this paper we primarily discuss the issues and challenges related to managing change and time in workflows representing dynamic business processes. We also present an analysis of workflow modifications and provide feasibility considerations for the automation of this process.

A Formal Approach to Support Interoperability in Scientific Meta-workflows

Scientific workflows orchestrate the execution of complex experiments frequently using distributed computing platforms. Meta-workflows represent an emerging type of such workflows which aim to reuse existing workflows from potentially different workflow systems to achieve more complex and experimentation minimizing workflow design and testing efforts. Workflow interoperability plays a profound role in achieving this objective. This paper is focused at fostering interoperability across meta-workflows that combine workflows of different workflow systems from diverse scientific domains. This is achieved by formalizing definitions of meta-workflow and its different types to standardize their data structures used to describe workflows to be published and shared via public repositories. The paper also includes thorough formalization of two workflow interoperability approaches based on this formal description: the coarse-grained and fine-grained workflow interoperability approach. The paper presents a case study from Astrophysics which successfully demonstrates the use of the concepts of meta-workflows and workflow interoperability within a scientific simulation platform.