Erik Torres

Supporting biodiversity studies with the EUBrazilOpenBio Hybrid Data Infrastructure

EUBrazilOpenBio is a collaborative initiative addressing strategic barriers in biodiversity research by integrating open access data and user‐friendly tools widely available in Brazil and Europe. The project deploys the EU‐Brazil Hybrid Data Infrastructure that allows the sharing of hardware, software and data on‐demand. This infrastructure provides access to several integrated services and resources to seamlessly aggregate taxonomic, biodiversity and climate data, used by processing services implementing checklist cross‐mapping and ecological niche modelling. A Virtual Research Environment was created to provide users with a single entry point to processing and data resources. This article describes the architecture, demonstration use cases and some experimental results and validation. Copyright

Programming Ecological Niche Modeling Workflows in the Cloud

In the last decades biology scientists have relied on their own resources and tools to run the experiments and store the results of the analysis. However, the explosion of big data and the growing availability of computational methods find an obstacle in the lack of computational and storage resources. Cloud computing platforms are emerging as potential solution to overcome these limitations, but adaptation of the applications to enable scientific users to benefit from resources acquired on demand is a complex process requiring multidisciplinary expertise. The EUBrazilOpenBio initiative is implementing an e-Infrastructure that provides biodiversity community with a rich set of computational and data resources exploiting existing cloud technologies from EU and Brazil. This paper presents the implementation of one of the two use cases selected, the environmental niche modeling by means of implementing such workflow through the COMPSs framework and its deployment on the EUBrazil OpenBio platform. The proposed approach has been evaluated on a Cloud test bed managed by the VENUS-C middleware.

Service monitoring and differentiation techniques for resource allocation in the grid, on the basis of the level of service

The study of meta-scheduling of jobs in the Grid has been a recurrent topic on the literature. Many tools have been developed for allocating the jobs to the most appropriate resources according to specific application needs while balancing the workload among resources. However, few of them focus on evaluating the level of service attained by providers of Grid services. On the contrary, Grid generally offers best-effort service to all the applications. Without Quality of Service (QoS), the jobs are executed without any guarantee on the execution time or throughput. Also, the support for qualitative attributes, such as security, is limited to the information provided by the resources. The uncertainty on the final performance is an issue that affects user satisfaction, reducing the interest of Grid infrastructures. In this paper, we present GRIDIFF, a software architecture that covers all necessary steps to integrate QoS into the process of allocating resources for the execution of jobs in the Grid. GRIDIFF has been used in practice to differentiate the resources according to the fulfillment of the 100% of the QoS considering three groups with failure rates of 9.1%, 13.3% and 64.1%, respectively. Scalability has been evaluated through simulation in up to 7000 nodes that can handle up to 250 monitoring agents per node.

Assessing the Usability of a Science Gateway for Medical Knowledge Bases with TRENCADIS

Biomedical applications are often built on top of knowledge bases that contain medical images and clinical reports. Currently, these bases are being used to improve diagnosis, research and teaching, but in many cases, the infrastructure required has a prohibitive cost for many medical centres. However, resources can be attached from existing e-Science infrastructures. Therefore, many efforts have been made to establish best practices that allow the use of such infrastructures. However, e-Science relies on open, distributed, collaborative environments, built on top of very specialized technologies, such as Grid and Cloud computing, which require reasonable technical skills for their usage. Therefore, science gateways have become essential tools that assist users in interacting with e-Science applications. This paper describes TRENCADIS, a technology that supports the creation and operation of virtual knowledge bases. To this end, it provides developers with components and APIs for building secure data services that can be annotated and queried through ontology templates, based on DICOM and DICOM-SR. This technology was used in this paper to build a gateway for assisting diagnosis and research in breast cancer. We also present here the results of a study conducted to evaluate the gateway, from the point of view of the usability perceived by a group of physicians and radiologists.

A supporting infrastructure for evaluating QoS-specific activities in SOA-based Grids

Despite the advances that have been made in Grid acceptance and adoption, further efforts are needed to ensure that the required level of service predictability is achieved. QoS issues require close attention, especially those aspects related to the evaluation of specific service activities with the aim of ensuring that the execution of a task produces an outcome according with its expectative behaviour. In this paper we present a supporting infrastructure to enable organisations to tackle the lack of tools for evaluating QoS-specific service activities. Additionally, we describe a case study that illustrates the applicability of the proposed model to general-purpose service management issues. The model has been tested in a controlled environment with promising results.

Introducing High-Performance and High-Throughput Processing in the TRENCADIS Data Sharing Architecture

TRENCADIS (towards a grid environment to process and share DICOM objects) is a data sharing infrastructure based on grid technologies that federate distributed repositories of radiological studies using ontological models on the information of the structured reports. TRENCADIS has demonstrated its efficiency in data sharing. This work describes an extension of the architecture, based on WSRF, to deal with both high-performance and high-throughput applications on medical images. This enables TRENCADIS to work with complex workflows exploiting the computing capabilities of current e-infrastructures, such as EGEE.

Long-term storage and management of encrypted biomedical data in real scenarios

This paper emphasizes the development and application of technologies to effective guarantying the confidentiality and integrity of patient data in Grid-enabled biomedical applications. By strongly focusing on the interaction between security technologies and the human environment, this paper relates the experience of developing a model for the storage and management of encrypted medical data in the Grid. The ideas and concepts behind the proposed solution are briefly explained, as well as the components implementing the model in an OGSA compliant architecture. TRENCADIS, a project for managing DICOM structured reporting objects for use in a Valencian cyberinfrastructure for medical imaging in oncology (CVIMO), is currently adopting the architecture as a core component.