Ammar Benabdelkader

VLAM-G: A Grid-based virtual laboratory

The Grid-based Virtual Laboratory AMsterdam (VLAM-G), provides a science portal for distributed analysis in applied scientific research. It offers scientists remote experiment control, data management facilities and access to distributed resources by providing cross-institutional integration of information and resources in a familiar environment. The main goal is to provide a unique integration of existing standards and software packages. This paper describes the design and prototype implementation of the VLAM-G platform. In this testbed we applied several recent technologies such as the Globus toolkit, enhanced federated database systems, and visualization and simulation techniques. Several domain specific case studies are described in some detail. Information management will be discussed separately in a forthcoming paper.

A data-centric neuroscience gateway: design, implementation, and experiences

Science gateways provide UIs and high‐level services to access and manage applications and data collections on distributed resources. They facilitate users to perform data analysis on distributed computing infrastructures without getting involved into the technical details. The e‐BioInfra Gateway is a science gateway for biomedical data analysis on a national grid infrastructure, which has been successfully adopted for neuroscience research. This paper describes the motivation, requirements, and design of a new generation of e‐BioInfra Gateway, which is based on the grid and cloud user support environment (also known as WS‐PGRADE/gUSE framework) and supports heterogeneous infrastructures. The new gateway has been designed to have additional data and meta‐data management facilities to access and manage (biomedical) data servers, and to provide data‐centric user interaction. We have implemented and deployed the new gateway for the computational neuroscience research community of the Academic Medical Center of the University of Amsterdam. This paper presents the system architecture of the new gateway, highlights the improvements that have been achieved, discusses the choices that we have made, and reflects on those based on initial user feedback. Copyright

A reference architecture for scientific virtual laboratories

Abstract Recent advances in the IT can be applied to properly support certain complex requirements in the scientific and engineering domains. In experimental sciences, for instance, researchers should be assisted with conducting their complex scientific experimentation and supporting their collaboration with other scientists. The main requirements identified in such domains include the management of large data sets, distributed collaboration support, and high-performance issues, among others. The virtual laboratory project initiated at the University of Amsterdam aims at the development of a hardware and software reference architecture, and an open, flexible, and configurable laboratory framework to enable scientists and engineers with working on their experimentation problems, while making optimum use of modern information technology approaches. This paper describes the current stage of design of a reference architecture for this scientific virtual laboratory, and focuses further on the cooperative information management component of this architecture, and exemplifying its application to experimentation domain of biology.

Toward a Multi-layer Architecture for Scientific Virtual Laboratories

In order to assist researchers with conducting their complex scientific experimentation and to support their collaboration with other scientists, modern advances in the IT area can be properly applied to the domain of experimental sciences. The main requirements identified in this domain include management of large data sets, distributed collaboration support, and high-performance issues, among others. The Virtual Laboratory project initiated at the University of Amsterdam aims at the development of a hardware and software reference architecture, and an open, flexible and configurable laboratory framework to enable scientists and engineers to work on their experimentation problems, while making optimum use of modern information technology approaches. This paper first describes the current design of a multi-layer architecture for this Scientific Virtual Laboratory, and then focuses further on the cooperative information management layer of this architecture, and exemplifying its application to experimentation domain of biology.

Characterizing workflow-based activity on a production e-infrastructure using provenance data

Grid computing and workflow management systems emerged as solutions to the challenges arising from the processing and storage of shear volumes of data generated by modern simulations and data acquisition devices. Workflow management systems usually document the process of the workflow execution either as structured provenance information or as log files. Provenance is recognized as an important feature in workflow management systems, however there are still few reports on its usage in practical cases. In this paper we present the provenance system implemented in our platform, and then use the information captured by this system during 8 months of platform operation to analyze the platform usage and to perform multilevel error pattern analysis. We make use of the large amount of structured data using the explanatory potential of statistical approaches to find properties of workflows, jobs and resources that are related to workflow failure. Such an analysis enables us to characterize workflow executions on the infrastructure and understand workflow failures. The approach is generic and applicable to other e-infrastructures to gain insight into operational incidents.

Provenance opportunities for WS-VLAM: an exploration of an e-science and an e-business approach

Scientific applications are frequently modeled as a workflow that is executed under the control of a workflow management system. One crucial requirement during the execution is the validation of the generated results and the traceability of the experiment execution path. The automated tracking and storage of provenance information during workflow execution could satisfy this requirement. To collect provenance data using the Grid-enabled scientific workflow management system WS-VLAM, experimentation was made with two different implementations of the provenance concepts. The first one adopts the Open Provenance Model (OPM) as basis to represent, store, and share scientific experiments metadata using the Provenance Layer Infrastructure for e-Science Resources (PLIER). The second one is the history-tracing XML (HisT) which was developed for e-Business provenance. HisT provides a specific model to store provenance data within layered XML documents, whereby each layer is related to one individual workflow task. This paper explores these two provenance models by using an example workflow application and describes how they are integrated into WS-VLAM including implementation details of the provenance architecture. It finally gives a comparison of the two different approaches with a special regard to provenance for human actors.

Provenance for distributed biomedical workflow execution

Scientific research has become very data and compute intensive because of the progress in data acquisition and measurement devices, which is particularly true in Life Sciences. To cope with this deluge of data, scientists use distributed computing and storage infrastructures. The use of such infrastructures introduces by itself new challenges to the scientists in terms of proper and efficient use. Scientific workflow management systems play an important role in facilitating the use of the infrastructure by hiding some of its complexity. Although most scientific workflow management systems are provenance-aware, not all of them come with provenance functionality out of the box. In this paper we describe the improvement and integration of a provenance system into an e-infrastructure for biomedical research based on the MOTEUR workflow management system. The main contributions of the paper are: presenting an OPM implementation using relational database backend for the provenance store, providing an e-infrastructure with a comprehensive provenance system, defining a generic approach to provenance implementation, potentially suitable for other workflow systems and application domains and demonstrating the value of this system based on use cases presenting the provenance data through a user-friendly web interface.

Cooperative Information Management for Distributed Production Nodes

Advanced manufacturing environments nowadays involve a number of cooperating heterogeneous nodes, where each node supports a distinct activity, and their joint efforts and information exchange is of a complicated nature. There is a need to develop a strong interoperable distributed information management system to support these nodes with their information exchange and the management of large amount of data. Interestingly enough, different complex production environments share similar complexities. For instance, in production of potable water, that is the application described in this paper, similar to other production environments, there is a prominent need for coordinated control in order to achieve good product. Therefore, the information management strategies suitable for this production application can also properly support other applications. Existing systems for control and/or monitoring of the water production and water distribution are heterogeneous and of different levels of automation and reliability. The distributed/federated information management framework described in the paper supports the cooperation and information exchange among different nodes, and the activities involved in an intelligent water production network. Although, this paper mainly addresses the required interoperability and information management issues for the water production application, the approach described in this paper or a substantial part of it can be applied to any other manufacturing applications.

WS-PGRADE/gUSE-Based Science Gateways in Teaching

Various WS-PGRADE/gUSE science gateways have been extensively used in educational contexts, supporting courses offered by different European universities and organizations. This chapter presents some examples of how WS-PGRADE/gUSE generic and customized gateways have been used in such courses. These examples include practical cases from a variety of scientific fields and educational styles. For each case, the educational context and the course organization are presented, with emphasis on how the respective portal has been adopted for the practical exercises. A summary of experiences are also reported, including advantages and difficulties faced for using these gateways in teaching.

Computational Neuroscience Gateway: A Science Gateway Based on the WS-PGRADE/gUSE

Computational neuroscientists face challenges to manage ever-increasing large volume of data and to process them with applications that require great computational power. The Brain Imaging Centre of the Academic Medical Centre of the University of Amsterdam is a community of neuroscientists who are involved in various computational neuroscience research studies. They face various challenges to process and manage a growing amount of neuroimaging data. The goal of the computational neuroscience gateway is to facilitate large-scale data processing on distributed infrastructures and to enhance data management and collaboration for scientific research. The gateway is based on the WS-PGRADE/gUSE generic science gateway framework as platform for distributed computing, and it is connected to a data server based on the eXtensible Neuroimaging Archive Toolkit (XNAT). This chapter presents the design and architecture of the gateway with focus on the utilization of the WS-PGRADE/gUSE framework, and the lessons learned during its implementation and operation.