Dmitry Vasunin

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.

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. By facilitating access to distributed compute and information resources held by multiple organizations, and providing remote experiment control, data management and information retrieval capabilities, it allows scientists to better analyze their data. The ability to use data from multiple sources and correlating these data sets without in-depth domain expertise is a prime goal of the system. This paper describes the design and an implementation prototype of the VLAMG platform. The feasibility of the system is demonstrated by a generalized sample scenario from the chemo-physical analysis domain.

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.

Service-oriented visualization applied to medical data analysis

With the era of Grid computing, data driven experiments and simulations have become very advanced and complicated. To allow specialists from various domains to deal with large datasets, aside from developing efficient extraction techniques, it is necessary to have available computational facilities to visualize and interact with the results of an extraction process. Having this in mind, we developed an Interactive Visualization Framework, which supports a service-oriented architecture. This framework allows, on one hand visualization experts to construct visualizations to view and interact with large datasets, and on the other hand end-users (e.g., medical specialists) to explore these visualizations irrespective of their geographical location and available computing resources. The image-based analysis of vascular disorders served as a case study for this project. The paper presents main research findings and reports on the current implementation status.

SigWin-detector: a Grid-enabled workflow for discovering enriched windows of genomic features related to DNA sequences

BackgroundChromosome location is often used as a scaffold to organize genomic information in both the living cell and molecular biological research. Thus, ever-increasing amounts of data about genomic features are stored in public databases and can be readily visualized by genome browsers. To perform in silico experimentation conveniently with this genomics data, biologists need tools to process and compare datasets routinely and explore the obtained results interactively. The complexity of such experimentation requires these tools to be based on an e-Science approach, hence generic, modular, and reusable. A virtual laboratory environment with workflows, workflow management systems, and Grid computation are therefore essential.FindingsHere we apply an e-Science approach to develop SigWin-detector, a workflow-based tool that can detect significantly enriched windows of (genomic) features in a (DNA) sequence in a fast and reproducible way. For proof-of-principle, we utilize a biological use case to detect regions of increased and decreased gene expression (RIDGEs and anti-RIDGEs) in human transcriptome maps. We improved the original method for RIDGE detection by replacing the costly step of estimation by random sampling with a faster analytical formula for computing the distribution of the null hypothesis being tested and by developing a new algorithm for computing moving medians. SigWin-detector was developed using the WS-VLAM workflow management system and consists of several reusable modules that are linked together in a basic workflow. The configuration of this basic workflow can be adapted to satisfy the requirements of the specific in silico experiment.ConclusionAs we show with the results from analyses in the biological use case on RIDGEs, SigWin-detector is an efficient and reusable Grid-based tool for discovering windows enriched for features of a particular type in any sequence of values. Thus, SigWin-detector provides the proof-of-principle for the modular e-Science based concept of integrative bioinformatics experimentation.

HisT/PLIER: A Two-Fold Provenance Approach for Grid-Enabled Scientific Workflows Using WS-VLAM

Large scale scientific applications are frequently modeled as a workflow that is executed under the control of a workflow management system. One crucial requirement is the validation of the generated results, e.g. The trace ability 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, experimentations were made with two different implementations of the provenance concepts. The first one, adopts the Open Provenance Model (OPM) using the Provenance Layer Infrastructure for e-Science Resources (PLIER). The second one is the history-tracing XML (HisT). This paper describes how these two provenance models are integrated into WS-VLAM.

Evaluating the VLAM-G toolkit on the DAS-2

The Grid-based Virtual Laboratory AMsterdam (VLAM-G) provides a science portal for distributed analysis in applied scientific research. DAS-2 is a wide-area distributed computer of 200 Dual Pentium-III nodes, distributed over five Dutch universities. During the iGrid conference, the current reference implementation of VLAM-G was evaluated with an application from the chemo-physical application domain on the DAS-2. It was shown how data flows are instantiated on DAS-2 resources, driven by an information management system that is designed to extract information from raw data sets. Both the information management system and data processing modules are provided by the middleware of the Virtual Laboratory (VL). This paper describes the software and hardware setup of this study, and evaluates the use and performance of the VLAM-G science portal.