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E-Science (e-Science), 2011 IEEE 7th International Conference on

Date 5-8 Dec. 2011

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Displaying Results 1 - 25 of 65
  • [Front cover]

    Page(s): C1
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  • [Title page i]

    Page(s): i
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  • [Title page iii]

    Page(s): iii
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  • [Copyright notice]

    Page(s): iv
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  • Table of contents

    Page(s): v - ix
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  • Message from the General Chairs

    Page(s): x
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  • Message from the Program Chair

    Page(s): xi
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  • Committee Lists

    Page(s): xii - xiii
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  • Reviewers

    Page(s): xiv - xv
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  • A Virtual Research Environment for Cancer Imaging Research

    Page(s): 1 - 6
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (588 KB) |  | HTML iconHTML  

    The "Virtual Research Environment for Cancer Imaging" project aims to support image processing researchers and clinicians by providing a framework for sharing images and algorithms. In this paper we present the system developed to date which has focused on sharing and managing DICOM images using Microsoft's Share Point 2010. The system allows configuring the metadata to be extracted from the DICOM tags to meet requirements from both set of users: imaging researchers and clinicians. We present the work conducted to allow sharing algorithms as scientific workflows through the use of the Trident Workflow Workbench and the initial library of activities and workflows created for one of the most popular image processing toolkits among imaging researchers, the Insight Toolkit. View full abstract»

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  • An Open-source Collaboration Environment for Metagenomics Research

    Page(s): 7 - 14
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (443 KB) |  | HTML iconHTML  

    By analyzing metagenomic data from microbial communities, the taxonomical and functional component of hundreds of previously unknown microbial communities have been elucidated in the past few years. However, metagenomic data analyses are both data- and computation-intensive, which require extensive computational power. Most of the current metagenomic data analysis software were designed to be used on a single PC (Personal Computer), which could not match with the fast increasing number of large metagenomic projects' computational requirements. Therefore, advanced computational environment has to be developed to cope with such needs. In this paper, we proposed an open-source collaboration environment for metagenomic data analysis, which enabled the parallel analysis of multiple metagenomic datasets at the same time. By using this collaboration environment, researchers from different locations could submit their data, collaboratively configure the analysis pipeline, and perform data analysis efficiently. As of now, more than 30 metagenomic data analysis projects have already been conducted based on this environment. View full abstract»

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  • rCAD: A Novel Database Schema for the Comparative Analysis of RNA

    Page(s): 15 - 22
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1808 KB) |  | HTML iconHTML  

    Beyond its direct involvement in protein synthesis with mRNA, tRNA, and rRNA, RNA is now being appreciated for its significance in the overall metabolism and regulation of the cell. Comparative analysis has been very effective in the identification and characterization of RNA molecules, including the accurate prediction of their secondary structure. We are developing an integrative scalable data management and analysis system, the RNA Comparative Analysis Database (rCAD), implemented with SQL Server to support RNA comparative analysis. The platform-agnostic database schema of rCAD captures the essential relationships between the different dimensions of information for RNA comparative analysis datasets. The rCAD implementation enables a variety of comparative analysis manipulations with multiple integrated data dimensions for advanced RNA comparative analysis workflows. In this paper, we describe details of the rCAD schema design and illustrate its usefulness with two usage scenarios. View full abstract»

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  • A National Grid Submission Gateway for eScience

    Page(s): 23 - 30
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1086 KB) |  | HTML iconHTML  

    Much contemporary research benefits from the operation of the Grid for large-scale data storage, sharing, analysis, processing and simulation. However, existing grid systems typically require users to have good IT skills, which is a hurdle for many scientists. Providing easier usability of grid systems is a big challenge. A number of systems, frameworks and portals have been developed over the past few years, however they have mostly been designed to work based on several assumptions in a particular environment, and it is not easy to adapt them to different needs or environments. In this paper, we present our system that adopts several new technologies and acts as a broker and a gateway to regional grid resources. Interaction and usability are improved by multiple interfaces aimed at users with different requirements and IT skills: a modern and easy-to-use web interface, a SOAP web service interface and a Restful interface. The usability of this system is demonstrated in a case study. View full abstract»

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  • Investigating the Use of Gadgets, Widgets, and OpenSocial to Build Science Gateways

    Page(s): 31 - 38
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (712 KB) |  | HTML iconHTML  

    Many science applications require more and more computing power as the amount of input data keeps increasing. To simplify using large-scale clusters and complicated application codes, and to facilitate cross-disciplinary collaboration, there has been substantial research and development work on Web-based science gateways. With numerous gateways needing to be developed for many different scientific domains, there has also been a long-standing need for reusable codes and extensible component models. During the previous decade, the component model for many gateways was the Java portlet. To overcome some of the port let model's limitations, new gateways take a different approach that utilizes modern Web technologies. In this paper, we examine the use of new standards such as Open Social, Gadgets, and W3C Widgets to build science gateway user interfaces. These standards overcome many shortcomings of the older port let development model. As general-purpose Web standards, however, they lack support for specialized science gateway requirements and so must be extended. We propose a generic architecture in which Open Social is integrated with backend services and grid infrastructures. We implement and evaluate these concepts in the Gadget Container, software developed by the authors. View full abstract»

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  • A Chemistry-Inspired Workflow Management System for Scientific Applications in Clouds

    Page(s): 39 - 46
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (435 KB) |  | HTML iconHTML  

    With the proliferation of Web Services, scientific applications are more and more designed as temporal compositions of services, commonly referred to as, workflows. To address this paradigm shift, different workflow management systems have been proposed. If their efficiency has been established over centralized reliable systems, it is questionable over highly decentralized failure-prone platforms. Scientific applications recently started to be deployed over clouds, leading to new issues, like elasticity, i.e., the possibility to dynamically refine, at runtime, the amount of resources dedicated to an application. This raised a new demand for programming models, able to express autonomic self-coordination of services in a dynamic, elastic platform. Chemistry-inspired computing recently regained momentum in this context, naturally expressing parallelism, distribution, and autonomic behaviors. While its high expressiveness and adequacy for this context has been established, the chemical model severely suffers from a lack of proof of concepts. In this paper, we concretely show how to leverage such models in this context. We focus on the design, the implementation and the experimental validation of a chemistry-inspired scientific workflow management system. View full abstract»

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  • A Cloud-based Dynamic Workflow for Mass Spectrometry Data Analysis

    Page(s): 47 - 54
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (881 KB) |  | HTML iconHTML  

    There is a growing interest in the use of cloud computing for scientific applications, including scientific workflows. Key attractions of the cloud include the pay-as-you-go model and elasticity. While the elasticity offered by clouds can be beneficial for many applications and use-scenarios, it also imposes significant challenges in the development of applications or services. For example, no general framework exists that can enable a scientific workflow to execute in a dynamic fashion, i.e. exploiting elasticity of clouds and automatically allocating and deal locating resources to meet time and/or cost constraints. This paper presents a case-study in creating a dynamic cloud workflow implementation of a scientific application. We work with Mass Matrix, an application which searches proteins and peptides from tandem mass spectrometry data. In order to use cloud resources, we first parallelize the search method used in this algorithm. Next, we create a flexible workflow using the Pegasus Workflow Management System. Finally, we add a new dynamic resource allocation module, which can use fewer or a larger number of resources based on a time constraint specified by the user. We evaluate our implementation using several different datasets, and show that the application scales quite well, and that our dynamic framework is effective in meeting time constraints. View full abstract»

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  • Creating a Cloud-based Life Science Gateway

    Page(s): 55 - 61
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (685 KB) |  | HTML iconHTML  

    Cloud computing is increasingly becoming a popular solution to massive data analysis in life science community. To completely harness the power of Cloud computing, scientists need science gateways to efficiently manage their virtual machines, share Cloud resources, and run high-throughput sequence analysis with bioinformatics software tools. This paper introduces the development and use of Open Life Science Gateway, which manages computational jobs on top of Hadoop streaming, and supports user-customized runtime environment with virtual machine images. Moreover, it facilitates researchers to team up on solving challenging computing problems by sharing Cloud based data sources and software tools. This gateway has been used for investigating better B-cell epitope prediction. View full abstract»

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  • Optimizing Phylogenetic Analysis Using SciHmm Cloud-based Scientific Workflow

    Page(s): 62 - 69
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (307 KB)  

    Phylogenetic analysis and multiple sequence alignment (MSA) are closely related bioinformatics fields. Phylogenetic analysis makes extensive use of MSA in the construction of phylogenetic trees, which are used to infer the evolutionary relationships between homologous genes. These bioinformatics experiments are usually modeled as scientific workflows. There are many alternative workflows that use different MSA methods to conduct phylogenetic analysis and each one can produce MSA with different quality. Scientists have to explore which MSA method is the most suitable for their experiments. However, workflows for phylogenetic analysis are both computational and data intensive and they may run sequentially during weeks. Although there any many approaches that parallelize these workflows, exploring all MSA methods many become a burden and expensive task. If scientists know the most adequate MSA method a priori, it would spare time and money. To optimize the phylogenetic analysis workflow, we propose in this paper SciHmm, a bioinformatics scientific workflow based in profile hidden Markov models (pHMMs) that aims at determining the most suitable MSA method for a phylogenetic analysis prior than executing the phylogenetic workflow. SciHmm is also executed in parallel in a cloud environment using SciCumulus middleware. The results demonstrated that optimizing a phylogenetic analysis using SciHmm considerably reduce the total execution time of phylogenetic analysis (up to 80%). This optimization also demonstrates that the biological results presented more quality. In addition, the parallel execution of SciHmm demonstrates that this kind of bioinformatics workflow is suitable to be executed in the cloud. View full abstract»

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  • Wireless Sensing Networks for Environmental Monitoring: Two Case Studies from Tropical Forests

    Page(s): 70 - 76
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (419 KB) |  | HTML iconHTML  

    The emergence of new environmental monitoring tools utilizing Wireless Sensor Networks (WSNs) represents new opportunities to understand locally driven ecological processes in tropical environments at larger spatial and temporal scales, while at the same time opens new opportunities for eScience research. In this paper we present results from the outcome of two WSNs deployments aimed to evaluate this new technology in tropical environments. Leaf temperature and Photosynthetically Active Radiation (PAR) were measured at high temporal resolution in Panama and Brazil, respectively. Our results indicate that WSN technologies can be used effectively enough to measure important micro-meteorological variables that are sensitive to climate change and land use/cover change. Some of the temperatures recorded during our experiments in Panama were significantly high than those suggested as critical environmental thresholds for tropical environments. Our PAR results from Brazil showcase the value of this technology to evaluate the role of light patterns on ecosystem succession as a result of regional land use/cover change process. Our experiments indicate the WSN can serve as a key element in future understandings of ecosystem process driven by eScience in the years to come. View full abstract»

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  • On the Powerful Use of Simulations in the Quake-Catcher Network to Efficiently Position Low-cost Earthquake Sensors

    Page(s): 77 - 84
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (725 KB) |  | HTML iconHTML  

    The Quake-Catcher Network (QCN) uses low-cost sensors connected to volunteer computers across the world to monitor seismic events. The location and density of these sensors' placement can impact the accuracy of the event detection. Because testing different special arrangements of new sensors could disrupt the currently active project, this would best be accomplished in a simulated environment. This paper presents an accurate and efficient framework for simulating the low cost QCN sensors and identifying their most effective locations and densities. Results presented show how our simulations are reliable tools to study diverse scenarios under different geographical and infrastructural constraints. View full abstract»

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  • Communicating Coastal Risk Analysis in an Age of Climate Change

    Page(s): 85 - 88
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (358 KB) |  | HTML iconHTML  

    Complex science and large volumes of disparate data required for risk analysis of coastal hazards can be very difficult to communicate effectively to government and business decision makers. Including potential future scenarios as a result of climate change complicates matters further. An immersive visualization environment integrating data from high resolution imagery, sensed and measured data, model output, and more, that can scale from the desktop to large dome theater venues demonstrate promise for greatly enhancing the impact and reach of these scientific endeavors. View full abstract»

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  • Application of Data Mining in Research of Avian Influenza Virus Cross-Species Infection

    Page(s): 89 - 96
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (863 KB) |  | HTML iconHTML  

    Avian Influenza Virus (AIV) has already crossed species barriers to infect humans, but the reason for avian flu cross-species infection is unknown. A lot of biology experiment accumulated tens of thousands of biological information data. As a new technology based on database and statistics, data mining provides unprecedented data analysis tool to biologists and powerful means to gene and protein's analysis and extraction. In this paper, we applied feature-based clustering and classification method to the research of AIV cross-species infection, finding useful patterns, and created a web-based early warning system. We also applied entropy plot and regression analysis to discover host-associated sites in AIV cross-species infection, and got the key sites that differentiate human versus avian influenza using the same method. Compared the two sets, we expected to discover some rules about the mutation trend. View full abstract»

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  • Fostering Scientific Workflow Preservation through Discovery of Substitute Services

    Page(s): 97 - 104
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (347 KB) |  | HTML iconHTML  

    Scientific workflows are increasingly gaining momentum as the new paradigm for modeling and enacting scientific experiments. The value of a workflow specification does not end once it is enacted. Indeed, workflow specifications encapsulate knowledge that documents scientific experiments, and are, therefore, worth preserving. Our experience suggests that workflow preservation is frequently hampered by the volatility of the constituent service operations when these operations are supplied by third-party providers. To deal with this issue, we propose a heuristic for locating substitutes that are able to replace unavailable service operations within workflows. The proposed method uses the data links connecting inputs and outputs of service operations in existing workflow specifications to locate operations with parameters compatible with those of the missing operations. Furthermore, it exploits provenance traces collected from past executions of workflows to ensure that candidate substitutes perform tasks similar to those of the missing operations. The effectiveness of the proposed method has been empirically assessed. View full abstract»

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  • A Novel Framework for Monitoring and Analyzing Quality of Data in Simulation Workflows

    Page(s): 105 - 112
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (359 KB) |  | HTML iconHTML  

    In recent years scientific workflows have been used for conducting data-intensive and long running simulations. Such simulation workflows have processed and produced different types of data whose quality has a strong influence on the final outcome of simulations. Therefore being able to monitor and analyze quality of this data during workflow execution is of paramount importance, as detection of quality problems will enable us to control the execution of simulations efficiently. Unfortunately, existing scientific workflow execution systems do not support the monitoring and analysis of quality of data for multi-scale or multi-domain simulations. In this paper, we examine how quality of data can be comprehensively measured within workflows and how the measured quality can be used to control and adapt running workflows. We present a quality of data measurement process and describe a quality of data monitoring and analysis framework that integrates this measurement process into a workflow management system. View full abstract»

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  • Transient Modeling of Permafrost Dynamics in Changing Climate Scenarios

    Page(s): 113 - 118
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1573 KB) |  | HTML iconHTML  

    Analysis of permafrost dynamics with a three-phase, two-component flow system coupled to heat transport is used to evaluate transient changes in groundwater seepage. Both seasonal and annual analysis of flow is conducted, assuming three warming temperature trends over a ten year period, representing three climate change scenarios. Previous results have indicated that a reduction in temporal variability of groundwater flow is expected to occur for a moderate temperature trend over long warming time periods. Here, new results indicate this is also expected for larger rates-of-change of temperature increase and over shorter time periods. Additionally it is shown that short-term annual flow variability may serve as early indicators for permafrost degradation also for greater warming trends, rather than solely relying on long-term changes in mean flows. View full abstract»

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