2013 IEEE 9th International Conference on e-Science最新文献

Scientific Analysis by Queries in Extended SPARQL over a Scalable e-Science Data Store 在可扩展的电子科学数据存储上扩展SPARQL查询的科学分析

2013 IEEE 9th International Conference on e-Science Pub Date : 2013-10-22 DOI: 10.1109/ESCIENCE.2013.19

Andrej Andrejev, S. Toor, A. Hellander, S. Holmgren, T. Risch

{"title":"Scientific Analysis by Queries in Extended SPARQL over a Scalable e-Science Data Store","authors":"Andrej Andrejev, S. Toor, A. Hellander, S. Holmgren, T. Risch","doi":"10.1109/ESCIENCE.2013.19","DOIUrl":"https://doi.org/10.1109/ESCIENCE.2013.19","url":null,"abstract":"Data-intensive applications in e-Science require scalable solutions for storage as well as interactive tools for analysis of scientific data. It is important to be able to query the data in a storage-independent way, and to be able to obtain the results of the data-analysis incrementally (in contrast to traditional batch solutions). We use the RDF data model extended with multidimensional numeric arrays to represent the results, parameters, and other metadata describing scientific experiments, and SciSPARQL, an extension of the SPARQL language, to combine massive numeric array data and metadata in queries. To address the scalability problem we present an architecture that enables the same SciSPARQL queries to be executed on the RDF dataset whether it is stored in a relational DBMS or mapped over a specialized geographically distributed e-Science data store. In order to minimize access and communication costs, we represent the arrays with proxy objects, and retrieve their content lazily. We formulate typical analysis tasks from a computational biology application in terms of SciSPARQL queries, and compare the query processing performance with manually written scripts in MATLAB.","PeriodicalId":325272,"journal":{"name":"2013 IEEE 9th International Conference on e-Science","volume":"72 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115643321","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 9

Identity Management for Virtual Organizations: An Experience-Based Model 虚拟组织的身份管理:一个基于经验的模型

2013 IEEE 9th International Conference on e-Science Pub Date : 2013-10-22 DOI: 10.1109/eScience.2013.47

Robert Cowles, Craig Jackson, Von Welch

引用次数: 3

Developing Sustainable Data Services in Cyberinfrastructure for Higher Education: Requirements and Lessons Learned 在高等教育网络基础设施中发展可持续的数据服务:要求和经验教训

2013 IEEE 9th International Conference on e-Science Pub Date : 2013-10-22 DOI: 10.1109/eScience.2013.46

Wilfred W. Li, R. Moore, Matthew Kullberg, B. Battistuz, S. Meier, Ronald Joyce, R. Wagner, T. Reynales, Qian Liu

{"title":"Developing Sustainable Data Services in Cyberinfrastructure for Higher Education: Requirements and Lessons Learned","authors":"Wilfred W. Li, R. Moore, Matthew Kullberg, B. Battistuz, S. Meier, Ronald Joyce, R. Wagner, T. Reynales, Qian Liu","doi":"10.1109/eScience.2013.46","DOIUrl":"https://doi.org/10.1109/eScience.2013.46","url":null,"abstract":"The University of California, San Diego (UC San Diego) Research Cyber infrastructure (RCI) program provides long-term quality services in centralized storage, colocation, computing, data curation, networking and technical expertise. To help define the data storage needs and set priorities, the RCI data services (RCIDS) team conducted a series of interviews with faculty and senior staff members between September 2012 and February 2013. A total of 50 groups from 29 separate departments and organized research units (ORUs) participated in the interviews, representing more than 600 UC San Diego researchers. From human genomic sequences, marine natural products, to cosmological simulations, their diverse datasets are shared with hundreds of thousands of users worldwide. The top 10 requirements on data services and the top 5 existing challenges and risks as reported by UC San Diego researchers have been identified. Based upon these requirements, the RCIDS team recommends a Network Attached Storage (NAS) data service to be first deployed with a sustainable business model. Additional services will be developed through further discussion with the research community and in view of emerging cloud computing technologies. An extensive discussion is provided on the implementation plan, cloud-based data services, and the lessons learned in building sustainable e-science infrastructure for higher education research.","PeriodicalId":325272,"journal":{"name":"2013 IEEE 9th International Conference on e-Science","volume":"258 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122369190","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

An e-Science Environment for Ecological and Hydrological Simulation Research 生态水文模拟研究的e-Science环境

2013 IEEE 9th International Conference on e-Science Pub Date : 2013-10-22 DOI: 10.1109/eScience.2013.37

Yaonan Zhang, Yingpin Long, Guohui Zhao, Yufang Min, Jianfang Kang, L. Luo, Zhenfang He, Yang Wang

{"title":"An e-Science Environment for Ecological and Hydrological Simulation Research","authors":"Yaonan Zhang, Yingpin Long, Guohui Zhao, Yufang Min, Jianfang Kang, L. Luo, Zhenfang He, Yang Wang","doi":"10.1109/eScience.2013.37","DOIUrl":"https://doi.org/10.1109/eScience.2013.37","url":null,"abstract":"Comprehensive integrated research on ecological and hydrological processes and the simulation of river basin environments are critical foundations for decision making by governments and river-basin managers. The demand for a holistic understanding of environmental systems such as river basins is increasing. Eco-hydrological research needs two types of monitoring platforms to access and collect data from basins: a modeling platform to support access, select, and run models online, and build new models with the collected data, and a manipulation platform to generate forcing data, run models, and visualize the results. Consequently, we developed an e-science environment framework comprising three platforms - a monitoring platform, a model platform, and a manipulation platform. The framework allows automatic data transmission, storage, management, analysis, model management, simulation, computing, and result visualization. The e-science environment integrates land surface models such as Simplified Simple Biosphere model, the Revised Simple Biosphere model and WRF, hydrological models such as SWAT and TOPMODEL, data assimilation filters including such as Kalman filter algorithm, and several tools and methods for dealing with data, principally artificial neural networks and Markov chains. We demonstrate the application of the framework that uses an SSIB land surface model ensemble Kalman filter to improve evapotranspiration, soil moisture, and ground temperature simulation in the Heihe inland river basin. The approach proves suitable for environmental simulation for inland river research.","PeriodicalId":325272,"journal":{"name":"2013 IEEE 9th International Conference on e-Science","volume":"112 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124113391","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

CloudDRN: A Lightweight, End-to-End System for Sharing Distributed Research Data in the Cloud CloudDRN:一个轻量级的端到端系统，用于在云中共享分布式研究数据

2013 IEEE 9th International Conference on e-Science Pub Date : 2013-10-22 DOI: 10.1109/eScience.2013.53

M. Humphrey, Jacob Steele, I. Kim, M. Kahn, J. Bondy, Michael Ames

{"title":"CloudDRN: A Lightweight, End-to-End System for Sharing Distributed Research Data in the Cloud","authors":"M. Humphrey, Jacob Steele, I. Kim, M. Kahn, J. Bondy, Michael Ames","doi":"10.1109/eScience.2013.53","DOIUrl":"https://doi.org/10.1109/eScience.2013.53","url":null,"abstract":"The cloud has proven itself as a scalable platform for Web-based applications. However, scientists and medical researchers are still searching for a simple cloud-based architecture that enables secure collaboration and sharing of distributed datasets. To date, attempts at using the cloud for this purpose generally view the cloud as simply a pool of servers upon which to run their legacy software. This approach fails to leverage the unique platform capabilities of the cloud. In this paper, we describe our Cloud Distributed Research Network (CloudDRN). We leverage the cloud for availability, reliability, scalability, and improved security as compared to legacy distributed systems while still supporting site autonomy. Our philosophy is to adapt commercial software tooling that was originally designed for business use-cases, thereby benefiting from the large built-in user community. We describe our general architecture and show an example of our system created to share distributed clinical research data. We evaluate our system in Amazon Web Services (AWS) and in Microsoft Windows Azure and find that while each cloud achieves similar financial cost, representative queries are 3.5x slower on average in Windows Azure.","PeriodicalId":325272,"journal":{"name":"2013 IEEE 9th International Conference on e-Science","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129374580","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 11

Constructing a Social Content Delivery Network for eScience 构建面向eScience的社会化内容分发网络

2013 IEEE 9th International Conference on e-Science Pub Date : 2013-10-22 DOI: 10.1109/ESCIENCE.2013.52

Kai Kugler, K. Chard, Simon Caton, O. Rana, D. Katz

引用次数: 8

Operation Properties: A Representation and their Role in the Propagation of Meta-Data 操作属性:一种表示及其在元数据传播中的作用

2013 IEEE 9th International Conference on e-Science Pub Date : 2013-10-22 DOI: 10.1109/eScience.2013.13

Juan Amiguet-Vercher, P. Apers, A. Wombacher

引用次数: 0

e-Enabling International Cancer Research: Lessons Being Learnt in the ENS@T-CANCER Project 使国际癌症研究电子化:ENS@T-CANCER项目的经验教训

2013 IEEE 9th International Conference on e-Science Pub Date : 2013-10-22 DOI: 10.1109/eScience.2013.33

A. Stell, R. Sinnott

引用次数: 7

OzTrack -- E-Infrastructure to Support the Management, Analysis and Sharing of Animal Tracking Data OzTrack——支持动物跟踪数据管理、分析和共享的电子基础设施

2013 IEEE 9th International Conference on e-Science Pub Date : 2013-10-22 DOI: 10.1109/ESCIENCE.2013.38

J. Hunter, C. Brooking, Wilfred Brimblecombe, R. G. Dwyer, H. Campbell, Matthew E. Watts, C. Franklin

引用次数: 18

Data Pipeline in MapReduce MapReduce中的数据管道

2013 IEEE 9th International Conference on e-Science Pub Date : 2013-10-22 DOI: 10.1109/eScience.2013.21

Jiaan Zeng, Beth Plale

引用次数: 4