2012 IEEE 8th International Conference on E-Science最新文献_第5页

Towards the gamification of well-being measures 走向幸福衡量的游戏化

2012 IEEE 8th International Conference on E-Science Pub Date : 2012-10-08 DOI: 10.1109/eScience.2012.6404457

M. Hall, S. Kimbrough, Christian Haas, Christof Weinhardt, Simon Caton

{"title":"Towards the gamification of well-being measures","authors":"M. Hall, S. Kimbrough, Christian Haas, Christof Weinhardt, Simon Caton","doi":"10.1109/eScience.2012.6404457","DOIUrl":"https://doi.org/10.1109/eScience.2012.6404457","url":null,"abstract":"There is an overriding interest in measuring the well-being of communities and institutions: healthy (flourishing) individuals and groups perform “better” than those that are not. Capturing the facets of well-being is, however, not straightforward: it contains personal information with sometimes uncomfortable self-realizations associated to it. Yet, the benefit of such data is the ability to observe and react to imbalances of a community, i.e. it can facilitate community management. Due to its personal nature, the observation of well-being needs to leverage carefully considered constructs. To have a comprehensive look at the concept of individual well-being, we propose a gamified frame of reference within a social network platform to lower traditional entrance barriers for data collection and encourage continued usage. In our setting, participants can record aspects of their well-being as a part of their “normal” social network activities, as well as view trends of themselves and their community. To evaluate the feasibility of our approach, we present the results of an initial study conducted via Facebook.","PeriodicalId":6364,"journal":{"name":"2012 IEEE 8th International Conference on E-Science","volume":"36 1","pages":"1-8"},"PeriodicalIF":0.0,"publicationDate":"2012-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86022975","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

Why workflows break — Understanding and combating decay in Taverna workflows 为什么工作流中断——理解和对抗Taverna工作流中的衰减

2012 IEEE 8th International Conference on E-Science Pub Date : 2012-10-08 DOI: 10.1109/ESCIENCE.2012.6404482

Jun Zhao, José Manuél Gómez-Pérez, Khalid Belhajjame, G. Klyne, Esteban García-Cuesta, Aleix Garrido, K. Hettne, M. Roos, D. D. Roure, C. Goble

引用次数: 114

MARISSA: MApReduce Implementation for Streaming Science Applications MARISSA:流科学应用的MApReduce实现

2012 IEEE 8th International Conference on E-Science Pub Date : 2012-10-08 DOI: 10.1109/eScience.2012.6404432

Elif Dede, Zacharia Fadika, Jessica Hartog, M. Govindaraju, L. Ramakrishnan, D. Gunter, S. Canon

{"title":"MARISSA: MApReduce Implementation for Streaming Science Applications","authors":"Elif Dede, Zacharia Fadika, Jessica Hartog, M. Govindaraju, L. Ramakrishnan, D. Gunter, S. Canon","doi":"10.1109/eScience.2012.6404432","DOIUrl":"https://doi.org/10.1109/eScience.2012.6404432","url":null,"abstract":"MapReduce has since its inception been steadily gaining ground in various scientific disciplines ranging from space exploration to protein folding. The model poses a challenge for a wide range of current and legacy scientific applications for addressing their “Big Data” challenges. For example: MapRe-duce's best known implementation, Apache Hadoop, only offers native support for Java applications. While Hadoop streaming supports applications compiled in a variety of languages such as C, C++, Python and FORTRAN, streaming has shown to be a less efficient MapReduce alternative in terms of performance, and effectiveness. Additionally, Hadoop streaming offers lesser options than its native counterpart, and as such offers less flexibility along with a limited array of features for scientific software. The Hadoop File System (HDFS), a central pillar of Apache Hadoop is not a POSIX compliant file system. In this paper, we present an alternative framework to Hadoop streaming to address the needs of scientific applications: MARISSA (MApReduce Implementation for Streaming Science Applications). We describe MARISSA's design and explain how it expands the scientific applications that can benefit from the MapReduce model. We also compare and explain the performance gains of MARISSA over Hadoop streaming.","PeriodicalId":6364,"journal":{"name":"2012 IEEE 8th International Conference on E-Science","volume":"27 1","pages":"1-8"},"PeriodicalIF":0.0,"publicationDate":"2012-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81772601","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: 24

Towards HPC for the digital Humanities, Arts, and Social Sciences: Needs and challenges of adapting academic HPC for big data 面向数字人文、艺术和社会科学的高性能计算:适应大数据的学术高性能计算的需求和挑战

2012 IEEE 8th International Conference on E-Science Pub Date : 2012-10-08 DOI: 10.1109/eScience.2012.6404439

Kalev H. Leetaru

引用次数: 6

Service-based integration of human users in workflow-driven scientific experiments 工作流驱动的科学实验中基于服务的人类用户集成

2012 IEEE 8th International Conference on E-Science Pub Date : 2012-10-08 DOI: 10.1109/eScience.2012.6404435

D. Karastoyanova, Dimitrios Dentsas, D. Schumm, M. Sonntag, Lina Sun, Karolina Vukojevic-Haupt

{"title":"Service-based integration of human users in workflow-driven scientific experiments","authors":"D. Karastoyanova, Dimitrios Dentsas, D. Schumm, M. Sonntag, Lina Sun, Karolina Vukojevic-Haupt","doi":"10.1109/eScience.2012.6404435","DOIUrl":"https://doi.org/10.1109/eScience.2012.6404435","url":null,"abstract":"The use of information technology in research and practice leads to increased degree of automation of tasks and makes scientific experiments more efficient in terms of cost, speed, accuracy, and flexibility. Scientific workflows have proven useful for the automation of scientific computations. However, not all tasks of an experiment can be automated. Some decisions still need to be made by human users, for instance, how an automated system should proceed in an exceptional situation. To address the need for integration of human users in such automated systems, we propose the concept of Human Communication Flows, which specify best practices about how a scientific workflow can interact with a human user. We developed a human communication framework that implements Communication Flows in a pipes-and-filters architecture and supports both notifications and request-response interactions. Different Communication Services can be plugged into the framework to account for different communication capabilities of human users. We facilitate the use of Communication Flows within a scientific workflow by means of reusable workflow fragments implementing the interaction with the framework.","PeriodicalId":6364,"journal":{"name":"2012 IEEE 8th International Conference on E-Science","volume":"9 1","pages":"1-8"},"PeriodicalIF":0.0,"publicationDate":"2012-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74530120","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: 5

Happy or not: Generating topic-based emotional heatmaps for Culturomics using CyberGIS 快乐与否:使用CyberGIS为文化组生成基于主题的情感热图

2012 IEEE 8th International Conference on E-Science Pub Date : 2012-10-08 DOI: 10.1109/ESCIENCE.2012.6404440

Eric Shook, Kalev H. Leetaru, G. Cao, Anand Padmanabhan, Shaowen Wang

{"title":"Happy or not: Generating topic-based emotional heatmaps for Culturomics using CyberGIS","authors":"Eric Shook, Kalev H. Leetaru, G. Cao, Anand Padmanabhan, Shaowen Wang","doi":"10.1109/ESCIENCE.2012.6404440","DOIUrl":"https://doi.org/10.1109/ESCIENCE.2012.6404440","url":null,"abstract":"The field of Culturomics exploits “big data” to explore human society at population scale. Culturomics increasingly needs to consider geographic contexts and, thus, this research develops a geospatial visual analytical approach that transforms vast amounts of textual data into emotional heatmaps with fine-grained spatial resolution. Fulltext geocoding and sentiment mining extract locations and latent “tone” from text-based data, which are combined with spatial analysis methods - kernel density estimation and spatial interpolation - to generate heatmaps that capture the interplay of location, topic, and tone toward narrative impacts. To demonstrate the effectiveness of the approach, the complete English edition of Wikipedia is processed using a supercomputer to extract all locations and tone associated with the year of 2003. An emotional heatmap of Wikipedia's discussion of “armed conflict” for that year is created using the spatial analysis methods. Unlike previous research, our approach is designed for exploratory spatial analysis of topics in text archives by incorporating multiple attributes including the prominence of each location mentioned in the text, the density of a topic at each location compared to other topics, and the tone of the topics of interest into a single analysis. The generation of such fine-grained emotional heatmaps is computationally intensive particularly when accounting for the multiple attributes at fine scales. Therefore a CyberGIS platform based on national cyberinfrastructure in the United States is used to enable the computationally intensive visual analytics.","PeriodicalId":6364,"journal":{"name":"2012 IEEE 8th International Conference on E-Science","volume":"5 1","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2012-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81568576","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: 32

Efficient data transfer protocols for big data 面向大数据的高效数据传输协议

2012 IEEE 8th International Conference on E-Science Pub Date : 2012-10-08 DOI: 10.1109/eScience.2012.6404462

B. Tierney, E. Kissel, D. M. Swany, Eric Pouyoul

引用次数: 63

Verification and user experience of high data rate bandwidth-on-demand networks 高数据速率按需带宽网络的验证与用户体验

2012 IEEE 8th International Conference on E-Science Pub Date : 2012-10-08 DOI: 10.1109/eScience.2012.6404460

Jimmy Cullen, R. Hughes-Jones, R. Spencer

引用次数: 0

WorkWays: Interactive workflow-based science gateways 工作方式:基于交互式工作流的科学网关

2012 IEEE 8th International Conference on E-Science Pub Date : 2012-10-08 DOI: 10.1109/eScience.2012.6404428

H. Nguyen, D. Abramson

引用次数: 11

Statistical analysis and visualization services for Spatially Integrated Social Science datasets 空间集成社会科学数据集的统计分析和可视化服务

2012 IEEE 8th International Conference on E-Science Pub Date : 2012-10-08 DOI: 10.1109/eScience.2012.6404421

Irfan Azeezullah, Friska Pambudi, Tung-Kai Shyy, Imran Azeezullah, Nigel Ward, J. Hunter, R. Stimson

{"title":"Statistical analysis and visualization services for Spatially Integrated Social Science datasets","authors":"Irfan Azeezullah, Friska Pambudi, Tung-Kai Shyy, Imran Azeezullah, Nigel Ward, J. Hunter, R. Stimson","doi":"10.1109/eScience.2012.6404421","DOIUrl":"https://doi.org/10.1109/eScience.2012.6404421","url":null,"abstract":"The field of Spatially Integrated Social Science (SISS) recognizes that much data of interest to social scientists has an associated geographic location. SISS systems use geographic location as the basis for integrating heterogeneous social science data sets and for visualizing and analyzing the integrated results through mapping interfaces. However, sourcing data sets, aggregating data captured at different spatial scales, and implementing statistical analysis techniques over the data are highly complex and challenging steps, beyond the capabilities of many social scientists. The aim of the UQ SISS eResearch Facility (SISS-eRF) is to remove this burden from social scientists by providing a Web interface that allows researchers to quickly access relevant Australian socio-spatial datasets (e.g. census data, voting data), aggregate them spatially, conduct statistical modeling on the datasets and visualize spatial distribution patterns and statistical results. This paper describes the technical architecture and components of SISS-eRF and discusses the reasons that underpin the technological choices. It describes some case studies that demonstrate how SISS-eRF is being applied to prove hypotheses that relate particular voting patterns with socio-economic parameters (e.g., gender, age, housing, income, education, employment, religion/culture). Finally we outline our future plans for extending and deploying SISS-eRF across the Australian Social Science Community.","PeriodicalId":6364,"journal":{"name":"2012 IEEE 8th International Conference on E-Science","volume":"10 3 1","pages":"1-8"},"PeriodicalIF":0.0,"publicationDate":"2012-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83773454","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: 0