EpiC: A Cyberinfrastructure that Supports the Plug-and-Play of Datasets & Algori

EpiC：支持数据集即插即用的网络基础设施

• 批准号: 7923116
• 负责人: KATY BORNER
• 金额: $ 28.98万
• 依托单位: TRUSTEES OF INDIANA UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-09-26 至 2013-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7923116
• 关键词: Affect; Alcohol consumption; Alcohols; Algorithms; Area; Arts; Behavior; Behavioral Sciences; Biological Models; Cessation of life; Cognitive; Communicable Diseases; Communities; Community Developments; Complex; Computer Simulation; Computers; Data; Data Analyses; Data Set; Decision Making; Development; Diffusion; Disease; Epidemic; Epidemiology; Goals; Habits; Heroin; Image; Imagery; Individual; Information Resources Management; Institutes; Judgment; Knowledge; Lead; Maintenance; Medical; Medicine; Methodology; Modeling; National Institute of Allergy and Infectious Disease; National Institute of Drug Abuse; National Institute of General Medical Sciences; Natural History; Patients; Physics; Play; Population; Population Density; Prevention; Process; Psychologist; Public Health; Records; Research; Research Infrastructure; Research Project Grants; Resources; Scientist; Site; Smoking; Social Behavior; Societies; Software Engineering; Specialist; System; Techniques; Technology; Tobacco; Validation; Work; base; computer infrastructure; computer science; computerized tools; contagion; coping; cyber infrastructure; design; experience; experimental analysis; improved; indexing; knowledge of results; member; movie; new technology; novel; simulation; social; social cognition; tool

DESCRIPTION (provided by applicant): The study of epidemic and social contagion processes is crucial for the understanding, prediction, and prevention of many phenomena affecting public health, such as infectious disease, alcohol use, and smoking habits. Improving epidemic and social contagion research is therefore important to the goals of the NIDA, NIAID and NIGMS institutes. Research progress in this area is difficult because the datasets and processes unfold over multiple temporal and spatial scales, requiring applied mathematical and computational approaches that can cope with non-linear complex phenomena. This requires an integrated research approach where the many layers - from the single individual to the global society - are analyzed at once. Such an approach calls for qualitatively new technology that supports the easy exchange, combination, and application of data analysis capabilities, methodologies, and visualization tools developed in very different areas of research. This project proposes the design, implementation, deployment, and maintenance of a computational infrastructure for epidemic research called the Epidemics Cyber infrastructure (EpiC). EpiC is a qualitatively new type of cyber infrastructure -- an "empty shell" that supports the easy plug-and-play of datasets, algorithms, and visualization components in customized EpiC Tools. The proposed EpiC infrastructure is also unique in the utilization of a "scholarly marketplace" for sharing commonly used datasets, algorithms, and visualization components - the "fillings" of the EpiC Tools. The marketplace might be best compared with popular file and content sharing community sites like Flickr (http://flickr.com/), YouTube (http://youtube.com/), or Wikipedia (http://wikipedia.org/). However, instead of sharing images, movies, or encyclopedia entries, scholars will use EpiC to share datasets, algorithms, and any other items relevant to the study of epidemics. The overarching goals of EpiC are the improvement and facilitation of multi-scale analysis of social data integrated into dynamic systems modeling, agent-based modeling, and other simulation techniques for epidemic processes; the direct transfer of knowledge and results from fields of specialist research to the wider interdisciplinary scientific community; and the development of a cyber infrastructure technology that is open, usable, extensible, and sustainable. This project proposes the design, implementation, deployment, and maintenance of a computational infrastructure for epidemic research called Epidemics Cyber infrastructure (EpiC) for the improvement and facilitation of the multi-scale analysis of social data and their integration in systems dynamic modeling, agent-based modeling, and other simulation techniques for epidemic processes. EpiC is a qualitatively new type of cyber infrastructure -- an "empty shell" that supports the easy plug-and-play of datasets, algorithms, and visualization components in customized EpiC Tools. The proposed EpiC infrastructure is also unique in the utilization of a "scholarly marketplace" to share commonly used datasets, algorithms, and visualization components - the "fillings" of the EpiC Tools.

流行病和社会传染过程的研究对于理解，预测和预防影响公共卫生的许多现象至关重要，如传染病，饮酒和吸烟习惯。因此，改进流行病和社会传染研究对NIDA、NIAID和NIGMS研究所的目标至关重要。在这一领域的研究进展是困难的，因为数据集和过程在多个时间和空间尺度上展开，需要应用数学和计算方法，可以科普非线性复杂现象。这需要一种综合的研究方法，从单个个体到全球社会的多个层面都要同时进行分析。这种方法要求采用质的新技术，支持在非常不同的研究领域开发的数据分析能力、方法和可视化工具的轻松交换、组合和应用。该项目提出了流行病研究的计算基础设施的设计，实施，部署和维护，称为流行病网络基础设施（EpiC）。EpiC是一种新型的网络基础设施-一个“空壳”，支持定制的EpiC工具中的数据集，算法和可视化组件的简单即插即用。所提出的EpiC基础设施在利用“学术市场”来共享常用数据集、算法和可视化组件（EpiC工具的“填充物”）方面也是独一无二的。与流行的文件和内容共享社区网站（如Flickr（http：//flickr.com/）、YouTube（http：//youtube.com/）或维基百科（http：//wikipedia.org/））相比，该市场可能是最好的。然而，学者们将使用EpiC来共享数据集、算法和任何其他与流行病研究相关的项目，而不是共享图像、电影或百科全书条目。EpiC的总体目标是改进和促进社会数据的多尺度分析，将其集成到动态系统建模，基于代理的建模和其他流行病过程的模拟技术中;将知识和结果从专业研究领域直接转移到更广泛的跨学科科学界;以及开发开放，可用，可扩展和可持续的网络基础设施技术。该项目提出了流行病研究的计算基础设施的设计，实施，部署和维护，称为流行病网络基础设施（EpiC），以改善和促进社会数据的多尺度分析，并将其集成到系统动态建模，基于代理的建模和其他流行病过程的模拟技术中。EpiC是一种新型的网络基础设施-一个“空壳”，支持定制的EpiC工具中的数据集，算法和可视化组件的简单即插即用。所提出的EpiC基础设施在利用“学术市场”来共享常用的数据集、算法和可视化组件（EpiC工具的“填充物”）方面也是独一无二的。

项目成果

Towards a characterization of behavior-disease models.

• DOI: 10.1371/journal.pone.0023084
• 发表时间: 2011
• 期刊: PloS one
• 影响因子: 3.7
• 作者: Perra N;Balcan D;Gonçalves B;Vespignani A
• 通讯作者: Vespignani A

Modeling human mobility responses to the large-scale spreading of infectious diseases.

• DOI: 10.1038/srep00062
• 发表时间: 2011
• 期刊: SCIENTIFIC REPORTS
• 影响因子: 4.6
• 作者: Meloni, Sandro;Perra, Nicola;Arenas, Alex;Gomez, Sergio;Moreno, Yamir;Vespignani, Alessandro
• 通讯作者: Vespignani, Alessandro

Invasion threshold in structured populations with recurrent mobility patterns.

• DOI: 10.1016/j.jtbi.2011.10.010
• 发表时间: 2012-01-21
• 期刊: JOURNAL OF THEORETICAL BIOLOGY
• 影响因子: 2
• 作者: Balcan, Duygu;Vespignani, Alessandro
• 通讯作者: Vespignani, Alessandro

Phase transitions in contagion processes mediated by recurrent mobility patterns.

• DOI: 10.1038/nphys1944
• 发表时间: 2011-07-01
• 期刊: Nature physics
• 影响因子: 19.6

Human mobility networks, travel restrictions, and the global spread of 2009 H1N1 pandemic.

• DOI: 10.1371/journal.pone.0016591
• 发表时间: 2011-01-31
• 期刊: PloS one
• 影响因子: 3.7
• 作者: Bajardi P;Poletto C;Ramasco JJ;Tizzoni M;Colizza V;Vespignani A
• 通讯作者: Vespignani A