SEI: Coordinated Visualization and Analysis of Sky Survey Data and Astronomical Literature

SEI:巡天数据和天文学文献的协调可视化和分析

基本信息

  • 批准号:
    0612129
  • 负责人:
  • 金额:
    $ 41.31万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Continuing Grant
  • 财政年份:
    2006
  • 资助国家:
    美国
  • 起止时间:
    2006-07-15 至 2010-06-30
  • 项目状态:
    已结题

项目摘要

Scientists in disciplines such as astronomy are facing increasing challenges in order to keep abreast of research fronts and maintain a good understanding of scientific data due to massive volumes of new scientific data and rapidly growing bodies of dynamic and highly specialized scientific knowledge. Information technology has the potential to augment scientists' abilities to deal with the complexity, dynamics, and scale of these challenges. This interdisciplinary project aims to advance information integration techniques and their applications to astronomy and support the analysis of astronomical data in an integral context of astronomical literature. The research focuses on the analysis and modeling of patterns to be identified from four data sources in association with the Sloan Digital Sky Survey (SDSS): the SDSS astronomical data, the search query log data from the SDSS SkyServer, an SDSS-specific bibliographic dataset drawn from the NASA Astrophysics Data System (ADS), and an interdisciplinary bibliographic dataset drawn from the Science Citation Index (SCI). The research advances the integration and innovative use of techniques for tracking thematic trends and detecting conceptual changes, integrated text mining and citation network analysis, and visualizing spatial-semantic structural and temporal patterns, and incorporating visual analytics tools for hypothesis generation and testing. The project are (1) to establish a conceptual and operational platform for coordinated access, visualization, and analysis of astronomical data and literature; (2) to develop scalable algorithms and tools for tracking the evolution and diffusion of knowledge and for facilitating hypothesis generation and testing; (3) to develop scalable algorithms and tools for incrementally visualizing large-scale astronomical data and scholarly publications; and (4) to evaluate the use of knowledge visualization and tracking in astronomy and a broader range of disciplines. The project will produce an interactive 3D sky browser, coordinated astronomical-bibliographic visualizations, visual explorers of scientific discoveries, and tools for hypothesis generation. The research has broader impacts in terms of enabling scientists to keep track of the advances of their own fields and facilitating the study and evaluation of the role of massive new data in scientific discovery and scholarly communication. These visualization tools and metrics will measure the rate of dissemination and acceptance of new astronomical discoveries made with SDSS, identify the highest impact discoveries, illuminate patterns of interaction and feedback among different research groups, and measure the scientific effectiveness of the NSF-supported SDSS and aid planning for future astronomical survey projects. The research has direct implications on education and outreach of science and technology in terms of improving public understanding of science and guiding new researchers through a field of study with a clear intellectual roadmap. For the astronomical community, the impact of these tools will include aiding new researchers in the field, particularly students, by identifying the most important papers and connecting these to the original SDSS data through the SkyExplorer interface. The network of SDSS-related citations will provide a roadmap to possible analysis of similar datasets from other surveys and at other wavelengths. The tools will be also valuable to the development of timely educational materials.
天文学等学科的科学家面临着越来越多的挑战,因为大量新的科学数据和迅速增长的动态和高度专业化的科学知识,他们需要跟上研究前沿的步伐,并对科学数据保持良好的理解。信息技术有可能增强科学家应对这些挑战的复杂性、动态性和规模的能力。这一跨学科项目旨在推进信息集成技术及其在天文学中的应用,并支持在天文学文献的整体背景下分析天文学数据。该研究的重点是分析和建模的模式,以确定从四个数据源与斯隆数字巡天(SDSS):SDSS天文数据,从SDSS SkyServer的搜索查询日志数据,从美国宇航局天体物理数据系统(ADS)得出的SDSS特定的书目数据集,以及从科学引文索引(SCI)得出的跨学科书目数据集。该研究推进了跟踪主题趋势和检测概念变化的技术的集成和创新使用,集成文本挖掘和引用网络分析,可视化空间语义结构和时间模式,并将可视化分析工具用于假设生成和测试。该项目是(1)建立一个概念和操作平台,用于协调访问,可视化和分析天文数据和文献;(2)开发可扩展的算法和工具,用于跟踪知识的演变和传播,并促进假设的生成和测试;(3)开发可扩展的算法和工具,用于增量可视化大规模天文数据和学术出版物;以及(4)评估知识可视化和跟踪在天文学和更广泛的学科中的使用。该项目将产生一个交互式3D天空浏览器,协调天文书目可视化,科学发现的可视化探索者,以及假设生成工具。该研究具有更广泛的影响,使科学家能够跟踪自己领域的进展,并促进研究和评估大量新数据在科学发现和学术交流中的作用。这些可视化工具和指标将衡量SDSS新天文发现的传播和接受率,确定影响最大的发现,阐明不同研究小组之间的互动和反馈模式,并衡量NSF支持的SDSS的科学有效性,并为未来的天文调查项目提供帮助。这项研究对科学技术的教育和推广有直接的影响,可以提高公众对科学的理解,并指导新的研究人员通过一个具有明确知识路线图的研究领域。对于天文学界来说,这些工具的影响将包括帮助该领域的新研究人员,特别是学生,识别最重要的论文,并通过SkyExplorer接口将这些论文与原始SDSS数据连接起来。SDSS相关引文网络将为其他调查和其他波长的类似数据集的可能分析提供路线图。这些工具对于及时编写教育材料也很有价值。

项目成果

期刊论文数量(0)
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专利数量(0)

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Chaomei Chen其他文献

Measuring the movement of a research paradigm
衡量研究范式的变动
  • DOI:
    10.1117/12.602251
  • 发表时间:
    2005
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Chaomei Chen
  • 通讯作者:
    Chaomei Chen
Representing Scientific Knowledge
代表科学知识
The Structure and Dynamics of Scientific Knowledge
  • DOI:
    10.1007/978-1-4471-5128-9_5
  • 发表时间:
    2013
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Chaomei Chen
  • 通讯作者:
    Chaomei Chen
Tracing Competing Paradigms
追踪竞争范式
  • DOI:
    10.1007/978-1-4471-5128-9_6
  • 发表时间:
    2013
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Chaomei Chen
  • 通讯作者:
    Chaomei Chen
A century of research on neuromodulation interventions: A scientometric analysis of trends and knowledge maps
一个世纪的神经调节干预研究:趋势和知识图谱的科学计量分析
  • DOI:
    10.1016/j.neubiorev.2023.105300
  • 发表时间:
    2023
  • 期刊:
  • 影响因子:
    8.2
  • 作者:
    M. Sabé;Adi Sulstarova;Chaomei Chen;Joshua Hyde;E. Poulet;A. Aleman;J. Downar;V. Brandt;L. Mallet;O. Sentissi;Michael A Nitsche;M. Bikson;A. Brunoni;Cortese Samuele;M. Solmi
  • 通讯作者:
    M. Solmi

Chaomei Chen的其他文献

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{{ truncateString('Chaomei Chen', 18)}}的其他基金

A Visual Analytic Observatory of Scientific Knowledge
科学知识的可视化分析观测站
  • 批准号:
    1633286
  • 财政年份:
    2016
  • 资助金额:
    $ 41.31万
  • 项目类别:
    Standard Grant

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