DAT: A Visual Analytics Approach to Science and Innovation Policy

在科学发现的可视化和科学学科之间关系的可视化领域，已经完成了相当数量的工作，如科学可视化方法的地图。通常情况下，地图和组合分析都是基于对研究论文的关键词和/或引用分析，再加上期刊和会议的学科分类。虽然有用，但这种分析还远远不够完整，因为它没有考虑论文的全文，只考虑关键词和引用，也没有考虑其他来源，例如资助机构编制的研究项目摘要和机构或研究组织发表的报告。作为政策决定、供资效力评价或某一领域方向评价的基础的完整分析将包括对所有这些来源的综合分析。智力优势：该项目开发了一种可视化的分析方法来执行这些对多个来源的评估，包括以前没有的论文全文、摘要和报告。这种方法是探索性的，支持人们在最初并不确切知道自己在寻找什么的情况下进行调查，而是使用允许发现新关系和揭示见解的工具。一旦发现了这些见解，就可以更详细地研究，用收集的新证据进行测试，然后成为进一步见解发现的基础。为了支持这种探索性的调查，分析必须是，至少在初始阶段，非结构化和自动化的。最重要的词语和关系必须从文本中浮现出来。它们必须是自动化的，因为将有太多的文本文档，以任何其他方式进行评估。然而，分析不能完全自动化；必须有一个地方来插入理解，组织和理解所发现的东西，并根据所发现的东西将调查引向一个新的方向。这正是交互式视觉分析做出贡献的地方，它以可理解的视觉显示方式向调查人员揭示详细的结果，为进一步的探索提供线索，并支持对收集到的证据进行组织和注释，并追求新的假设。该项目还研究了论文和其他藏品随时间的变化和趋势。随着时间的推移，对变化和趋势的详细检查会带来一些行为，这些行为可能是由一个领域的研究人员选择的新的或新发现的方向、资金的变化或新的和重要的应用所引起的。应用的方法是基于对组织成故事、报告或类似叙事结构的流文本的分析。流媒体故事被组织成？事件集群?相似的故事，在特定的时间点开始和结束，有详细的时间结构。目标是确定激励事件，如新的资助方向，一个领域的领导者建立的新方向，以及跨领域的新的跨学科重点。更广泛的影响。最近的科学发现可视化研讨会（2008年9月）由美国国家科学基金会、美国能源部科学办公室赞助，由美国国家科学基金会的几个部门合作，以及项目经理、研究人员和商业创新者的广泛参与表明，人们对可视化有很大的兴趣和需求。此外，科学技术政策办公室和国家科学技术委员会刚刚发布的科学政策路线图（2008年11月）突出提到了可视化，特别是可视化分析，科学分析工具的需求。该报告还提到需要评估这些工具的实际科学分析应用。该项目旨在通过开发和评估一种广泛、灵活的可视化分析方法来满足这两种需求，这种方法可用于使用真实数据的真正科学和创新政策应用。

A fair amount of work, such as map of science visualization methods, has been done in the area of visualization of scientific discovery and of the relationships among scientific disciplines. Typically, both the maps and the portfolio analyses are derived from keyword and/or citation analyses of research papers coupled with categorizations by discipline of journals and conferences. Although useful, this analysis is far from complete because it does not consider the full text of the papers, just the keywords and citations, and does not consider other sources, such as research project abstracts compiled by funding agencies and reports published by agencies or research organizations. A complete analysis upon which to base policy decisions, evaluations of the effectiveness of funding, or assessments of the direction of a field would include an integrated analysis of all these sources.Intellectual Merit: This project develops a visual analytics approach to perform these assessments of multiple sources, including full text of papers, abstracts, and reports that have not been available before. The approach is exploratory, supporting investigations where one does not initially know precisely what one is looking for but rather uses tools that permit the discovery of new relations and the uncovering of insights. Once found these insights can be looked at in more detail, tested with the gathering of new evidence, and then be the basis of further insight discovery. To support this exploratory investigation, analyses must be, at least in initial stages, unstructured and automated. The most significant words and relations must bubble up from the texts themselves. They must be automated because there will be too many text documents to assess in any other way. Yet, the analyses cannot be completely automated; there must be a place to insert understanding, to organize and make sense of what is found and to direct the investigation in a new direction based on what is found. This is exactly where interactive visual analytics makes its contribution, revealing to investigators detailed results in understandable visual displays, providing clues to prompt further exploration, and supporting organization and annotation of collected evidence and pursuit of new hypotheses. This project also looks at changes and trends over time in the paper and other collections. Detailed examination of changes and trends over time brings out behaviors that may be caused by new or newly revealed directions chosen by researchers in a field, by changes in funding, or by new and important applications. The approach that is applied is based on analyses of streaming text organized into stories, reports, or similar narrative structures. The streaming stories are organized on the fly into ?event clusters? of similar stories that begin and end at particular points in time and have detailed time structures. The goal is to identify motivating events such as new funding directions, new directions established by leaders in a field, as well as new interdisciplinary thrusts across fields. Broader Impacts. As indicated by the recent Visualization of Scientific Discovery Workshop (September, 2008) with sponsorship by NSF, the DOE Office of Science, collaboration by several NSF divisions, and broad attendance by program managers, researchers, and business innovators, there is a significant interest and need for visualization. In addition, the just-released Science of Science Policy Roadmap (November, 2008) from the Office of Science and Technology Policy and the National Science and Technology Council prominently mentions the need for visualization, and in particular visual analytics, tools for science analysis. This report also mentions the need for assessment of these tools for real science analysis applications. This project is positioned to meet both these needs by pursuing the development and assessment of a broad, flexible visual analytics approach for real science and innovation policy applications with real data.