TLS: Towards a Macroscope for Science Policy Decision Making

TLS：走向科学政策决策的宏观视野

• 批准号: 0738111
• 负责人: Katy Borner
• 金额: $ 39.99万
• 依托单位: Indiana University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2008
• 资助国家: 美国
• 起止时间: 2008-01-01 至 2011-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0738111&HistoricalAwards=false
• 关键词: TLS; Towards; Macroscope; Science; Policy

Science policy and other decision makers need qualitatively novel tools to help them identify the publications, patents, technology claims, grant proposals, or other developments that are most important or potentially profitable and deserve their full attention. They also need a tool that lets them analyze and mine terabytes of relevant data and presents aggregated results in an easy to understand way, enabling them to increase the quality of their decisions. However, more than just a tool is needed. The design of tools that truly support science policy making requires a detailed characterization and prioritization of the information needs of science policy makers, along with a conceptual framework that links the information needs of the policy maker to the available data, analysis and indicator types. Once these are in place, tool development that truly addresses the needs of today's science policy makers given the constraints of existing datasets as well as theoretical and algorithmic approaches can proceed. This study addresses three challenges. First, a detailed analysis is conducted of the information needs of a representative set of science policy makers including existing data, approaches and tools. Second, a theoretic conceptualization is developed of tasks relevant to science policymaking that maps the needs of policy makers to theoretically grounded and practically valuable processing pipelines that transform data into actionable information. This conceptualization is then made available online in a wiki-like format for community review and consensus building. Third, a prototypical tool--a macroscope--is designed to visualize structure, patterns, trends, and outliers in science and technology data sets that are too large and complex to be comprehensible to the researchers through direct observation--just like microscopes and telescopes make it possible to see things that are too small or too far away. The prototypical macroscope supports a well defined set of information needs, e.g., identification of emerging research frontiers or correlation of funding with publications and patents in an area of research and exploration of results using graphs and geospatial and science maps. Macroscope tool development will benefit from the NSF funded Scholarly Database (SDB)) that provides access to more than 20 million scholarly records, and the Cyberinfrastructure Shell (CIShell), which supports the easy plug and play of datasets and algorithms and the design of stand-alone tools. Usability studies are conducted to evaluate and optimize the macroscope. The macroscope as well as its support of advanced science mapping techniques will be introduced to a broader audience by means of the Places and Spaces: Mapping Science exhibit. Researchers and science policymakers in Japan will participate in this project, generating a bi-directional flow of best theory and practice.The scientific study and management of science and technology requires a shared terminology and conceptualization of how science works. It requires shared data repositories that can be used to run benchmarks and comparisons of algorithms, to thoroughly validate the combination of algorithms, indicators, and evaluation procedures. The theoretical component of this study, as well as the extension of the SDB and the prototypical design of a macroscope, will create a basic shared understanding and a freely available cyberinfrastructure and tool for the science of science (policy) community. The same capabilities that could make the macroscope a tool of choice for science policy makers could also make it attractive to other potential users. For instance, students or members of the public will be able to see the large scale structures of science, and find potential areas of interest for further study; researchers will be able to monitor and access research results, relevant funding opportunities, or find potential collaborators within and without their fields of inquiry. Program managers and reviewers will use it to meet their individual needs.

科学政策和其他决策者需要在质量上新颖的工具来帮助他们识别最重要或潜在有利可图的出版物、专利、技术要求、拨款提案或其他发展，并值得他们充分关注。他们还需要一种工具，使他们能够分析和挖掘tb级的相关数据，并以易于理解的方式呈现汇总结果，使他们能够提高决策质量。然而，需要的不仅仅是一个工具。设计真正支持科学政策制定的工具需要对科学决策者的信息需求进行详细的描述和优先排序，以及将决策者的信息需求与现有数据、分析和指标类型联系起来的概念框架。一旦这些都到位，在现有数据集以及理论和算法方法的限制下，真正满足当今科学决策者需求的工具开发就可以继续进行。这项研究解决了三个挑战。首先，详细分析了一组具有代表性的科学决策者的信息需求，包括现有的数据、方法和工具。其次，开发了与科学决策相关的任务的理论概念化，将决策者的需求映射到理论基础和实际有价值的处理管道，将数据转换为可操作的信息。然后，这种概念化以类似维基的形式在网上提供，供社区审查和建立共识。第三，一个原型工具——宏观——被设计用来可视化科学和技术数据集中的结构、模式、趋势和异常值，这些数据集太大、太复杂，研究人员无法通过直接观察来理解——就像显微镜和望远镜可以看到太小或太远的东西一样。原型宏观支持一组明确定义的信息需求，例如，确定新出现的研究前沿或将资助与研究领域的出版物和专利联系起来，并使用图形和地理空间和科学地图探索结果。Macroscope工具的开发将受益于NSF资助的学术数据库（SDB）和Cyberinfrastructure Shell (CIShell)，前者提供了超过2000万条学术记录的访问，后者支持数据集和算法的简单即插即用，以及独立工具的设计。进行可用性研究以评估和优化宏观。通过“地点与空间：测绘科学”展览，将向更广泛的观众介绍宏观以及它对先进科学测绘技术的支持。日本的研究人员和科学决策者将参与这个项目，形成最佳理论和实践的双向流动。科学技术的科学研究和管理需要对科学如何工作有一个共同的术语和概念。它需要可用于运行基准测试和算法比较的共享数据存储库，以彻底验证算法、指示器和评估过程的组合。本研究的理论组成部分，以及SDB的扩展和宏观模型的原型设计，将为科学（政策）界创造一个基本的共享理解和一个免费的网络基础设施和工具。可以使宏观科学成为科学决策者选择的工具的能力也可以使它对其他潜在用户具有吸引力。例如，学生或公众将能够看到科学的大规模结构，并找到进一步研究的潜在兴趣领域；研究人员将能够监测和获取研究成果、相关的资助机会，或者在其研究领域内外找到潜在的合作者。项目经理和评审人员将使用它来满足他们各自的需求。