Collaborative Research: Institutionalizing the Data Sciences, a Sociotechnical Investigation of BDHubs

合作研究：数据科学制度化，BDHub 的社会技术调查

• 批准号: 1638903
• 负责人: David Ribes
• 金额: $ 39.94万
• 依托单位: University of Washington
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-08-01 至 2019-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1638903&HistoricalAwards=false
• 关键词: Collaborative; Research; Institutionalizing; Data; Sciences

The world is being changed by Big Data, and data science is receiving a remarkably rapid uptake across the nation and the globe as it institutionalized in university curricula, state governance, and industry strategy. Across the sciences, state and industry, new forms of data collection and analysis hold the prospect of our being able to address the major social and scientific issues of our times: from responding to natural disasters to monitoring the environment to developing fundamental technological insights which will revolutionize industry. None of this will happen by fiat ? the development of the appropriate data analytics must be accompanied by new organizational alignments between research, policy and industry. The Big Data Hubs and Spokes (BDHubs) program is a key site for analyzing the nature of these alignments with a view to gaining a basic understanding of the stakes as the terrain shifts. All long-term research and innovation infrastructure must adapt to such ongoing changes. This research will contribute to understanding institutional flexibility: strategies, techniques and organizational innovations to adapt to changes in regulatory, policy and funding environments. We can expect but not precisely predict, continuing transformations in the sociotechnical, scientific and institutional ecologies of today?s research and scientific infrastructure. This project will investigate the ongoing activities at the BDHubs and its partner institutions, their emerging plans for the future, and tie these to the long-history of developing research infrastructures (50+ years) to understand the changes we can expect BDHubs to encounter over time (scientific, technological and institutional), and what strategies they employ in the face of transformations to the landscape of science, information technology and institutional environment. Many challenges facing contemporary science such as environmental research or chronic disease management require long-term studies and supporting infrastructures. This project will contribute directly to NSF and other efforts to build more open, effective, and sustainable knowledge communities across the sciences, industry and government. Improving understanding of the long-term trajectory of research infrastructure will lead to smarter and more sustainable investment and design choices on the part of project leaders, participants, tool builders, and funders. Many other science agencies are in the midst of funding such cross-cutting projects. This research will inform science policy and regulatory environments to help develop sustainable and productive research infrastructures. In order to do so, this study will develop a general organizational understanding of the development of large-scale and long-term endeavors in the data sciences and map the institutional landscape of modern data science with particular focus on the activities of infrastructure building, policy development and community formation. In addition, this study will help to develop an understanding of the ?rise of the data sciences? in the US both as an institutional movement and as a form of technical research, with special focus on establishing a framework for evaluating and understanding large-scale, cross-disciplinary collaboration on big data tools, techniques and methods.

大数据正在改变世界，随着数据科学在大学课程、国家治理和行业战略中的制度化，数据科学在全国和全球范围内得到了快速的普及。在科学、国家和工业领域，新形式的数据收集和分析使我们能够解决当今时代的重大社会和科学问题：从应对自然灾害到监测环境，再到开发基本的技术见解，这些见解将帮助我们解决当今时代的重大社会和科学问题。彻底改变工业。 这一切都不会通过法令发生吗？适当的数据分析的发展必须伴随着研究、政策和行业之间新的组织协调。 大数据中心和辐条 (BDHubs) 计划是分析这些路线性质的关键站点，以便对地形变化时的利害关系有基本的了解。 所有长期研究和创新基础设施都必须适应这种持续的变化。这项研究将有助于理解制度灵活性：适应监管、政策和融资环境变化的战略、技术和组织创新。 我们可以预期但无法准确预测当今研究和科学基础设施的社会技术、科学和制度生态的持续变革。 该项目将调查 BDHubs 及其合作机构正在进行的活动、他们对未来的新兴计划，并将这些与发展研究基础设施的悠久历史（50 多年）联系起来，以了解我们预计 BDHubs 将遇到的变化时间（科学、技术和制度），以及他们在面对科学、信息技术和制度环境的转变时采取的策略。当代科学面临的许多挑战，例如环境研究或慢性病管理，需要长期研究和支持基础设施。该项目将直接为 NSF 和其他努力做出贡献，以在科学、工业和政府领域建立更加开放、有效和可持续的知识社区。加深对研究基础设施长期发展轨迹的了解，将使项目领导者、参与者、工具构建者和资助者做出更明智、更可持续的投资和设计选择。许多其他科学机构正在资助此类跨领域项目。这项研究将为科学政策和监管环境提供信息，以帮助发展可持续和富有成效的研究基础设施。为此，本研究将对数据科学领域大规模和长期工作的发展形成总体的组织理解，并绘制现代数据科学的制度图景，特别关注基础设施建设、政策等活动。发展和社区形成。此外，这项研究将有助于加深对“数据科学的兴起”的理解。在美国，它既作为一种制度运动，又作为一种技术研究形式，特别注重建立一个评估和理解大数据工具、技术和方法的大规模、跨学科合作的框架。

项目成果

How I Learned What a Domain Was

我是如何知道什么是域名的

• DOI: 10.1145/3359140
• 发表时间: 2019
• 期刊: Proceedings of the ACM on Human-Computer Interaction
• 作者: Ribes, David .

Fostering Historical Research in CSCW & HCI

促进 CSCW 的历史研究

• DOI: 10.1145/3311957.3359436
• 发表时间: 2019
• 期刊: Computer Supported Cooperative Work
• 作者: Soden, Robert;Ribes, David;Jack, Maggie;Sutherland, Will;Khovanskaya, Vera;Avle, Seyram;Sengers, Phoebe;Bødker, Susanne
• 通讯作者: Bødker, Susanne

STS, Meet Data Science, Once Again

• DOI: 10.1177/0162243918798899
• 发表时间: 2019-05-01
• 期刊: SCIENCE TECHNOLOGY & HUMAN VALUES
• 影响因子: 3.1
• 作者: Ribes, David

Prospecting (in) the data sciences

• DOI: 10.1177/2053951720906849
• 发表时间: 2020-01
• 期刊: Big Data & Society
• 影响因子: 8.5
• 作者: S. Slota;Andrew Hoffman;David Ribes;G. Bowker

The logic of domains

• DOI: 10.1177/0306312719849709
• 发表时间: 2019-06-01
• 期刊: SOCIAL STUDIES OF SCIENCE
• 影响因子: 3
• 作者: Ribes, David;Hoffman, Andrew S.;Bowker, Geoffrey C.
• 通讯作者: Bowker, Geoffrey C.