Building a government data strategy: aligning open data and advanced research with the public and open science principles

Tom L. Schenk
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引用次数: 6

Abstract

Summary form only given. Governments have initiated and expanded open data policies at the municipal, state, and national levels. While these policies spark the promise of transparency, an open data program is an effective gateway to a larger data and technology strategy. Governments can use portals to convene a tech community consisting of entrepreneurs, professionals in information technology from large enterprises, and civic activists. The blend of the technology components and grassroots culture is necessary for governments to function as a platform. Yet, open data can achieve more than transparency and GaaP services. By leveraging open data and applying the principles of open access and open science, governments can collaborate with external researchers to implement analytic, stochastic research models that improve the efficiency of city operations and help advise on data-driven policy. Governments can leverage technologies such as open source software and distributed version control to share research with others, inviting review through reproducible research and also inviting improvements. In order to be successful, there must be a alignment between the governments internal technology stack and it's edifice to the public. We will discuss lessons from building a broad data strategy inclusive of open data, advanced analytics a la open science, internal technology systems, and necessary culture to iterate toward an collaboration between governments, the public, researchers, and private enterprise.?
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建立政府数据战略:将开放数据和先进研究与公共和开放科学原则相结合
只提供摘要形式。政府已经在市、州和国家层面启动并扩大了开放数据政策。虽然这些政策激发了透明度的承诺,但开放数据计划是通往更大数据和技术战略的有效途径。政府可以利用门户网站召集一个由企业家、大型企业信息技术专业人员和公民活动人士组成的技术社区。技术成分和基层文化的融合是政府发挥平台作用的必要条件。然而,开放数据可以实现的不仅仅是透明度和公认会计准则服务。通过利用开放数据,应用开放获取和开放科学的原则,政府可以与外部研究人员合作,实施分析的、随机的研究模型,从而提高城市运营的效率,并为数据驱动的政策提供建议。政府可以利用开源软件和分布式版本控制等技术与他人分享研究成果,通过可重复的研究邀请审查,并邀请改进。为了取得成功,政府内部的技术堆栈必须与公众的大厦保持一致。我们将讨论建立广泛的数据战略的经验教训,包括开放数据、高级分析和开放科学、内部技术系统和必要的文化,以实现政府、公众、研究人员和私营企业之间的合作。
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