石头点评：十年战略行动实践指南，看似并没有让人振奋人心的“宏伟目标”，绝大部分都是务实而又基础性的管理要素。例如，识别解决问题的数据需求、质量、复用、安全与隐私保护，数据文化等等。对于全国性或者行业管理机构，乃至集团型企业组织，或许值得参考。
美国联邦政府公布了2020到2030年十年数据战略规划框架。
The Federal Data Strategy (FDS) describes a 10–year vision for how the Federal Government will accelerate the use of data to deliver on mission, serve the public, and steward resources while protecting security, privacy, and confidentiality. The strategy will guide federal data management and use via: a mission statement, ten operating principles, and a set of 40 best practices to guide agencies in leveraging the value of federal and federally-sponsored data. All Executive Branch agencies will implement the strategy through annual government-wide Action Plans. These annual Action Plans will identify and prioritize practice-related steps for a given year and build on progress from year to year.
联邦数据战略（FDS）描述了联邦政府如何加快数据的使用，以执行任务、服务公众和管理资源，同时保护安全、隐私和机密性。该战略将通过以下方式指导联邦数据管理和使用：使命、十项运营原则和一套40项最佳做法，以指导各机构利用联邦和联邦赞助的数据的价值。所有行政部门机构将通过年度行动计划实施战略。这些年度行动计划将确定特定年份与实践指南有关的步骤并确定其优先次序，并在逐年进展的基础上再接再厉。
下面摘录了战略框架中的40项实践指南，供朋友们参考。
The Federal Data Strategy’s Practices are designed to inform agency actions on a regular basis, to be continually relevant, and to be sufficiently general so as to broadly apply at all federal agencies and across all missions.
联邦数据战略行动指南旨在定期为机构行动提供基础性的、持续相关的、足够普遍的信息，以便广泛适用于所有联邦机构和团体。
The Practices represent aspirational goals that, when fully realized, will continually challenge and guide agencies, practitioners, and policymakers to improve the government’s approach to data stewardship and the leveraging of data to create value.
这些做法代表了理想的目标。要充分实现这些目标将不断挑战和指导机构、从业人员和决策者改进政府的数据管理方法和利用数据创造价值。
Building a Culture that Values Data and Promotes Public Use
构建重视数据、促进公共使用的文化
1. Identify Data Needs to Answer Key Agency Questions: Use the learning agenda process to identify and prioritize the agency’s key questions and the data needed to answer them.
1. 识别回答机构关键问题的数据需求：利用学习议程流程识别机构关键问题以及回答这些问题所需的数据并确定其优先次序。
2. Assess and Balance the Needs of Stakeholders: Identify and engage stakeholders throughout the data lifecycle to identify stakeholder needs and to incorporate stakeholder feedback into government priorities to maximize entrepreneurship, innovation, scientific discovery, economic growth, and the public good.
2. 评估和平衡利益相关者的需求：在整个数据生命周期中确定和吸引利益相关者，以确定利益相关者的需求，并将利益相关者的反馈纳入政府优先事项，以最大限度地提高创业、创新、科学发现、经济增长和公益。
3. Champion Data Use: Leaders set an example, incorporating data in decision-making and targeting resources to maximize the value of data for decision-making, accountability, and the public good.
3. 出众的数据使用：领导人树立榜样，将数据纳入决策，并确定资源目标，以最大限度地提高数据对决策、问责制和公益的价值。
4. Use Data to Guide Decision-Making: Effectively, routinely, transparently, and appropriately use data in policy, planning, and operations to guide decision-making; share the data and analyses behind those decisions.
4. 利用数据指导决策：有效、例行、透明和适当地在政策、规划和运营中使用数据指导决策；共享这些决策背后的数据和分析。
5. Prepare to Share: Assess and proactively address the procedural, regulatory, legal, and cultural barriers to sharing data within and across federal agencies, as well as with external partners.
5. 准备共享：评估并主动解决在联邦机构内部和跨联邦机构以及与外部合作伙伴共享数据的程序、监管、法律和文化障碍。
6. Convey Insights from Data: Use a range of communication tools and techniques to effectively present insights from data to a broad set of audiences.
6. 从数据中获取见解：使用一系列沟通工具和技术，有效地向广泛的受众展示从数据中获得的见解。
7. Use Data to Increase Accountability: Align operational and regulatory data inputs with performance measures and other outputs to help the public to understand the results of federal investments and to support informed decision-making and rule-making.
7. 利用数据加强问责制：将业务和监管数据输入与业绩计量和其他产出保持一致，以帮助公众了解联邦投资的结果，并支持知情的决策和规则制定。
8. Monitor and Address Public Perceptions: Regularly assess and address public confidence in the value, accuracy, objectivity, and privacy protection of federal data to make strategic improvements, advance agency missions, and improve public messages about planned and potential uses of federal data.
8. 监测和解决公众的看法：定期评估和解决公众对联邦数据的价值、准确性、客观性和隐私保护的信心，以进行战略改进，推进机构任务，并改进有关联邦数据计划和潜在用途的公共信息。
9. Connect Data Functions Across Agencies: Establish communities of practice for common agency data functions (e.g., data management, access, analytics, informatics, and user support) to promote efficiency, collaboration, and coordination.
9. 跨机构连接数据职能：为共同机构数据职能（例如数据管理、访问、分析、信息学和用户支持）建立实践社区，以提高效率、协作和协调。
10.Provide Resources Explicitly to Leverage Data Assets: Ensure that sufficient human and financial resources are available to support data driven agency decision-making, accountability and the ability to spur commercialization, innovation, and public use.
10. 明确提供资源以利用数据资产：确保有足够的人力和财政资源来支持数据驱动的机构决策、问责制和刺激商业化、创新和公共使用的能力。
Governing, Managing, and Protecting Data
治理、管理和保护数据
11.Prioritize Data Governance: Ensure there are sufficient authorities, roles, organizational structures, policies, and resources in place to transparently support the management, maintenance, and use of strategic data assets.
11. 优先考虑数据治理：确保有足够的权力、角色、组织结构、政策和资源，以透明地支持战略数据资产的管理、维护和使用。
12.Govern Data to Protect Confidentiality and Privacy: Ensure there are sufficient authorities, roles, organizational structures, policies, and resources in place to provide appropriate access to confidential data and to maintain public trust and safeguard privacy.
12. 实施数据监管以保护安全和隐私：确保有足够的权力、角色、组织结构、政策和资源，以提供对机密数据的适当访问，并维护公众信任和保护隐私。
13.Protect Data Integrity: Emphasize state-of-the-art data security as part of Information Technology security practices for every system that is refreshed, architected, or replaced to address current and emerging threats; foster innovation and leverage new technologies to maintain protection.
13. 保护数据完整性：为应对当前和新兴威胁，强调最先进的数据安全作为信息技术安全实践的一部分，并确保每个信息系统的安全措施得到更新、重构或升级。促进创新并利用新技术来维持保护措施。
14.Convey Data Authenticity: Disseminate data sets such that their authenticity is discoverable and verifiable by users throughout the information lifecycle, consistent with open data practices, and encourage appropriate attribution from users.
14. 传递数据真实性：传播数据集，使用户在整个信息生命周期中都能发现和验证其真实性。这与开放数据政策也保持一致，并鼓励用户适当归属。
15. Assess Maturity: Evaluate the maturity of all aspects of agency data capabilities to inform priorities for strategic resource investment.
15. 评估成熟度：评估机构数据能力所有方面的成熟度，以为战略资源投资的优先事项提供依据。
16.Inventory Data Assets: Maintain an inventory of data assets with sufficient completeness, quality, and metadata to facilitate discovery and collaboration in support of answering key agency questions and meeting stakeholder needs.
16. 盘点数据资产：维护具有足够完整性、质量和元数据的数据资产清单，以促进发现和协作，以支持回答关键机构问题和满足利益相关者的需求。
17.Recognize the Value of Data Assets: Assign value to data assets based on maturity, key agency questions, stakeholder feedback, and applicable law and regulation to appropriately prioritize and document resource decisions.
17. 认识数据资产的价值：根据成熟度、关键机构问题、利益相关者反馈以及适用的法律和法规，对数据资产进行估值，以适当地确定资源决策的优先级并记录资源决策。
18.Manage with a Long View: Include data investments in annual capital planning processes and associated guidance to ensure appropriated funds are being used efficiently to leverage data as a strategic long-term asset.
18. 从长远视角进行管理：将数据投资纳入年度资本规划流程和相关指导，以确保有效利用批款资金，将数据作为战略长期资产加以利用。
19.Maintain Data Documentation: Store up-to-date and comprehensive data documentation in accessible repositories to facilitate use and document quality, utility, and provenance in support of informing key agency questions and meeting stakeholder needs.
19. 维护数据文档：将最新和全面的数据文档存储在可访问的存储库中，以促进使用和文档质量、效用和来源，以支持为关键机构问题提供信息和满足利益相关者的需求。
20. Leverage Data Standards: Adopt or adapt, create as needed, and implement data standards within relevant communities of interest to maximize data quality and facilitate use, access, sharing, and interoperability.
20. 利用数据标准：在相关利益社区内采用或调整、根据需要创建和实施数据标准，以最大限度地提高数据质量，促进使用、访问、共享和互操作性。
21. Align Agreements with Data Management Requirements: Establish terms and conditions for contracts, grants, cooperative agreements, and other agreements that meet data management requirements for processing, storage, access, transmission, and disposition.
21. 使协议与数据管理要求保持一致：制定合同、赠款、合作协议和其他协议的条款和条件，以满足处理、存储、访问、传输和处置数据管理要求。
22.Identify Opportunities to Overcome Resource Obstacles: Coordinate with stakeholders to identify mutually-acceptable cost recovery, shared service, or partnership opportunities to enable data access while conserving available resources to meet user needs.
22. 识别克服资源障碍的机会：与利益相关者协调，确定相互接受的成本回收、共享服务或伙伴关系机会，以实现数据访问，同时保存可用资源以满足用户需求。
23. Allow Amendment: Establish clear procedures to allow members of the public to access and amend federal data about themselves, as appropriate and in accordance with federal laws, regulations and policies, in order to safeguard privacy, reduce potential harm from inaccurate data, and promote transparency.
23. 允许修订：（略）。
24. Enhance Data Preservation: Preserve federal data in accordance with applicable law, regulation, policy, approved schedules, and mission relevance.
24. 加强数据保存：根据适用的法律、法规、政策、批准的时间表和任务相关性保存联邦数据。
25.Coordinate Federal Data Assets: Coordinate and share data assets across federal agencies to advance progress on shared and similar objectives, fulfill broader federal information needs, and reduce collection burden.
25. 协调联邦数据资产：协调和共享联邦机构之间的数据资产，以推进共享和类似目标的进展，满足更广泛的联邦信息需求，并减少收集负担。
26. Share Data Between State, Local, and Tribal Governments and Federal Agencies: Facilitate data sharing between state, local, and tribal governments and the Federal Government, where relevant and appropriate and with proper protections, particularly for programs that are federally funded and locally administered, to enable richer analyses for more informed decision-making.
26. 州、地方和部落政府与联邦机构之间共享数据：在相关和适当的情况下，促进州、地方和部落政府与联邦政府之间的数据共享，并提供适当的保护，特别是对于联邦资助和地方管理的方案，以便进行更丰富的分析，以便更明智的决策。
Promoting Efficient and Appropriate Data Use
促进高效和适当的数据使用
27.Increase Capacity for Data Management and Analysis: Educate and empower the federal workforce by investing in training, tools, communities, and other opportunities to expand capacity for critical data-related activities such as analysis and evaluation, data management, and privacy protection.
27. 提高数据管理和分析能力：通过投资于培训、工具、社区和其他机会，教育和增强联邦劳动力的能力，以扩大分析和评估、数据管理和隐私保护等关键数据相关活动的能力。
28. Align Quality with Intended Use: Data likely to inform important public policy or private-sector decisions must be of appropriate utility, integrity, and objectivity.
28. 使质量与预期用途保持一致：可能为重要公共政策或私营部门决策提供信息的数据必须具有适当的效用、完整性和客观性。
29.Design Data for Use and Re-Use: Design new data collections with the end uses and users in mind to ensure that data are necessary and of high enough quality to meet planned and future agency and stakeholder needs.
29. 设计用于使用和重复使用的数据：设计新的数据收集时考虑到最终用途和用户，以确保数据是必要的，质量足够高，以满足计划和未来的机构和利益相关者的需要。
30.Communicate Planned and Potential Uses of Data: Review data collection procedures to update and improve how planned and future uses of data are communicated, promoting public trust through transparency.
30. 沟通数据的计划和潜在用途：审查数据收集程序，以更新和改进如何沟通数据的计划和未来用途，通过透明度促进公众信任。
31. Explicitly Communicate Allowable Use: Regularly employ descriptive metadata that provides clarity about access and use restrictions for federal data, explicitly recognizes and safeguards applicable intellectual property rights, conveys attribution as needed, and optimizes potential value to stakeholders to maximize appropriate legal use.
31. 明确传达允许使用：定期使用描述性元数据，明确说明联邦数据的访问和使用限制，明确承认和保障适用的知识产权，根据需要传达归属，并优化利益相关者的潜在价值，以最大限度地提高适当的法律使用。
32.Harness Safe Data Linkage: Test, review, and deploy data linkage and analysis tools that use secure and privacy-protective technologies to address key agency questions and meet stakeholder needs while protecting privacy.
32. 利用安全数据链接：测试、审查和部署数据链接和分析工具，这些工具使用安全和隐私保护技术来解决关键机构问题，满足利益相关者的需求，同时保护隐私。
33.Promote Wide Access: Promote equitable and appropriate access to data in open, machine-readable form and through multiple mechanisms, including through both federal and non-federal providers, to meet stakeholder needs while protecting privacy, confidentiality, and proprietary interests.
33. 促进广泛访问：促进以开放、机器可读形式和多种机制公平和适当地访问数据，包括通过联邦和非联邦提供商，以满足利益相关者的需求，同时保护隐私、保密和专有利益。
34.Diversify Data Access Methods: Invest in the creation and usability of multiple tiers of access to make data as accessible as possible while minimizing privacy risk and protecting confidentiality.
34. 多样化数据访问方法：投资于多层访问的创建和可用性，以使数据尽可能可访问，同时最大限度地降低隐私风险和保护机密性。
35.Review Data Releases for Disclosure Risk: Review federal data releases to the public to assess and minimize the risk of re-identification, consistent with applicable laws and policies, and publish reviews to promote transparency and public trust.
35. 审查披露风险的数据发布：审查向公众发布的联邦数据，以评估和最大限度地降低重新识别的风险，并公布审查，以促进透明度和公众信任。
36. Leverage Partnerships: Create and sustain partnerships that facilitate innovation with commercial, academic, and other partners to advance agency mission and maximize economic opportunities, intellectual value, and the public good.
36. 利用伙伴关系：建立和维持伙伴关系，促进与商业、学术和其他伙伴的创新，以推进机构使命，最大限度地提高经济机会、智力价值和公益。
37. Leverage Buying Power: Monitor needs and systematically leverage buying power for private-sector data assets, services, and infrastructure to promote efficiency and reduce federal costs.
37. 利用购买力：监控需求，系统地利用私营部门数据资产、服务和基础设施的购买力，以提高效率和降低联邦成本。
38. Leverage Collaborative Computing Platforms: Periodically review and optimize the use of modern collaborative computing platforms to minimize costs, improve performance, and increase use.
38. 利用协作计算平台：定期审查和优化现代协作计算平台的使用，以最大限度地降低成本、提高性能和增加使用量。
39. Support Federal Stakeholders: Engage with relevant agencies to share expert knowledge of data assets, promote wider use, improve usability and quality, and meet mission goals.
39. 支持联邦利益相关者：与相关机构接触，分享数据资产的专业知识，促进更广泛的使用，提高可用性和质量，并实现任务目标。
40. Support Non-Federal Stakeholders: Engage with industry, academic, and other non-federal users of data to share expert knowledge of data assets, promote wider use, improve usability and quality, and advance innovation and commercialization.
40. 支持非联邦利益相关者：与行业、学术和其他非联邦数据用户接触，分享数据资产的专业知识，促进更广泛的使用，提高可用性和质量，并推进创新和商业化。
网站已经公开了2020年、2021年两年的行动计划，有兴趣朋友可以自行上网获取。网站链接：Federal Data Strategy
除此以外，Data.gov为大众提供了25万多个实时更新的数据集，这些恐怕都是值得我们借鉴的实际行动。
译者介绍： 石健卿
文章来源：微信公众号 数据力学