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1.
《Government Information Quarterly》2022,39(4):101705
Public sector organizations at all levels of government increasingly rely on Big Data Algorithmic Systems (BDAS) to support decision-making along the entire policy cycle. But while our knowledge on the use of big data continues to grow for government agencies implementing and delivering public services, empirical research on applications for anticipatory policy design is still in its infancy. Based on the concept of policy analytical capacity (PAC), this case study examines the application of BDAS for early crisis detection within the German Federal Government—that is, the German Federal Foreign Office (FFO) and the Federal Ministry of Defence (FMoD). It uses the nested model of PAC to reflect on systemic, organizational, and individual capacity-building from a neoinstitutional perspective and allow for the consideration of embedded institutional contexts. Results from semi-structured interviews indicate that governments seeking to exploit BDAS in policymaking depend on their institutional environment (e.g., through research and data governance infrastructure). However, specific capacity-building strategies may differ according to the departments' institutional framework, with the FMoD relying heavily on subordinate agencies and the FFO creating network-like structures with external researchers. Government capacity-building at the individual and organizational level is similarly affected by long-established institutional structures, roles, and practices within the organization and beyond, making it important to analyze these three levels simultaneously instead of separately. 相似文献
2.
《Government Information Quarterly》2021,38(4):101612
Recently, attention has been paid to the opportunities of data sharing across government sectors for complex public problems. These so-called ‘data collaboratives’ are seen as a novel way of leveraging different sources of data and expertise for societal impact. Data collaboratives come with new challenges that might require new governance structures and processes. So far, scant attention has been paid in the literature to data collaborative governance. This study aims to fill that gap. Building upon the collaborative governance and information sharing literature, a framework for Data Collaborative Governance is developed. This framework was tested in a living lab that focused on the public problem of anti-social behavior. Empirical data was collected over a period of one and a half years and analyzed based on an abductive research approach. The findings show that data sharing adds new elements to collaborative governance theory and practice. This study also demonstrates that a living lab is a promising methodology for studying data collaboratives. Finally, it shows that working across boundaries of organizations and sharing data to address complex problems in more collaborative ways has the potential to generate insights for complex public problems. 相似文献
3.
《Government Information Quarterly》2022,39(2):101645
Computational algorithms and automated decision making systems that include them offer potential to improve public policy and organizations. But computational algorithms based on biased data encode those biases into algorithms, models and their outputs. Systemic racism is institutionalized bias with respect to race, ethnicity and related attributes. Such bias is located in data that encode the results and outputs of decisions that have been discriminatory, in procedures and processes that may intentionally or unintentionally disadvantage people based on race, and in policies that may discriminate by race. Computational algorithms may exacerbate systemic racism if they are not designed, developed, and used–that is, enacted–with attention to identifying and remedying bias specific to race. Advancing social equity in digital governance requires systematic, ongoing efforts to assure that automated decision making systems, and their enactment in complex public organizational arrangements, are free from bias. 相似文献
4.
Gerald GrantAuthor Vitae Shawn McKnightAareni UruthirapathyAuthor Vitae Allen BrownAuthor Vitae 《Government Information Quarterly》2007
As shared services organizations (SSO) become more popular as a service management and delivery option in government, properly defining and setting up the governance structure continues to be a key success factor. This paper explores the options and issues to consider when selecting and implementing shared services governance including topics such as oversight, accountability, culture, management of resources, and of day-to-day operations. Shared services organizations are increasingly common in private sector companies and the particular challenges involved in the governance of an SSO in a public service context are highlighted and discussed. 相似文献
5.
大数据是IT业颠覆性的技术变革。通过表面的数据,揭示其背后隐藏的有价值的信息,是大数据的核心。图书馆利用大数据将面临许多挑战,图书馆如何获取并存储大数据,大数据在图书馆有哪些应用能促进图书馆的创新发展,大数据的相关技术如Hadoop、Hbase、云存储、云计算、数据分析与挖掘技术的研究,将会是大数据时代图书馆研究的主要问题。 相似文献
6.
数据共享视角下跨部门政府数据治理框架构建 总被引：2，自引：1，他引：1
[目的/意义] 跨部门的政府数据共享面临着巨大挑战，部门之间数据隔离，数据共享进展缓慢。引入跨部门的政府数据治理有助于促进政府的信息资源共享，提升政府服务水平和服务对象的满意度。针对跨部门政府数据治理的相关实践亟需科学理论的指导。[方法/过程] 首先对政府数据治理的含义进行分析和界定，对已有的数据治理框架进行总结论述，然后分析政府数据治理的特殊性所在。[结果/结论] 在国内外认可度较高的数据治理框架基础上，结合政府数据治理的特殊性，提出我国跨部门政府数据治理框架--CGCS数据治理框架，由战略目标、规范与标准、关注范围、治理主体、过程、方法与技术6方面内容组成，并对框架每一部分结合我国实际情况进行阐述。最后，对CGCS数据治理框架在跨部门政府数据治理实践中的应用进行示例分析，阐明CGCS数据治理框架的可用性。 相似文献
7.
数据治理是数据管理的核心职能。在多部门协同治理数据问题的大数据时代,档案部门应从全局、资产、融入、生态等视角出发,有效利用数据治理的机制、方法和工具,积极参与高层次数据管理活动,尤其关注数据治理格局中多主体协同关系的建立。建议国家档案局增补为促进大数据发展部际联席会议成员单位,并主导建立高层次电子档案治理协作组;基层档案部门以机构内容管理为职责定位;档案行业成为内容管理系统研发和实施的支撑行业。 相似文献
8.
Government agencies are increasingly using social media to connect with those they serve. These connections have the potential to extend government services, solicit new ideas, and improve decision-making and problem-solving. However, interacting via social media introduces new challenges related to privacy, security, data management, accessibility, social inclusion, governance, and other information policy issues. The rapid adoption of social media by the population and government agencies has outpaced the regulatory framework related to information, although the guiding principles behind many regulations are still relevant. This paper examines the existing regulatory framework and the ways in which it applies to social media use by the U.S. federal government, highlighting opportunities and challenges agencies face in implementing them, as well as possible approaches for addressing these challenges. 相似文献
9.
随着数字化转型的深入推进,企业数据治理体系日趋成熟,企业档案与数据资产的协同管理问题日益凸显。本文综合运用案例研究法和行动研究法,从术语、资源、业务、系统、组织和制度等维度构建分析框架。企业档案与数据资产的协同管理存在术语不统一、体制相割裂、方法不衔接、系统未整合等问题,需进一步明确协同目标,厘清档案数据、档案部门和档案系统在数据资产管理框架体系中的定位,按照数据档案化治理和档案数据化开发两条发展主线,通过创新协同机制、促进方法集成、联通数据标准、推动系统转型升级等策略实现多维度的协同管理。 相似文献
10.
政府大数据治理规则体系构建研究构想 总被引：2，自引：1，他引：1
[目的/意义] 弥补大数据发展应用背景下政府大数据治理规则体系缺失及其研究的不足。[方法/过程] 从大数据认知多维视角出发,分析大数据治理主体、治理客体、治理活动和治理风险4个方面所面临的挑战及其大数据规则制定需求;诊断政府大数据治理规则体系构建研究的阻碍问题及原因。以公共价值理论、数字连续性理论和多元价值理论为主要理论支持,提出政府大数据治理规则体系构建研究的基本框架。[结果/结论] 明晰了政府大数据治理规则体系构建的关键性要素及其关系,对构建政府大数据治理的长效规则体系提供了一种多维视角的研究思路和一个综合集成的研究方案。 相似文献
11.
Demchenko Yuri Zhao Zhiming Grosso Paola Wibisono Adianto de Laat Cees 《中国科技资源导刊 (中国信息导报)》2013,(1):30-35
首先探讨大数据科学（Big Data Science）给现代和未来科研数据基础设施（SDI）带来的挑战,并参考不
同科研团体的工作对数据管理、访问控制和安全要求进行定义,然后介绍科研数据生命周期管理（SDLM）模型,分析
所有的主要阶段,反映现代e-Science的数据管理特性,提出SDI 通用架构模型,为利用现代技术和最佳实践构建以互
用性数据或项目为中心的SDI 奠定了基础,最后对如何利用基于云的现代基础设施服务配置模型顺利实现文中提出的
SDLM和SDI 模型进行阐述,解决SDI 资源的联合访问控制问题,为科研团体提供了一种灵活的访问控制和身份管理模
型。 相似文献
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13.
大数据作为多重属性复合的新兴产物,为图书馆的信息数据管理提供了全新的思路和方法,但同时也给数据治理带来了前所未有的挑战。本研究结合SWOT分析法,解析并构建了数据生态系统,旨在改善图书馆生态系统中信息数据的应用效率,并进一步探讨数据治理的路径,以期为图书馆数据治理系统的理论研究及数据管理的创新提供一定的借鉴和启发。 相似文献
14.
This paper presents a review of open data research based on bibliometric analysis of publications in Web of Science from 1998 to 2016. It shows that research on open data has grown rapidly since 2009 with the development of various open data initiatives. We identify the different themes using science mapping and performance analysis. The most important themes are semantic web, open government, and crowdsourcing. The basic and transversal themes are data sharing and public sector information. As for the emerging themes, these are Big Data and open government data. In addition, data journalism, monitoring, and recommender systems are specific themes that deserve special attention. The UK and the USA are the leading publishing countries, both in theoretical and practical research on open data. In China, most researchers focus on practical research, and there have been efforts to promote the development of open data. Papers introducing large‐scale projects receive more attention and citation quickly. Recently, researchers have been publishing more on objective topics, including possible issues and dilemmas in the era of Big Data and many problems such as budgets, ownership, licensing, culture, and sustainable development. 相似文献
15.
高校图书馆数据治理及其框架 总被引：1，自引：0，他引：1
[目的/意义]数据治理是对机构的数据资产管理行使权力和控制的活动集合。将高校图书馆视为以数据为核心业务的典型行业,引入数据治理理论框架,意在促进高校图书馆基于数据资产的服务创新和价值创造。[方法/过程]首先阐明数据治理及其意义和作用,然后分析归纳高校图书馆数据的类型和特点,并就目前高校图书馆数据治理的现状和存在问题进行梳理和总结。[结果/结论]在国际权威机构数据治理框架的基础上,结合高校图书馆行业特点,创新性地提出我国高校图书馆数据治理框架——CALib框架,包括促成因素、范围和实施评估3个子框架,并对每个子框架进行详细阐述。 相似文献
16.
Scott Crawford 《Public Library Quarterly》2013,32(4):387-393
More and more organizations are using Big Data to support evidence-based, customer-centric decisions and public libraries are following suit. This article presents the reasons behind a rise in Big Data and discusses the solutions that public libraries can apply to add value to the patron experience. 相似文献
17.
Deen Freelon 《广播与电子媒介杂志》2013,57(1):59-75
The widespread availability of analytical tools for Big Data offers enormous opportunities and challenges for communication researchers. In contrast to user-generated texts, digital trace data (evidence of online user activities such as hyperlinks and retweets) represent a new methodological frontier for the field. However, interpretive strategies remain scattered and ad hoc with few best practices to guide them. To help remedy this situation, this article reviews recent scholarship in both communication and social computing research that has incorporated three common types of trace data: hyperlinks, Twitter followers, and retweets. It finds that while researchers in both fields have interpreted each trace in a variety of ways, they have largely declined to explain the validity of their interpretations. 相似文献
18.
Daniel Goldberg Miriam Olivares Zhongxia Li Andrew G. Klein 《Journal of Map & Geography Libraries》2014,10(1):100-122
In upcoming years, two major changes in the computing landscape will reshape how map and GIS data libraries (MGDLs) will be required to perform their core functions in the future. These advancements—cloud computing and the “Big Data era”—offer opportunities and challenges for libraries, but most dramatically changes. Commercial cloud computing solutions are available as on-demand service; low-cost, internal private clouds are now a financial possibility. Simultaneously, Geographic Information Science (GISci) data and services have advanced at an ever-increasing pace into the “Big Data,” swelling the types and amounts of GIS data and services available. These two shifts have and will impact the entire GIS world and MGDLs, in response, and will now be required to collect, curate, and make available more data and services than ever. The MGDL community must be prepared to respond and react in order to remain effective. This article explores the evolving landscapes within which MGDLs must operate and examines how their roles and operational organization will be impacted. The hope of the authors is that such analyses will spark community-driven discussion to motivate the next major phase of research and implementation in the world of MGDLs. 相似文献
19.
Local governments are increasingly establishing functional decentralized agencies, such as autonomous organizations, public companies, foundations and public business entities to provide public services. Furthermore, they are also introducing the private sector, contracting out public services to a private company and creating mixed companies. Our aim is to analyze the effect of functional decentralization and externalization (outsourcing or contracting out) processes on public transparency levels, since theoretically, they are aimed toward good governance and accountability. To do so, we use a sample composed of the 110 largest Spanish cities for the period 2008–2010. The results show that decentralized agencies, especially public companies and foundations, impact positively on levels of public transparency. However, there is no evidence that suggests that the introduction of the private sector, using outsourcing and mixed companies, affects the transparency of local governments. 相似文献
20.
[目的/意义]数据治理是实现大数据驱动公共安全治理模式变革的基础,构建体现领域特殊性与敏感性的公共安全数据治理体系为开展科学研究与治理实践提供理论框架指导。[方法/过程]从交叉学科视角出发,对公共安全数据治理的概念进行溯源,并剖析其发展的学科理论基础和驱动力;在此基础上解析代表性文献,梳理公共安全数据治理的解决问题、治理主体、客体、工具和目标五个关键要素的内容范畴与核心内涵,进而构建涵盖多要素、不同维度的数据治理体系逻辑框架。[结果/结论]该框架以数据流为连接点凸显学科之间的知识交叉融合,统筹各关键要素并指出公共安全数据治理的关键议题包括应用情境搭建、数据资源体系建设、主体决策机制建设以及治理工具选择。 相似文献