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The availability of healthcare data has exponentially grown, both in quantity and complexity. The speed of this evolution has generated new challenges for translating complex data into effective evidence-informed policy. Visual analytics offers new capacity to analyze healthcare systems and support better decision-making. We conducted a systematic scoping review to look for evidence of visual analytics approaches being applied to mental healthcare systems and their use in driving policy. We found 79 relevant studies and categorized them in two ways: by study purpose and by type of visualization. The majority (67.1%) of the studies used geographical maps, and 11% conducted highly complex studies requiring novel visualizations. Significantly, only 15% of the studies provided information indicating high levels of usability for policy and planning. Our findings suggest that while visual analytics continues to evolve rapidly, there is a need to ensure this evolution reflects the practical needs of policy makers. 相似文献
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Recently, patient safety and healthcare have gained high attention in professional and health policy-makers. This rapid growth causes generating a high amount of data, which is known as big data. Therefore, handling and processing of this data are attracted great attention. Cloud computing is one of the main choices for handling and processing of this type of data. But, as far as we know, the detailed review and deep discussion in this filed are very rare. Therefore, this paper reviews and discusses the recently introduced mechanisms in this field as well as providing a deep analysis of their applied mechanisms. Moreover, the drawbacks and benefits of the reviewed mechanisms have been discussed and the main challenges of these mechanisms are highlighted for developing more efficient healthcare big data processing techniques over cloud computing in the future. 相似文献
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The computerized healthcare information system has undergone tremendous advancements in the previous two decades. Medical institutions are paying further attention to the replacement of traditional approaches that can no longer handle the increasing amount of patient data. In recent years, the healthcare information system based on big data has been growing rapidly and is being adapted to medical information to derive important health trends and support timely preventive care. This research aims to evaluate organization-driven barriers in implementing a healthcare information system based on big data. It adopts the analytic network process approach to determine the aspect weight and applies VlseKriterijumska Optimizacija I Kzompromisno Resenje (VIKOR) to conclude a highly appropriate strategy for overcoming such barriers. The proposed model can provide hospital managers with forecasts and implications that facilitate the withdrawal of organizational barriers when adopting the healthcare information system based on big data into their healthcare service system. Results can provide benefits for increasing the effectiveness and quality of the healthcare information system based on big data in the healthcare industry. Therefore, by understanding the sequence of the importance of resistance factors, managers can formulate efficient strategies to solve problems with appropriate priorities. 相似文献
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基于Web of Science（WoS）数据库,本文运用文献计量学方法和可视化工具对比分析了2009-2016年中美大数据研究论文的跨学科性发展态势,研究内容包括跨学科性（Rao-Stirling Index）测度、核心学科分布以及跨学科性与引用影响的关系,并应用VOSviewer将两国的学科分布进行了可视化呈现。结果显示,尽管中美两国论文的跨学科性都在逐年增强,研究期间美国论文的跨学科性始终高于中国。美国的大数据研究参考的学科数量更多,且学科分布更均衡,涉及的主要学科包括数学与计算机科学、生物医学与健康科学以及社会科学与人文科学;中国的大数据研究涉及学科较少,主要集中在数学和计算机科学领域。论文涉及的学科数量与被引百分位显著相关,美国论文的跨学科性与引用影响之间存在一定相关性,但中国论文的这种关系不显著。 相似文献
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During the coronavirus pandemic, policy makers need to interpret available public health data to make decisions affecting public health. However, the United States’ coronavirus response faced data gaps, inadequate and inconsistent definitions of data across different governmental jurisdictions, ambiguous timing in reporting, problems in accessing data, and changing interpretations from scientific institutions. These present numerous problems for the decision makers relying on this information. This paper documents some of the data pitfalls in coronavirus public health data reporting, as identified by the authors in the course of supporting data management for New England’s coronavirus response. We provide recommendations for individuals to collect data more effectively during emergency situations such as a COVID-19 surge, as well as recommendations for institutions to provide more meaningful data for various users to access. Through this, we hope to motivate action to avoid data pitfalls during public health responses in the future. 相似文献
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我国科技政策学研究态势及国际比较 《科学学研究》2017,35(9):1289-1300
本文采用科学计量学方法,以科技论文和资助项目为主要资料,对2011年以来国际上发表的科技政策研究论文、以及美国SciSIP计划、日本SciREX计划和中国国家自然科学基金委员会管理科学部“科技管理与政策”相关的规划布局和资助项目进行定量和定性综合分析,揭示国际和我国科技政策学的研究态势。美国科技政策“学”强调“科学基础”,主要侧重于服务政府部门的科技政策制定和政策过程的科学化;日本则倾向“学科建设”,包括国家重要政策议题的专题研究（任务导向研究）,针对科技政策学术共同体的课题资助（自由申请研究）,机构设置与人才培养,以及数据基础设施建设。发展我国的科技政策学,建议同时借鉴日本学科建设的思路以及美国协调各政府部门政策过程的思路;建议加强社会科学与自然科学的跨学科融合研究,考虑设置“科技政策研究”专项资助渠道与多元资助机制;建议将数据基础设施建设作为一项基础性、战略性任务;建议建立政策研究界和决策者之间的建制性交流研讨机制等。 相似文献
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为探讨大数据的概念及全球的研究现状,以Web of Science TM核心集合作为数据源,对时间为2010—2016年期间有关大数据的经济管理类核心期刊进行文献梳理研究,利用知识图谱法、共词分析法和引文分析法对大数据研究领域的基础知识、知识演进以及研究热点及趋势展开分析和评述。基于文献计量软件Citespace绘制出时区视图、聚类图等,得出对大数据概念的多视角理解以及研究热点和研究趋势。 相似文献
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在大数据快速发展的背景下，制定科学、合理的大数据政策体系，支撑大数据高质量发展变得日益迫切。本文通过构建“政策工具-政策主题词”二维分析框架，对2000年以来国家层面有关大数据发展的政策文本进行了分析，从大数据政策的演进脉络、政策关系网络、政策主题词演进态势以及政策工具的使用情况等四个方面探究了大数据政策文本内容。研究结果表明：我国大数据政策发展，大致经历了从强调基础设施建设到关注产业培育与创新，再到构建大数据政策体系的发展过程。在发展的不同阶段，政策主题词与当时的经济、社会、国际环境密切相关。目前我国已经初步建立起大数据政策网络体系，但整体还处于初步发展阶段，大数据政策的顶层设计还不健全，现有政策工具中知识产权保护类政策工具和政府采购类政策工具使用较少等，仍需要进一步加强完善。 相似文献
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《International Journal of Information Management》2016,36(3):403-413
Big data has captured the interests of scholars across many disciplines over the last half a decade. Business scholars have increasingly turned their attention to the impact of this emerging phenomenon. Despite the rise in attention, our understanding of what big data is and what it means for organizations and institutional actors remains uncertain. In this study, we conduct a systematic review on “big data” across business scholarship over the past six years (2009–2014). We analyzed 219 peer-reviewed academic papers from 152 journals from the most comprehensive business literature database. We conducted the systematic review both quantitatively and qualitatively using the data analysis software NVivo10. Our results reveal several key insights about the scholarly investigation of big data, including its top benefits and challenges. Overall, we found that big data remains a fragmented, early-stage domain of research in terms of theoretical grounding, methodological diversity and empirically oriented work. These challenges serve to improve our understanding of the state of big data in contemporary research, and to further prompt scholars and decision-makers to advance future research in the most productive manner. 相似文献
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全面创新改革试验（以下简称“全创改”）是区域层面落实创新驱动发展战略的重要举措,是中国特色的创新政策转型实践,在一定程度上代表了创新政策未来的演进方向。然而由于政策系统复杂度高、政策资料无法公开获取等原因,全创改面临理论研究滞后于政策实践、政策实践缺乏理论研究支撑等问题。本文从政策评估视角出发,结合全面创新改革试验的政策特点和评估需求,提出采用网络大数据分析间接评估改革试验政策影响的方法。通过收集媒体和社会公众等政策利益相关者对全创改的舆论信息,识别相关信息的传播规律和特征,分析社会公众对全创改的重点关注内容,为政府优化和完善改革试验政策提供基于事实证据的决策依据,并结合评估结果提出完善改革试验的政策建议。 相似文献
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Anderson C Stackhouse R Shaw A Iredale R 《Public understanding of science (Bristol, England)》2011,20(2):146-162
While there has been research conducted on public views about ethical and social aspects of the National DNA Database (NDNAD), there is little which focuses on views of young people, in particular those whose details are held on the NDNAD. We describe an engagement activity developed in South Wales to engage young offenders with ethical and social issues surrounding the NDNAD--a Mock Trial--and how we facilitated the presentation of their views to policy makers. We discuss the successes and challenges we encountered with engaging young offenders, decisions that the young people reached about possible future policies for the NDNAD at the Mock Trial, and their contribution to the decision-making process. 相似文献
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Big Data Analytics (BDA) is increasingly becoming a trending practice that generates an enormous amount of data and provides a new opportunity that is helpful in relevant decision-making. The developments in Big Data Analytics provide a new paradigm and solutions for big data sources, storage, and advanced analytics. The BDA provide a nuanced view of big data development, and insights on how it can truly create value for firm and customer. This article presents a comprehensive, well-informed examination, and realistic analysis of deploying big data analytics successfully in companies. It provides an overview of the architecture of BDA including six components, namely: (i) data generation, (ii) data acquisition, (iii) data storage, (iv) advanced data analytics, (v) data visualization, and (vi) decision-making for value-creation. In this paper, seven V's characteristics of BDA namely Volume, Velocity, Variety, Valence, Veracity, Variability, and Value are explored. The various big data analytics tools, techniques and technologies have been described. Furthermore, it presents a methodical analysis for the usage of Big Data Analytics in various applications such as agriculture, healthcare, cyber security, and smart city. This paper also highlights the previous research, challenges, current status, and future directions of big data analytics for various application platforms. This overview highlights three issues, namely (i) concepts, characteristics and processing paradigms of Big Data Analytics; (ii) the state-of-the-art framework for decision-making in BDA for companies to insight value-creation; and (iii) the current challenges of Big Data Analytics as well as possible future directions. 相似文献
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大数据时代的到来,促进了计算机科学技术的飞速发展,同时也给科技情报分析方法的研究带来发展机遇。有效的数据分析方法是获取有价值情报的基础。科技政策数据分析是指利用计算机处理技术自动地从科技政策数据中提取简练且有代表性的语句,识别出数据的核心内容或用户感兴趣的语句内容。基于科技政策数据内容的特点,本文提出适用于科技政策数据内容特点的数据分析方法,设计并构建科技政策数据内容分析实验系统,验证了本文提出方法的有效性。为探索深层次的科技数据情报分析方法提供了新思路。 相似文献
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【目的/意义】随着网络购物的普及,在线评论成为影响消费者、销售者和生产者决策的重要数据。大数据
时代,在线评论呈现出多源异构、爆发式增长的特点,难以为用户的购买决策和商家竞争提供有力的情报支撑。【方
法/过程】本文利用多源异构的在线评论数据构建知识图谱,提出了一种基于多源异构数据构建知识图谱的框架,
模式层构建围绕在线评论的信源、内容以及形式构建,最终形成知识图谱的概念框架,并运用word2vec从多源异构
文本中获取实体、关系和属性,并进行数据融合与知识图谱分析。【结果/结论】实验部分以手机商品在线评论为例,
验证了本文所构建的知识图谱对在线评论相关研究及挖掘的有效性,研究结果揭示了多源异构在线评论数据的特
点,为大数据环境下在线评论信息组织、展示和挖掘提供了新的研究视角。【创新/局限】运用知识图谱对在线评论
进行描述,有效解决信息过载、多源异构信息融合等问题。本文采用半自动化的方式构建知识图谱,未来考虑引入
无监督的方法提高构建效率。 相似文献
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In recent years, policy approaches that build upon the notion of innovation systems have enjoyed increasing attention in science, technology and innovation policy. But while the usefulness of systemic thinking in policy-making has been demonstrated in a large number of empirical settings, we still lack a detailed understanding of the dynamics at play when policy makers address systemic problems. In this paper, we show how complex interdependencies and the uncertain nature of technological change shape the process of targeted policy interventions in socio-technical systems. Toward this end we analyzed the evolution of the German feed-in tariff (FIT) system for solar photovoltaic power, a highly effective and widely copied policy instrument targeted at fostering the diffusion and development of renewable energy technologies. We find that the policy has been subject to a considerable amount of changes, many of which are the result of policy makers addressing specific system issues and bottlenecks. Interestingly, however, often these issues themselves were driven by unforeseen technological developments induced by previous policy interventions. We argue that the pattern of policy serving as both a solution to and a driver of technological bottlenecks shows strong similarities with what Rosenberg (1969) called ‘compulsive sequences’ in the development of technical systems. By shedding more light on how the characteristics of socio-technical systems affect policy interventions, our framework represents a first step toward more closely integrating the literature on innovation systems with the work on policy learning. 相似文献
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本文采用纵贯研究、内容分析、访谈相结合的定性研究方法,以推动我国物联网产业发展的三个政策决策过程为研究对象,旨在探讨不确定性的情况下,互动是如何帮助政府进行政策决策的。研究结论表明:第一,互动是政府进行宏观政策决策的基石。新兴产业的政策决策是由数个渐进式决策阶段组成,每个阶段中建立在互动基础上的微观政策的决策和实施为推动力量。第二,新兴产业政策决策过程中存在五种互动方式,并且互动主导者因行政职位或决策事项的不同采取不同的互动方式。第三,随着决策事项的渐进式演变,互动规律存在显著差异。研究结论为政策决策者建立互动导向的政策决策机制,更好地推动我国战略性新兴产业发展提供了依据与建议。 相似文献
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Our lives are increasingly intertwined with the digital realm, and with new technology, new ethical problems emerge. The academic field that addresses these problems—which we tentatively call ‘digital ethics’—can be an important intellectual resource for policy making and regulation. This is why it is important to understand how the new ethical challenges of a digital society are being met by academic research. We have undertaken a scientometric analysis to arrive at a better understanding of the nature, scope and dynamics of the field of digital ethics. Our approach in this paper shows how the field of digital ethics is distributed over various academic disciplines. By first having experts select a collection of keywords central to digital ethics, we have generated a dataset of articles discussing these issues. This approach allows us to generate a scientometric visualisation of the field of digital ethics, without being constrained by any preconceived definitions of academic disciplines. We have first of all found that the number of publications pertaining to digital ethics is exponentially increasing. We furthermore established that whereas one may expect digital ethics to be a species of ethics, we in fact found that the various questions pertaining to digital ethics are predominantly being discussed in computer science, law and biomedical science. It is in these fields, more than in the independent field of ethics, that ethical discourse is being developed around concrete and often technical issues. Moreover, it appears that some important ethical values are very prominent in one field (e.g., autonomy in medical science), while being almost absent in others. We conclude that to get a thorough understanding of, and grip on, all the hard ethical questions of a digital society, ethicists, policy makers and legal scholars will need to familiarize themselves with the concrete and practical work that is being done across a range of different scientific fields to deal with these questions. 相似文献