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相关概念视频

Levels of Use of a GIS01:29

Levels of Use of a GIS

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Geographic Information Systems (GIS) operate across three levels of application, each representing an increasing degree of complexity: data management, analysis, and prediction. These levels reflect the expanding functionality and versatility of GIS technology in handling spatial data for diverse purposes.Data ManagementAt its foundational level, GIS serves as a tool for data management, enabling the input, storage, retrieval, and organization of spatial data. This level is often employed in...
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The issues and trends in healthcare delivery are constantly changing. The COVID-19 pandemic is one recent issue that wreaked havoc on healthcare systems, causing a shortage of healthcare workers, high demand for medicines and supplies, and increased medical expenditure due to a lack of insurance. Other issues include rising healthcare costs and care fragmentation.
Cost Containment
Payment for healthcare services has historically promoted adoption of costly and often unnecessary or inefficient...
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We have discussed why we form relationships, what attracts us to others, and different types of love. But what determines whether we are satisfied with and stay in a relationship? One theory that provides an explanation is social exchange theory. According to social exchange theory, we act as naïve economists in keeping a tally of the ratio of costs and benefits of forming and maintaining a relationship with others (Rusbult & Van Lange, 2003).
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GIS manipulation and analysis functions are vital for decision-making and planning. These activities range from data retrieval tasks, such as selecting information based on specific criteria, to advanced analytical techniques that address complex spatial problems.One critical GIS analysis method is overlaying, which combines multiple data layers to examine impacts. For example, overlaying a river-dammed lake boundary with road networks can identify affected infrastructure. Another common...
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The process of hypothesis testing based on the P-value method includes calculating the P- value using the sample data and interpreting it.
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As a system undergoes a change, its internal energy can change, and energy can be transferred from the system to the surroundings, or from the surroundings to the system. 
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数据团结:通过数字工具实现公共价值.

Seliem El-Sayed1, Ilona Kickbusch2, Barbara Prainsack1

  • 1Department of Political Science, University of Vienna, Vienna, Austria.

Global public health
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PubMed
概括
此摘要是机器生成的。

数据治理需要超越个人控制,以解决社会不平等问题. 基于团结的数据治理优先考虑公共价值和公平的风险分配,使用像PLUTO这样的工具进行评估.

关键词:
数据治理数据治理可持续发展目标10:减少不平等可持续发展目标12:负责任的消费和生产可持续发展目标3:健康和福祉可持续发展目标9:工业,创新和基础设施数据团结数据团结股权资本 股权资本公平的公平的公平.公共价值的公共价值.

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科学领域:

  • 数字健康数字健康
  • 数据治理数据治理
  • 公共卫生政策 公共卫生政策

背景情况:

  • 目前的数据治理框架主要保护数据主体.
  • 数字实践会产生更广泛的社会影响和权力不平衡.
  • 现有的框架未能解决数字社会中普遍存在的不平等问题.

研究的目的:

  • 建议从个人数据控制转向以股权为中心的数据治理.
  • 引入基于团结的数据治理 (数据团结) 作为一个新的框架.
  • 澄清公共价值在数据治理中的作用和运作.

主要方法:

  • 数据团结的概念框架开发.
  • 根据公共价值,风险和私人利益来优先考虑数据使用.
  • 引入PLUTO工具,用于评估数据使用的公共价值.

主要成果:

  • 数据团结优先考虑数据的使用,促进公共价值的产生.
  • 高风险的数据使用受到禁止或严格监管.
  • 从数据使用中获得的私人利益和低公共价值的利被征税用于再投资.

结论:

  • 基于团结的数据治理为数据管理提供了更公平的方法.
  • 通过像PLUTO这样的工具实现公共价值对全球健康数据治理至关重要.
  • 该框架促进数据使用带来的利益和风险的公平贡献.