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相关概念视频

GIS Software, Hardware, and Sources of GIS Data01:23

GIS Software, Hardware, and Sources of GIS Data

55
A Geographic Information System (GIS) combines specialized software and hardware to effectively manage, analyze, and present spatial and related data. GIS software includes critical functionalities such as a user interface for easy navigation, database management tools for handling spatial and attribute data, and data retrieval features for efficient access. Analytical tools transform raw data into insights, while display functions produce maps and reports in various formats for effective...
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Manipulation and Analysis01:21

Manipulation and Analysis

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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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Statistical Software for Data Analysis and Clinical Trials01:12

Statistical Software for Data Analysis and Clinical Trials

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Statistical software is pivotal in data analysis and clinical trials by providing tools to analyze data, draw conclusions, and make predictions. These software packages range from simple data management applications to complex analytical platforms, supporting various statistical tests, models, and simulation techniques. Their significance lies in their ability to handle vast amounts of data with precision and efficiency, enabling researchers to validate hypotheses, identify trends, and make...
532
Levels of Use of a GIS01:29

Levels of Use of a GIS

48
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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Introduction to R01:11

Introduction to R

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R is a powerful software environment for statistical computing and graphics. Originating as an implementation of the S language, developed at Bell Laboratories, R has evolved into a robust, open-source statistical software favored by statisticians and data scientists worldwide. Its comprehensive suite includes data manipulation, calculation, and graphical display capabilities, making it versatile for data analysis and visualization. Its programming language is at the core of R's...
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Data are individual items of information obtained from a population or sample. Data may be classified as qualitative (categorical), quantitative continuous, or quantitative discrete. Because it is not practical to measure the entire population in a study, researchers use samples to represent the population. A random sample is a representative group from the population chosen by using a method that gives each individual in the population an equal chance of being included in the sample. Random...
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Comparing Bibliometric Analysis Using PubMed, Scopus, and Web of Science Databases
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探索自由可用的数据工具,以支持开放数据和开放科学.

Christine Hislop1, Katie Pierce Farrier2, Elizabeth Roth3

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概括
此摘要是机器生成的。

图书馆员可以通过采用五种促进开放科学和开放数据实践的免费工具来加强研究支持. 这些资源有助于项目管理,数据清理,规划,标准化和非识别,赋予研究人员权力.

关键词:
开放数据是开放的数据.数据管理数据管理开放科学是一个开放的科学.

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科学领域:

  • 图书馆和信息科学 图书馆和信息科学
  • 研究 数据管理 数据管理
  • 开放科学是一个开放的科学.

背景情况:

  • 图书馆员在促进研究完整性和可重复性方面发挥着至关重要的作用.
  • 促进开放科学和开放数据实践是信息专业人员的关键责任.
  • 研究人员需要可访问的工具来有效地实施开放科学原则.

研究的目的:

  • 识别和描述支持开放科学实践的自由可用的工具.
  • 为图书馆员提供实用资源,以帮助研究人员采用开放科学.
  • 为研究生命周期的不同阶段强调特定工具的有用性.

主要方法:

  • 探索五种不同的,可自由访问的软件工具.
  • 根据其在支持开放科学方面的功能对工具的分类.
  • 描述每个工具的特点和好处,供研究人员和图书馆员使用.

主要成果:

  • 开放科学框架 (OSF) 提供项目管理,数据共享和存储.
  • OpenRefine 简化了数据的清理和格式化.
  • DMPTool为数据管理计划提供模板,符合资助人的任务.
  • 美国国家卫生研究院常用数据元素 (NIH Common Data Elements) 作为标准化数据元素的存储库.
  • 在非识别临床文本数据方面,NLM Scrubber有助于.

结论:

  • 将这五种工具整合到图书馆服务中,可以显著提高对研究人员的支持.
  • 信息专业人士可以积极推广这些资源,以培养开放科学的文化.
  • 采用这些工具使研究人员能够坚持开放科学和数据管理的最佳实践.