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Data validation is an essential part of a comprehensive assessment. Validation is confirming or verifying and opening the door to gathering more assessment data as it clarifies vague or unclear data. The process of checking and verifying the collected information is called data validation. The primary purpose of data validation is to ensure data is as free from error, bias, and misinterpretation as possible.
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German physicist Wilhelm Röntgen (1845–1923) was experimenting with electrical current when he discovered that a mysterious and invisible "ray" would pass through his flesh but leave an outline of his bones on a screen coated with a metal compound. In 1895, Röntgen made the first durable record of the internal parts of a living human: an "X-ray" image (as it came to be called) of his wife’s hand. Scientists worldwide quickly began their own experiments with...
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The physical assessment examines the patient for objective data that defines the patient's condition, and aids in formulating the nursing care plan. The purpose of physical assessment is a health status appraisal, which includes identifying health problems, and establishing a database for nursing intervention.
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Blogs as data: using XQuery for content evaluation.

Eli Wachter1, Elizabeth A Mullen2

  • 1wachter7@msu.edu, Data Visualization Librarian, Michigan State University Libraries, Michigan State University, 366 West Circle Drive (DB 24), East Lansing, MI.

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|April 15, 2026
PubMed
Summary
This summary is machine-generated.

This study used XQuery and AI to analyze institutions featured on the National Library of Medicine (NLM) blog, "Circulating Now." Visualizations revealed over 400 global institutions, aiding engagement assessment and future collaboration planning.

Keywords:
Data AnalysisData VisualizationHistory of MedicineNational Library of Medicine

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Area of Science:

  • Bibliometrics
  • Digital Humanities
  • Information Science

Background:

  • The National Library of Medicine's (NLM) 'Circulating Now' blog features community contributions.
  • Evaluating the institutional representation within the blog is crucial for understanding its reach and potential collaborations.

Purpose of the Study:

  • To develop a dataset of institutions represented on the 'Circulating Now' blog.
  • To explore the utility of XQuery in creating such a dataset.
  • To visualize the global reach of the blog's represented institutions.

Main Methods:

  • Utilized XQuery, developed with ChatGPT, to query XML data for institutional information.
  • Processed queries using BaseX and transferred data to Excel for manual enrichment with geographic and institutional type details.
  • Created data visualizations in Tableau to represent over 400 unique global institutions.

Main Results:

  • Successfully generated a dataset detailing over 400 unique institutions worldwide featured on the blog.
  • Visualizations provided a clear overview of the blog's current engagement reach.
  • Identified areas for potential future collaboration based on institutional representation.

Conclusions:

  • XQuery is an effective tool for developing datasets on institutional representation from blog content.
  • The analysis provides valuable insights for the 'Circulating Now' Editorial Board regarding engagement and collaboration opportunities.
  • Data visualization enhances the understanding of bibliometric data for strategic planning.