Finding Data in Figures, Tables, and Graphs

Can you think of a time you were digging through articles, scouring “Results” sections for a piece of information?  Maybe you wanted to see how other people had measured and reported a particular type of data, or maybe you wanted to know the range of values that have been reported for a type of experiment.

If this is your goal, you’re probably only interested in an article IF it’s using a particular method or reporting results from experiments similar to yours.  Maybe you can even picture the type of figure or table where this information would appear.

Enter PubMed Central.  PubMed Central is a full-text database of NIH-funded research articles and open access journal articles.  You may have contributed several articles yourself!  Now is your chance to reap the benefits of this full-text database!

Search Example

Let’s say you want to find RT-PCR data from studies of hyperoxia in mice. 

  1. Go to PubMed Central and click on Advanced.
  2. Change the label “All Fields” to “Figure/Table Caption”.
  3. In the search box, type words you’d expect to find in the text accompanying a figure: hyperoxia AND RT-PCR AND mice
  4. As you type, PubMed Central will automatically format your search so that it’s restricted to the Figure/Table caption.

Articles in your search results will contain all three of your terms in the text accompanying its figures or tables – although not necessarily all in the same figure.

If you’re only interested in quantitative RT-PCR, you can search for that exact phrase in the Figure/Table caption field by using quotation marks: “quantitative RT-PCR”.

Please view this document for screen shots illustrating these steps in PubMed Central.

All I Need Are a Few Good Articles: Using Sorting and Relevance Ranking Features

Your goal is to scan some abstracts, read 2-3 articles, and then move on.  What do you do, then, if your keyword search turns up 10,000 search results?  If you just need a few good articles, one strategy is to take advantage of sorting and relevance ranking features – to try to move “good” articles closer to the top of the list.  A challenge is that each database defines “good” (relevance) differently, and none of them can read your mind (yet).

Here’s an overview of sorting and relevance ranking features in PubMed, Google Scholar, and Web of Science, followed by a search example showing how they compare.  (Click HERE for screen shots showing how to change sorting options.)

PubMed: The “Best Match” option sorts search results according to where your search terms appear and how frequently they appear in the reference.

Google Scholar: Automatically ranks search results according to a proprietary algorithm which considers how frequently an article has been cited, where your search terms appear, and other factors.

Web of Science: Offers multiple sorting options.  Can sort search results by relevance, times cited, or usage count.  Like PubMed, “relevance” is based on where the search terms appear and how frequently they appear.

Resource Content Searched Factors Considered in Relevance Ranking Sorting Options
PubMed Titles, abstracts, author keywords, & MeSH terms – of journal articles Location and frequency of search terms in the reference Publication Date (default); Best Match; First Author; Last Author; Journal; Title
Google Scholar Full text of journal articles, dissertations, books, & other scholarly publications. Numbers of times cited; location of search terms in reference; journal; “other”. No options.  Ranking & sorting are automatic.
Web of Science Titles, abstracts, & keywords of journal articles, conference abstracts, & book chapters. Location and frequency of search terms in the reference. Date (default); Relevance; Times Cited; Usage Count; First Author; Journal Title

Search Example: The relationship of obesity to the microbiome.

Search Terms: microbiome obesity

Resource Interpretation of Search Terms
Number of Results (June2018) Article from the Top 5 Results Ranked by Relevance (or Best Match)
PubMed (microbiome OR microbiota) AND obesity 2,926 “Looking for a signal in the noise: revisiting obesity and the microbiome” – MBio, 2016.
Google Scholar microbiome AND obesity “About 46,900” “An obesity-associated gut microbiome with increased capacity for energy harvest” – Nature, 2006.
Web of Science microbiome AND obesity 1,609 “Obesity: Gut microbiome and serum metabolome changes” – editorial – Nature Reviews Endocrinology, 2017.

Still Not Finding What You Need?

What you consider “good” might not be a highly cited article or an article with your search terms in the title!  Consider looking for recent review articles, articles by a known expert in the field, or contact your librarian for assistance!

Tips from your Scientific Research Librarian

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