By now, it’s probably no secret that I love crunching bibliometric data. I find that analysing my results — both during search strategy formation and after downloading final results — gives me a broader perspective and see trends that I might otherwise miss.
However, analysing data can sometimes be time consuming and clunky. Data never seems to be in the format that you want it when you need it; the precise tool that you need at that moment hasn’t been invented yet or is otherwise proprietary; the right software for the job requires a programming language you haven’t yet learned, and so forth. Sometimes you want a quick and dirty answer to help develop a strategy and it doesn’t have to be tidy or perfect, but you need it now!
Here’s my quick and dirty trick for analysing your bibliometric [medline] data:
- Generate a list of PMIDs from your results (whether your strategy is finalised or not!)
- Pop into the data analysis program of your choosing…
The beauty of this trick is that you can copy-paste whatever you are working on at this very moment (provided you’re working with medline data, of course…) and get real-time feedback. No need to mess with clunky software interfaces or retype your strategy.
Generate a list of PMIDs
If you’re using PubMed, this part is easy. Click the “Format: Summary” drop down menu just below the search bar, then select “PMID”. Et voila! The resulting page is a plain text list of PMIDs, taken from the results on the previous page.
Note that the resulting PMID list will show only the citations from the previous page, so you may want to scroll to the bottom of the screen to show the max number of citations per page (200 at the time of this writing).
If you’re working in Ovid (like I generally do), this is a bit trickier. Ovid citations still contain a PMID in the “unique identifier” field, but it’s not quite so easy to extract. There’s a few ways to go about this, but my usual strategy is to:
- Download all search results into EndNote reference management software
- Extract a list of PMIDs through a custom export filter
The downside to this method is that there is a limit to the amount of citations you can export at once from Ovid, and EndNote also gets a wee bit finicky when you start importing citations by the thousands… Thus, this technique is best done with small-ish citation sets.
Analyse your data
Once you have your list of PMIDs, you can pop them into a variety of different tools to crunch the data in different ways. For example, try pasting your list into:
- PubReminer – for a word count analysis of authors, journals, MeSH, title/abstract words…
- Medline Trends – for an analysis of citations over time
- GoPubMed – for a variety of filters (maps! bar graphs! frequency charts!)
- Yale MeSH Analyser – for a side-by-side comparison of MeSH usage
And more! Someday I intend to write up a full list of medline data analysis tools freely available online, but that day is not today…
Why would a person bother to do this?
Building a search strategy is an iterative process and it requires using a lot of different tools. For example, you can use your own common sense and intuition, but other tried-and-true strategies include: backwards/forwards citation chaining, talking to experts in the field, or looking at highly cited papers/journals in the field.
Using quick data analysis strategies throughout the process of building a search strategy will help ensure that important concepts aren’t missed. They provide a more objective picture of what’s happening, what’s missing, and how you can better refine your strategy.
That’s it for this week!
PS This is my first proper blog and I must say… keeping a blog up to date is not as easy as I thought. Please do let me know if you find this content useful and I will try my utmost to keep ’em coming! You can use the site contact form or find me on twitter at @v_woolf.