But nowadays the good practice is to publish graphs in vector form. Other answerers assume that you deal with raster image of a graph. TL DR: WebPlotDigitizer is available as a web application as well as a chrome plugin GRABIT OpenSource (BSD) plugin that runs in a proprietary platform, Matlab.g3data (open source - GNU GPL) Has zoom window, no auto-recognition.Browser based, extracts data from images. R digitize (free, open source), because it simplifies the processs of getting data from the graph into an analysis by keeping all of the steps in R.ImageJ (open source, most extensible after R digitize).DigitizeIt (shareware) auto point / line recognition.Get Data (shareware) has zoom window, auto point / line recognition.Available in Ubuntu repository (engauge-digitizer) Digitizer (free software, GPL) auto point / line recognition.If have not tested the accuracy of any of these programs, but it would be interesting to compare among users, among programs, and against the results of reproduced statistical analyses. error from digitization << size of error bars or uncertainty in the estimate). Except in contexts where measurement error is very small, error from graph scraping is insignificant (e.g. I have listed them below.Īll of the ones I have used work fine. There are many programs, and they vary in extra features, usability, licensing, and cost. Often it helps selecting points if the image is zoomed, either by uploading a zoomed version of the image or using the zooming feature available in some of the programs. The program returns each point as an x-y matrix.
This feature could be worth the trouble for digitizing lines, but I have never had to do this.
I have not found one that recognizes different symbols. I am usually after points, and I find them too inconsistent to be helpful even with 100s of points.
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