Tuesday, 3 November 2015

Graph digitizer comparison – 16 ways to digitize your data (updated) | Connected Researchers

 Source: http://connectedresearchers.com/graph-digitizer-comparison-16-ways-to-digitize-your-data/


Graph digitizer comparison – 16 ways to digitize your data (updated)




progress-01Although
pdf files are the current standard for the dissemination of scientific
knowledge, the format comes with several, well known, drawbacks. An
important limitation is the difficulty to re-use the data embedded
in graphs and plots. Even with the advent of “enhanced” html versions of
articles, data is still most often represented with images, which makes
it difficult to extract the raw numbers. A few initiatives from
publishers now ask researchers to submit their data along with their
manuscript. But for the millions of paper already published, a number of
different software solutions can help you digitize the data from plots
and graphs.


Digitize your graphs and plots


All the tools presented below follow a similar process to convert
bars graphs, scatter plots, and line plots into a series of numbers.


 1. Open a graph


1270668950Depending
on the software, the graph can be imported directly from a .pdf file,
or will first have te be converted to an image format (jpg, bmp, png,
gif…). The image can be obtained through the html version of the paper,
or by taking a screenshot of the pdf file (on Mac use command-Shift-4;
on Windows use the print screen button or by use the Snipping Tool; on Linux use the Take Screenshot application). When saving your screenshot, be aware of what file format your software accepts.


 2. Set the scale


TWebPlotDigitizerhe
software will ask you to define the axis and set the scale. This is how
it will define the coordinates of each point. The more precise you are
while doing this, the better your results will be. Most software allow
for distorted axis (not perfectly perpendicular). And remember to
indicate wether the graph is in log scale. (the image to the left taken
from WebPlotDigitizer).


 3. Digitize the data points


WebPlotDigitizerYou
then need to digitize the points or lines. Depending on the software,
this step is going to be more or less automated. Most often, you are
asked to, at least approximatively, indicate where the points or lines
are located. Some fully manual will ask you to draw over the points or
line in order to digitize the data.


 4. Export the data


export-3Finally,
copy and export your data into the format that is most convenient to
you. Some software include additional acquisition data analysis
functionalities. But most often this is done by simply pasting a table
of coordinates in your favorite data processing software.





Comparative study of graph digitizer softwares


We have put together a comparison table of 16 graph digitizer
software. There might be others out there worth mentioning. Please do
not hesitate to comment and we will add them to the list.



So what solution is best for you? Well, as often, it depends. For most cases, using the browser-based WebPlotDigitzer
will be the most convenient. It handles many types of graphs and plots,
while being free. It does not require any installation, and
is compatible with all platforms. You might want to consider however
that because WebPlotDigitizer is a web-based tool, the current software
version number is unknown, which makes it hard to reference the analysis
you will have done with precision and can get in the way
of reproducibility.
For the more demanding situations, Un-Scan it might help, since comes with the longest list of functionalities. It is also the most expensive solution listed here.
Also, if you are a R user, you will find tutorials online on how R can help you extract data from graphs, and a paper describing a dedicated R package developed by Timothée Poisot.
Please comment and share your experience with these tools! Many thanks to David LeBauer for his insights and comments.
Update (30th of July 2015). I have added to the list im2graph


Graph digitizer comparison – 16 ways to digitize your data (updated) | Connected Researchers

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