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Teaching a Computer to Read Science #4

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@Imperssonator

Me

Nils Persson


Abstract

People in all scientific disciplines spend an incredible amount of time reading and preparing published figures and graphs. Somewhere between 60-80% of all published scientific data is trapped in a .jpg file or a PDF somewhere on a publisher's server. We live in an era of learning from big data, yet arguably the biggest, most validated, most scrutinized data collected by humankind is hiding in images. Automated extraction of data from images of figures and graphs has received a smattering of attention over the past decades, but the time has never been more ripe for this technology to come to the fore. With a dataset of hundreds of figures from open-access journals, how much information can we extract armed with just a Jupyter Notebook and computer vision libraries? The answer: quite a lot.


Affiliation

Georgia Institute of Technology

About Me

Nils is a chemical engineering PhD student at the Georgia Institute of Technology whose thesis could best be compared to a wayward fishing vessel lost in the middle of the Pacific. It will eventually beach on a deserted island, which will be deemed novel regardless of others having discovered it before.

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