Understanding the shape of innovation is difficult. But one way of looking at this is by examining inventions. Patented inventions have clear pieces of information associated with them, from their subject matter and the work that each one builds on, to the team involved in the idea. Each of these pieces of data can be combined to give a sense of how innovation—at least for inventions—occurs. Through patents, you can begin to do some fascinating exploration of Invention Big Data.
A team of researchers (I’m friends with them) created a company called PatentVector to do exactly this. PatentVector has a huge dataset of inventions going back several decades, and allows users to easily explore the patterns of innovation, from which fields different companies innovate in, to which patents are most influential. You can even easily see related patents, based on automatic categorization of inventions.
For example, here’s the patent related to multitouch from Apple:
The top left number is the patent number and the bar beside it shows its PatentVector score, with the amount of the bar that is shaded representing its percentile ranking. As can be seen, this patent is highly influential.
On the other hand, this can be easily compared to a far less influential invention: an umbrella for your beer.
From here, you can explore related patents, and information related to the company of the patent, the inventors, and even the examiner at the USPTO. You can also see how companies operate. Here’s IBM:
IBM has patents in many different subjects, such as configurable circuits, though none of these patents (represented by the vertical black bars) are the most influential ones in this domain (the more to the right they are, the more influential they are).
You can see more of the functionality of PatentVector here. While the world of patents is still very complicated and it’s not always clear how to understand innovation in the world of patents, PatentVector is a fascinating new tool for Invention Big Data and a step in the right direction.
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