Back in the 1980s, I watched a movie called Wall Street, and one scene always stuck with me: a young stockbroker played by Charlie Sheen gives a very prescient stock tip to his future mentor, played by Michael Douglas. After the tip proves to be accurate, we see Douglas telling Sheen that he knows that the head of the union at the company is Sheen's father. The implication is that he has researchers who can find connections between people and companies, but at the time it got me thinking about what connected data could do.
Of course, in this context it sounds a little creepy, but this is exactly the sort of research that agencies like the Securities and Exchange Commission (SEC) have to do manually in order to detect fraud and insider trading. Setting privacy concerns and personal data like family connections aside for a moment, consider what would happen if public data from hundreds of sources could be combined and we could search for connections between things. What would we find?
Here are a few off-the-cuff ideas to inspire you. Chances are, you'll have no interest in implementing these exactly, but hopefully they'll lead you to your own connected-data ideas.
Using trademark data, we can determine which companies are responsible for different brands, which we might combine with nutritional data from the USDA to determine which companies make the most sugary beverages. We could also take the classification of the logos from the trademark data to ...