All data tells a story—a story to be investigated. The beautiful thing about data is its ability to avoid all subtext and ambiguity and go straight to the facts. Swimming through large amounts of it however, can easily become overwhelming and unproductive. In order to be able to critically instigate the data and its story, one must be able to model and query it.
Last year we created a property graph model for a data set released to the public through the CHHS Open Data Portal. What struck us about this data was its enormous potential to be controversial. The data contained all cosmetic products sold in California “known or suspected to cause cancer, birth defects, or other developmental or reproductive harm” (CHHS). Many Californians assume that any makeup product they see on the shelves has passed every safety and health code before it reaches the public. This dataset said otherwise. Using the property graph model, we were able to bring meaning to the numbers.
The Chemicals in Cosmetics data set was richly interconnected
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