Data Science is rapidly growing into an interesting and diverse field encompassing a mixture of deep specialization and broad applications. As we work to define this field it is important that we always have access to the growing landscape of data science concepts, and understand how they branch from high level approaches to specific implementations. In an effort to mix a birds-eye view of this growing landscape with the ability to drill down and learn the concepts, I decided to capture data science approaches and tools visually in an expandable ontology visualization.
Although by no means exhaustive of every idea, the hope is that there is sufficient depth and detail to help guide and teach newcomers as they try to understand the tools and approaches of data science. Since Wikipedia represents a curated collection of knowledge from a variety of experts it made sense to connect wikis to the low-level concepts to assist those interested in learning more. I would encourage those interested in data science to use the ontology as a starting point, and dig deeper on your own as you learn how each of the concepts fit into the bigger picture. Every concept is a result of decades of work in a particular area, each made to study phenomena from a different angle and to address challenges in a variety of domains.
I am continuing to add to the ontology to help pass my 'birds-eye view' onto others looking to get a handle on this new and exciting field. Enjoy.
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