Data science & substantive knowledge


Data science includes 6 types of analyses, each defining the relationships between data elements. They include descriptive, exploratory, inferential, predictive, causal, and mechanistic types. When trying to make sense of the interconnectivity between systems in a city, breaking the relationships into these types can help clarify how the system itself functions and where dependencies are located.

"Data" can be more flexible than many realize, and sometimes, substantive data can be a great help. Substantive data has many definitions but can be understood as the skills and expertise of individuals who know a subject area well. For instance, a transportation expert may know about trends they have seen over the years without having verifiable data to prove their knowledge. When there are gaps in understanding how systems work, substantive data can help fill in the voids. This can be a tricky approach, of course, from a data validity standpoint due to being highly subjective.

Part of Solution

  • Understanding interconnectivity

  • Photos

    • Data science vd