This project was developed and submitted by Seth Schimmel in Spring 2021 towards the capstone requirement for completion of the Masters of Science in Data Analysis and Visualization at the CUNY Graduate Center. The project was motivated by my professional experience with data mining and analytics development within a private philanthropic foundation, and inspired by computational research methods being applied in social science fields like economic geography, science studies, and bibliometrics.
The Public Innovations Explorer is a tool for investigating awards made by Federal agencies and departments participating in the Small Business Innovation Research (SBIR) and Small Business Technology Transfer (STTR) grant-making programs between 2008 and 2018. Awards were geocoded at the congressional district level (116th Congress, 2018), allowing users to identify companies performing publicly-funded innovative research in each district and obtain dynamic district-level summaries of funding activity by agency and year. Additionally, spatial clustering was applied on districts' employment levels across major economic sectors to give users a way of examining the underlying economic activities of districts alongside Federally-funded innovation research activities taking place in a district. Finally, mathematical and dictionary-based text mining techniques were both used to derive district-level keyword details and provide users with access to some basic keyword stats for each district.
Go to The Public Innovations Explorer
Read more about the design and methodology via the official white paper or via the documentation here
React
Typescript
Django
Laravel
Facebook
Microsoft
Google
Alibaba
D3
Tencent