About this project:

OPEN NYU: Using Technology to Modernize NYU Governance through Expert Networks and Crowdsourcing

Over the course of the past year, GovLab has engaged with NYU UEI in an advisory relationship to explore, develop and help implement new types of tools for decision-making within our university community. Our collaboration, OPEN NYU, is developing ways for NYU to tap into the knowledge and talents that exist within its diverse community of students, faculty, staff, alumni and administrative leadership. In so doing, we aim to pioneer more open and collaborative practices at NYU that could be of value to other universities or colleges looking to modernize how they make decisions.

"Expert networking"

Expert networking refers to a set of strategies and tools designed to efficiently identify, organize, and make visible the knowledge, skills, and experiences of individuals within a group, so as to foster more and better collaboration among them. An “expert network” could just as easily be called a “knowledge map” or a “skills directory.” Put simply, expert networking is a strategy for figuring out which people, and with what sorts of backgrounds, to ask for specific sorts of information. ExpertNet is part of the GovLab’s ongoing Smarter Governance efforts, which are based on the belief that people who are not traditionally included in certain governance decisions have expertise, experience, and ideas that can offer new insights and solutions for public problems. ExpertNet is part of the GovLab’s ongoing Smarter Governance efforts, which are based on the belief that people who are not traditionally included in certain governance decisions have expertise, experience, and ideas that can offer new insights and solutions for public problems.

Framing questions:

  1. How do we know who is an expert in a particular field?
  2. How do we infer expertise if we have qualitative and quantitative data about people?
  3. How do we answer 1 and 2 in context of ‘data science’ at NYU?
  4. What is data science?

      5. All the code for this project is open-source. View it on GitHub here.

      Some other things...

      (1) THE PROBLEM

      translator

      (2) DATA PIPELINE

      Data pipeline

      (3) DATA SCIENCE "MINDMAP"

      Data pipeline