menu
Projectskeyboard_arrow_rightOrgPedia - Crowdsourcing and Impact Modeling

OrgPedia - Crowdsourcing and Impact Modeling

How can crowdsourcing and open data be used to gain better information about companies?

    Governance Area
  • National Governance
  • Institution Type
  • Corporate/Business
  • Innovative Capability
  • Open data Collective Intelligence Crowdsourcing Open innovation Design Thinking
  • Product Category
  • Platform

Background

Both corporate identities and activities remain too opaque and complex to get a full 3D view of any given company. To gain a greater understanding of corporations and their activities, the OrgPedia project aims to prototype the tools, processes and incentives for combining open government data, such as regulatory filings, with open private data, such as NGO reports, and crowdsourced data gathered from individuals about companies.

Location

Global

Partners

American International Group, Inc. (AIG)

Description

To build the foundation for the OrgPedia Project, the GovLab is developing the methodology, prototype, platform, and pilot a program to solicit, aggregate, and organize crowdsourced intelligence on a select number of corporations in the Extractives Industry – i.e., the oil, gas, and mining sectors. The project is to be designed with the goal of understanding whether it is possible to:

  • Build an open, public business intelligence system combining crowdsourcing and open data;
  • See the provenance and reliability (reputation) of data drawn from these different sources;
  • Understand what kinds of information crowdsourcing will yield, including information about what a company does, what it produces, who its owners, partners and collaborators are, and what channels and asset flows it uses.

Results & Impact

By making information about players in the Extractives industry more accessible, the project will seek to increase the transparency and accountability of those actors. Moreover, the initial pilot phase of the project will help to uncover an optimal methodology for combining crowdsourcing and open data to yield new insights into institutional behaviors.

Team

Beth Simone Noveck

Batu Sayici

Christopher Wong

Claudio Mendonca

Anna Bialas

Mark Adkins-Hastings