Skip to content

Overview

The Social Data Commons supports equity-informed decision-making at the local and regional level. It began as the Social Impact Data Commons, a project of the Social and Decision Analytics Division of the Biocomplexity Institute at the University of Virginia, and grew out of two sponsored projects that share one community process, one pipeline codebase, and one dashboard design.

Social Impact Data Commons to Inform Equitable Growth

Mastercard Center for Inclusive Growth · National Capital Region

Grounded in the questions of stakeholders in Arlington and Fairfax Counties: broadband equity, access to care, business diversity, and food security.

Objective

Most public data stop at the county. Local questions about broadband affordability, access to care, or food insecurity play out at the neighborhood level, so most of the work of the commons is producing sub-county measures and placing them in the geographies local stakeholders actually use. To make impactful, equity-informed decisions, decision-makers need data and indicators that:

  • Triangulate on their policy challenges and questions.
  • Sit at a geographic level that informs their decision-making.
  • Come in a geographic shape that is useful: a planning corridor, a school attendance zone, a civic association, a health district.
  • Are validated and timely.

What a finished dataset must be

Once datasets are discovered, vetted, created, synthesized, and validated, they must be easy to assess, access, and analyze. Everything is meant to be both machine readable and human readable.

Assessable

Are these the right data for the policy question?

Maps, tables, charts, and full metadata for every measure on the dashboards, so a dataset can be judged before it is downloaded.

Accessible

Can the data be downloaded?

Direct download from the dashboards, and compressed CSV files with metadata committed to the public GitHub repository.

Analyzable

Can the data go straight into a user's own analysis?

One long-format schema, standardized file names, and 2020 census geographies across every dataset.

What the commons provides

Two open-source dashboards

Lightweight static web applications that run on free hosting such as GitHub Pages. One for Virginia, one for the National Capital Region.

Dashboards

Open data and pipelines

Broadband, business climate, demographics, education, environment, financial well-being, food, health, housing, public safety, and transportation. The code that ingests each source lives beside its output.

Data inventory

Open-source tools

Published on PyPI: spatial access and availability metrics, redistribution of population data into alternate geographies, and 2010-to-2020 census boundary standardization.

Python packages

Data stories

Worked examples that apply the commons to real local issues, each triangulating several measures to answer one question.

Data stories

Looking ahead

The commons is designed to be modular, sustainable, and expandable. Ongoing work extends it into new policy areas and new geographies, creates new policy-relevant indicators, and keeps existing datasets current as new source data are released.

Contact

Aaron Schroeder, Principal Investigator, ads7fg@virginia.edu