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AMEND: Open Source and Data-Driven Oversight of Water Quality in New England

Author

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  • Nathan Edward Sanders

    (Mystic River Watershed Association, USA)

Abstract

The advent of government transparency through online data publication should provide a transformative benefit to the information gathering practices of civic organizations and environmental advocates. However, environmental agencies and other reporters often disseminate this critical data only in siloed repositories and in technically complex, inconsistent formats, limiting its impact. We have developed a new open source web resource, the Archive of Massachusetts ENvironmental Data or AMEND, which curates information relating to federal, state, and local environmental stewardship in Massachusetts, focused on water quality. We describe the construction of AMEND, its operation, and the datasets we have integrated to date. This tool supports the development and advocacy of policy positions with published analyses that are fully reproducible, versioned, and archived online. As a case study, we present the first publicly reported analysis of the distributional impact of combined sewer overflows on Environmental Justice (EJ) communities. Our analysis of the historical geospatial distribution of these sewer overflows and block-level US Census data on EJ indicators tracking race, income, and linguistic isolation demonstrates that vulnerable communities in Massachusetts are significantly overburdened by this form of pollution. We discuss applications of this analysis to the state-level legislative process in Massachusetts. We believe that this approach to increasing the accessibility of regulatory data, and the code underlying AMEND, can serve as a model for other civic organizations seeking to leverage data to build trust with and advocate to policymakers and the public.

Suggested Citation

  • Nathan Edward Sanders, 2019. "AMEND: Open Source and Data-Driven Oversight of Water Quality in New England," Media and Communication, Cogitatio Press, vol. 7(3), pages 91-103.
  • Handle: RePEc:cog:meanco:v7:y:2019:i:3:p:91-103
    DOI: 10.17645/mac.v7i3.2136
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