Meaning-making takes resources

In order for data to be broadly useful, it must be analyzed, transformed, visualized, or otherwise processed. Community groups with limited time or statistical capacity can often get stuck with useful data but an inability to interpret it for their purposes. Large, government datasets are often overwhelming, poorly curated, or difficult to access or use for localized environmental action. Figuring out how to make data useful and relevant for specific initiatives requires tailored support because thresholds for action can be highly contextual. This takes time and resources.

Solutions

1.

Desarrollar objetivos conjuntamente

Evaluar las necesidades de interpretación de datos de las comunidades y elaborar planes de análisis conjuntamente.

2.

Match analysis with capacity

Provide or connect communities with analysts (e.g., academic partners, data fellows, public interest technologists) who can help translate raw data into actionable formats.

3.

Build shared workflows

Develop repeatable, understandable workflows for analyzing and communicating data that community members can eventually lead or sustain.

4.

Use layered storytelling

Combine data with qualitative information (like lived experience or oral histories) to create outputs that are locally meaningful.

5.

Actionalize your data

Work with your local university's environmental law clinic to better understand your data's role in regulation and enforcement.

Know of another resource or solution?

Resources

The 2016 National Advisory Council for Environmental Policy and Technology (NACEPT) report

The 2016 National Advisory Council for Environmental Policy and Technology (NACEPT) report includes a framework showing the spectrum of data uses in participatory science.

The 2016 National Advisory Council for Environmental Policy and Technology (NACEPT) report
Related solutions
Desarrollar objetivos conjuntamente
Match analysis with capacity
Build shared workflows
Use layered storytelling

Action's Participatory Science Toolkit Against Pollution

Action's Participatory Science Toolkit Against Pollution addresses the practical problems that participatory scientists face throughout the different stages of each project. It draws on expertise in participatory science, participatory design, social innovation, socio-economic studies, pollution, open science, social computing, open data and software development to ensure it suits the requirements of participatory science projects.

Action's Participatory Science Toolkit Against Pollution
Related solutions
Desarrollar objetivos conjuntamente
Match analysis with capacity
Build shared workflows
Use layered storytelling

DataKind

DataKind reúne a científicos de datos pro bono y expertos del sector social para utilizar la ciencia de datos y la inteligencia artificial con fines sociales.

DataKind
Related solution
Adecuar el análisis a la capacidad

Code for America

Code for America partners with governments and communities to build digital tools and services that make public systems more effective and equitable.

Code for America
Related solution
Match analysis with capacity