Distributing Power with Open Data

Some lessons learned from our work getting electricity system data into the hands of activists and researchers who are trying to shift power in US energy policy making. Under what circumstances can data help drive policy changes, and how does that change happen? Is open data always preferable in an advocacy context? What does it really mean for data to be accessible to advocates? US energy regulation is extremely technocratic, and largely happens out of public view. For years we’ve tried to address the information asymmetry that exists between advocates and large utilities by publishing cleaned open datasets detailing the inner workings of the US electricity system. We use Python data science tools to prepare the data and they serve us well, but most advocates -- even those with a lot of domain expertise -- are either hardcore spreadsheet users, or are just starting to dabble in Jupyter Notebooks. Now that we have a decent data pipeline, we are turning our attention to improving the data’s accessibility for our target users, using Datasette, Docker containers that run Jupyter, and Intake data catalogs.