home / csvconf

talks

Data source: https://csvconf.com/

1 row where datetime = "2019-05-08T14:30:00", day = "May 8 2019", image = "https://csvconf.com/img/speakers-2019/zselvans.jpg" and url = "https://csvconf.com/speakers/#zane-selvans" sorted by rowid

View and edit SQL

url

image

day

datetime

Link rowid ▼ title speaker time day room url datetime abstract image
22 US Energy Data Liberation Zane Selvans 2:30 PM May 8 2019 Daisy Bingham Room https://csvconf.com/speakers/#zane-selvans 2019-05-08T14:30:00 An alphabet soup of government agencies like FERC, EPA, EIA, PHMSA, MSHA and the ISOs and RTOs collect and publish terabytes of data about the US energy system. It includes operating costs and fuel consumption, hourly power output and GHG emissions, and the age and length of natural gas pipelines, the price of electricity every 5 minutes at thousands of nodes in the grid, coal production numbers and much much more. In theory all this data is public and freely available, but in practice it takes a lot of wrangling to make it usable for analysis. The result: it's packaged up by one or two platform monopolies that charge tens of thousands of dollars a year for easy access, excluding most non-corporate users. But for anyone interested in the ongoing transformation of our energy system and its climate impacts, this data is a treasure trove worth excavating. The Public Utility Data Liberation project (https://github.com/catalyst-cooperative/pudl) has been working for the last 2.5 years to liberate this data and make it freely accessible to activists, data journalists, and researchers working on US climate and energy policy. This talk will take a look at what the data is, where it comes from, why it's interesting, how we're processing it and making it available, and some of the challenges we're facing and opportunities we see ahead. https://csvconf.com/img/speakers-2019/zselvans.jpg

Advanced export

JSON shape: default, array, newline-delimited

CSV options:

CREATE TABLE [talks] (
   [title] TEXT,
   [speaker] TEXT,
   [time] TEXT,
   [day] TEXT,
   [room] TEXT,
   [url] TEXT,
   [datetime] TEXT,
   [abstract] TEXT,
   [image] TEXT
)
Powered by Datasette · Query took 7.105ms · Data source: https://csvconf.com/