Plenario


About Plenario: “Plenario makes it possible to rethink the way we use open data. Instead of being constrained by the data that is accessible and usable, let’s start by formulating our questions and then find the data to answer them. Plenario makes this easy by tying together all datasets on one map and one timeline—because in the real world, everything affects everything else…
The problem
Over the past few years, levels of government from the federal administration to individual municipalities like the City of Chicago have begun embracing open data, releasing datasets publicly for free. This movement has vastly increased the amount of data available, but existing platforms and technologies are designed mainly to view and access individual datasets one at a time. This restriction contradicts decades of research contending that no aspect of the urban landscape is truly isolated; in today’s cities, everything is connected to everything else.
Furthermore, researchers are often limited in the questions they can ask by the data available to answer them. It is not uncommon to spend 75% of one’s time locating, downloading, cleaning, and standardizing the relevant datasets—leaving precious little resources for the important work.
What we do
Plenario is designed to take us from “spreadsheets on the web”1 to truly smart open data. This rests on two fundamental breakthroughs:

1)  Allow users to assemble and download data from multiple, independent data sources, such as two different municipal data portals, or the federal government and a privately curated dataset.
2)  Unite all datasets along a single spatial and temporal index, making it possible to do complex aggregations with one query.

With these advances, Plenario allows users to study regions over specified time periods using all relevant data, regardless of original source, and represent the data as a single time series. By providing a single, centralized hub for open data, the Plenario platform enables urban scientists to ask the right questions with as few constraints as possible….
being implemented by the Urban Center for Computation and Data and DataMade