In 2012, Open Knowledge International created the Global Open Data Index to provide a clear measure of available open data. This original Index was designed by international experts on open data. In early 2014, Open Knowledge announced that it would make this platform publicly available for others to use for their own evaluations of open data.
The U.S. City Open Data Census began as a partnership between the Sunlight Foundation, Code for America, and Open Knowledge International and was launched on February 22, 2014 as part of national Open Data Day and in conjunction with Code for America's CodeAcross 2014. A push for initial contributions took place on May 31, 2014 as part of the National Day of Civic Hacking.
Today the Census is maintained by Sunlight Foundation staff members, with technical support from Open Knowledge, local outreach by community members (including many Code for America brigades), and participation from interested contributors across the country.
The Census is not a comprehensive list of open datasets around the United States, nor does it aim to define what datasets are the most important to open. Instead, the Open Data Census is a benchmarking tool, which people can use to see how their city compares to others around the country, and as a starting point with their own local governments about open government data.
No. For Census purposes, "publicly available" means the dataset is available online for anyone to see at any time.
Licensing of online datasets can be found in the datasets' metadata or, if the dataset is available via an online open data portal or database, within that portal or database's Terms of Service. Licensing might also be articulated in your city's open data policy.
In order to count as having an open license, it must meet the Open Definition: "Open data and content can be freely used, modified, and shared by anyone for any purpose." If there's no such explicit statement, then it does not count as having an open license.
For maximal legal re-use, open government data should have a worldwide public-domain designation, such as such as the Creative Commons CC0 statement or an Open Data Commons Public Domain Dedication and License (PDDL). See here for a longer list of open licenses.
Since machine readability is not strictly a matter of data format, here are some further points to consider: HTML, even when well structured, will only sometimes count as machine-readable and is, by default, not machine-readable because it most often needs parsing and therefore is not directly reusable.
CSV, XML and XLS would usually count as machine readable, but not always.
In general we suggest to look at machine-readable as a combination of fact and objective judgement, and not say that a particular format is automatically machine-readable or not machine-readable. So, machine-readable is to be understood in the sense that you could extract the data and directly reuse it. Sunlight's Open Data Guidelines and the Open Data Index discussion boards are two additional places to look. If you are still not sure, email us.
Join Open Knowledge International's Open Data Census discussion boards to talk about updates to these and other Open Data Census websites around the world.