We’re excited to, for the first time, put PANDA into users’ hands! After roughly six months of development, we are releasing our first beta version. This release implements nearly all of our “must have” features.
We’ve written several times (1, 2, 3) about specific parts of PANDA in development, but until now haven’t paid much attention to the user interface of the application itself. With this release we feel we’ve reached a level of usability that will demonstrate exactly why you need a PANDA in your newsroom.
Store your datasets … and find them again
One common problem with handling data is figuring out how to archive it for safekeeping without making it difficult to access when you need it. PANDA meets this challenge by offering a central location to archive datasets and also indexing them so they can be retrieved by searching.
On the main PANDA search page you’ll find a list of recently uploaded datasets. I’ve uploaded several datasets from the City of Chicago’s data portal, as well as our contributor’s list and a spreadsheet of every Major League Baseball player.
You can browse datasets by category …
… or search for them. Dataset names, descriptions, categories, user names and column names are all searchable:
Advanced search queries work, too:
On the details page for any dataset you can edit metadata, add related files — such as a PDF of a FOIA (Freedom of Information Act) response — or even extend a dataset by adding another data file with new rows.
Cumulatively, these features allow you to securely store your data in a way that aids, rather than impedes, your ability to find it again. We hope you will never again wonder where an important dataset went. You and your fellow reporters can find datasets simply and naturally, the same way you would find information online. And once you’ve found it, you can easily download the original file or export it to a CSV.
Who did what? When? How? They did it where?
Searching datasets will help keep you organized, but what about exploring your data? PANDA indexes every row of each data file you upload, so your data is always accessible. You can search within a particular dataset, or across all your data.
Here is an example of searching within the “City of Chicago Employees” dataset:
The same search query, executed across all datasets, also finds baseball players with that name:
HOW TO GET A PANDA
Hopefully this tour has you excited to try out PANDA. Go read the docs to learn how to set one up! You can also ask questions on our new PANDA Project Users mailing list. This is a beta release, so some things may not go as we expect, but we’ve done our best to ensure it’s a useful product.