The Public Comment Analysis Toolkit (PCAT) is Web-based, university-hosted and supported software engineered for the specific task of reviewing public comments submitted via the Federal Docket Management System or email to federal agencies. PCAT is version 2.0 of the Coding Analysis Toolkit (CAT), therefore it is also useful for sorting all kinds of CAT-style datasets, including open ended survey responses and comments left on blogs or YouTube videos.

If you have lots of digitized text, you can use the PCAT platform to form a team of peers, create a project, upload data, discover important themes and issues, and organize your analysis. This system is the end product of ten years of NSF-funded public comment classification work by Dr. Stuart W. Shulman, who has published numerous peer-reviewed papers on the subject.

• The system is fast, secure and scalable.
• This is currently a free service in beta testing based on award-winning research software.
• It extends carefully researched principles of efficiency, accuracy, validity, usability, and transparency.
• It leverages a novel new approach to integrating credentials and distributed work flow.
• It is equally useful to public and private actors and accessible to all.
• It allows you to show or share your work with anyone on the system, or keep it private.
• It deals a blow to the tyranny of carpel tunnel causing mouse-clicks.
• It is very easy to learn and you can't break it.

Coding is a human-centered technique for sorting through text. Coders (or analysts) discover, tag and write about text passages that are automatically presented in the coding viewer. PCAT and CAT use two basic techniques, automated loading of text passages and keystrokes to record coding choices, to significantly ease the physical burden, as well as the management tasks, associated with reviewing lots of text.

The “code & retrieve” model allows teams to sort comments into categories for analysis while reducing the total number of carpel tunnel-causing mouse movements and clicks. Analysts can review the results on screen or export the coded text as part of writing a regulatory response. The PCAT system keeps track of everything, including which comments have been read or coded, and it allows you find, retrieve and utilize what you are looking for. The inclusion of a new “search–>bucket–>dataset” work flow makes it possible to quickly divide the task of comment analysis across different themes. This streamlines the process of assigning unique or over-lapping sub-parts of the agency archive to different peers in the team.

During the coding process, you can introduce bookmarks and write associated memos about passages of text you want to return to. Often, these memos include snippets of highly relevant text that “triggered” the bookmark itself. Memos can be searched, reviewed, coded, and exported in .csv, .rtf, .xml and HTML formats. Coders can designate each memo as either private (between the owner of the dataset and the peer who is the author of the memo) or public (shared with every peer assigned to a dataset). In the “Validations” module, the PCAT system simplifies the task of developing coherent and consistent coding practices. QDAP personnel use the adjudication process to better train coders and thereby improve coding and code definition validity.

• Read the October 30, 2009 press release for the official PCAT launch
• To test PCAT, visit http://pcat.qdap.net, or click here to watch an online tutorial

Why would I use this system? | Where do I get FDMS bulk downloads? | Does PCAT identify duplicates? | What is QDAP?

© 2009-2010 - Qualitative Data Analysis Program (QDAP), in the University Center for Social and Urban Research, at the University of Pittsburgh, and

QDAP-UMass, in the College of Social and Behavioral Sciences, at the University of Massachusetts Amherst.