About 30,000 US state and local governments produce audited financial statements each year. Because these financial reports typically appear in PDF format, they are difficult to analyze and compare. By tranisitioning from PDFs to machine readable disclosures, we can ultimately create a publicly accessible database of audited state and local government financial statistics.

The proposed taxonomy in this repository is a first step in this transition. We offer it to the community of statement filers and consumers for review, comment and improvement.

Aside from the taxonomy itself, we have a sample Inline XBRL instance document based on the city of St. Petersburg, Florida's 2017 Comprehensive Annual Financial Report. Please note that this sample is NOT an official financial document of the City of St. Petersburg and should not be used for any financial analysis purpose.

The repository includes an Excel workbook with VBA code that can generate compliant XBRL instance documents. To unlock sheets in this workbook, please use password Micro#16Vista; to see and modify the VBA code use password daolpu@16#. There is also a docx file containing tagged footnotes that can be emedded in the instance document.

The taxonomy is based on a peer reviewed article published by Professors Neal Snow and Jacqueline Reck in the Journal of Information Systems in 2016. A draft of this article is freely available on the Social Science Research Network at https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2474922. The published article is available to journal subscibers or for purchase at http://aaajournals.org/doi/10.2308/isys-51373.

A copy of the taxonomy is also online at http://www.govwiki.info/xbrl/2018-04-30/us-cafr-2018-04-30.xsd thereby allowing for validation of instance douments on Arelle or other XBRL platforms.

You can see previous advocacy of municipal CAFR XBRL from 2013 here and 2015 here.

Update June 24, 2018: An alternate taxonomy developed by IRIS Business addressing the same scope has been added to the repository. IRIS Business reviewed multiple Florida CAFRs and used Data Point Modeling to build this taxonomy.

For more information about this project, or to volunteer, please contact Marc Joffe at [email protected].