Until recently, XML has been the single format for NIEM data. NIEM is now in the process of adopting JSON (Javascript Object Notation) as a second standard format for representing data based on the NIEM data model.

These pages are designed to provide an easy introduction to the purpose of NIEM, the reasons to use NIEM with JSON data, and the developer knowledge needed to put NIEM JSON into practice. They are intended for:

  • Developers who know JSON but know nothing of NIEM or XML
  • Developers familiar with NIEM XML who need a JSON version of a data exchange
  • Data scientists wanting to understand or provide JSON data sources
  • Managers wondering if NIEM JSON is right for their project

This is the starting page for learning about NIEM and JSON. Readers will probably follow links to the content of interest and bypass the rest. Some starting choices are:

  • A NIEM-JSON Tutorial: This tutorial walks the reader through a small example of implementing an information exchange using NIEM-JSON. It begins with a small set of data requirements, constructs a NIEM information exchange model, expresses data for that model as JSON, then constructs a JSON schema for that data.
  • Frequently Asked Questions: Explains what NIEM and JSON each are and do and why they are useful together.
  • A NIEM-JSON Reference Guide: Provides normative and non-normative guidance on how NIEM and JSON are used, including lots of examples.

NIEM JSON is a work in progress. These pages are intended to help developers, data scientists, and managers understand the different ways they might use NIEM and JSON together. Technical specifications now on the drawing board will define NIEM JSON conformance targets to accompany the existing NIEM XML conformance targets. Open source tools in the planning stage will help developers switch between JSON and XML (and perhaps other serializations) by creating translators for runtime data and conversions for build-time artifacts.

The intent is to make the NIEM approach valuable to anyone wanting to create or apply community agreement on data semantics, using these to provide precise definitions of data available through any sort of API, or to document and harmonize published data resources for data analytics.