Metadata Technology North America Inc. (MTNA) has been awarded a contract by Statistics New Zealand for the delivery of its next generation classification management system.

Classifications, often referred to as code lists or value labels by statisticians, are a fundamental component of statistical data production, management, and analysis. Their standardisation and consistency are essential to ensure data comparability and harmonisation across datasets, time, topics, borders, or languages. 

Effectively maintaining and sharing such information at the international, national, institutional, or departmental levels presents significant challenges. As a result, this is often performed in isolation, leading to duplication of efforts and inconsistencies.

MTNA says its solution will take an innovative approach by providing a platform for collaboratively managing classifications, enable functionality such the capturing changes over time or cross-classification mappings, and provide standard web services and interfaces for interacting with external systems. 

The underlying information model will be concept driven and align on broadly accepted metadata specifications and best practices such a the Data Documentation Initiative (DDI), Statistical Data and Metadata Exchange standard (SDMX), Neuchatel Terminology, or the Simple Knowledge Organization System (SKOS). 

Web based user interfaces will be designed for managers, institutional, and public users, to maximize accessibility.

The project is due for completion in second quarter of 2014. As part of the agreement, the software will be licensed in perpetuity to Statistics New Zealand. Free licenses will also be extended to national statistical agencies in the 22 member countries of the Secretariat of the Pacific Community (SPC). It is further anticipated for the platform to become available for general licensing in 2014.

This classification management system is a core component of MTNA’s long term vision of delivering global cloud based environments for the management, publication, access, and analysis of statistical data. 

It says flexible and standard based classifications management tools, enabling sharing information across institutions and borders, would greatly facilitate single point of maintenance and foster reuse, leading to more consistent and comparable data, in turn supporting amongst others open government