The standards referenced here are cross-cutting, supporting the modernisation of all types of statistical production, and are endorsed by the HLG-MOS. For domain-specific standards, please see the Global Inventory of Statistical Standards.
The GSBPM describes and defines the set of business processes needed to produce official statistics. It provides a standard framework and harmonised terminology to help statistical organisations to modernise their statistical production processes, as well as to share methods and components.
The GSIM is a reference framework of information objects, which enables generic descriptions of the definition, management and use of data and metadata throughout the statistical production process. It provides a set of standardized, consistently described information objects, which are the inputs and outputs in the design and production of statistics. As a reference framework, GSIM helps to explain significant relationships among the entities involved in statistical production, and can be used to guide the development and use of consistent implementation standards or specifications.
CSPA builds on existing standards such as the GSBPM and the GSIM to create an agreed set of common principles and standards designed to promote greater interoperability within and between statistical organizations. It provides the “industry architecture” for official statistics.
The GSDEMs provide a standard vocabulary with common definitions and models to facilitate the sharing of information and best practices in the field of statistical data editing. Version 1.0 was approved for release by the HLG-MOS on 26 November 2015.
DDI is an initiative to create an international standard for describing data from the social, behavioral, and economic sciences. The DDI metadata specification now supports the entire research data life cycle. DDI metadata accompanies and enables data conceptualization, collection, processing, distribution, discovery, analysis, repurposing, and archiving.