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A.  Summary of good practices  

18.2.        The present Guide recognizes that metadata (a) play a crucial role in the statistical production process, as they enable and facilitate sharing, querying, understanding and using data over the different stages of their collection, compilation and dissemination, and at their various levels of aggregation and (b) are indispensable for assessment of the quality of data, as their availability and wide dissemination constitute a basis for the correct interpretation of publicly available statistics and their effective use. 

18.3.        It is advised that compilers take into account that statistical metadata cover the following items:[1] statistical description, unit of reference, reference period, institutional mandate, confidentiality, release policy, frequency of dissemination, dissemination format, accessibility of documentation, quality management, relevance, data accuracy and reliability, timeliness, comparability, coherence, cost and response burden, data revision and statistical processing. 

18.4.        The use of standard terminology for metadata across the various statistical domains and use of the SDMX information model is also advised, as they will facilitate further integration of statistics, the standardized sharing of data and the international comparability of data. 

18.5.        It is further advised that compilers design their metadata systems in the most efficient way so that metadata items can be conveniently retrieved from the relevant databases, be used in the generation of the intermediate and final data sets or in the production of other metadata, and be updated and synchronized. In that context, compilers are encouraged to design and use a warehousing system for data and metadata to integrate the dissemination of data and metadata with the collection and processing components of the statistical production process. 

18.6.        With regard to compiling metadata, compilers are encouraged to follow standardized metadata concepts, make use of the metadata developed in related statistical domains and already being applied in their national statistical system, define layers of metadata, establish metadata registries, incorporate structural metadata items into the data processing as early as possible, establish clear links between data and metadata and compile reference metadata. 

18.7.        In the case of countries with less developed statistical systems, it is good practice to begin by setting up an exhaustive, consistent and detailed repository (possibly in the form of a metadata registry) with both structural and reference metadata, adopting, as much as possible, metadata concepts that are standardized across all statistical domains, both nationally and internationally. The present Guide strongly advises that the next immediate priority be to grant equal, easy, extensive and timely access to metadata to all user groups, including the general public. 

18.8.         The structural metadata items promoted by the present Guide are those defined within the framework of the Balance of Payments Data Structure Definition (BOP-DSD)  defined by the Manual on Statistics of International Trade in Services (MSITS 2010) and the present Guide for FATS and for additional indicators on the international supply of services. Metadata items should cover both monetary and non-monetary (quantitative) data items whose compilation is encouraged by the present Guide

18.9.        The metadata standards of international organizations should be carefully considered by compilers, both to improve their metadata collection and compilation and ensure better compliance with their international and regional data and metadata reporting obligations. 

18.10.    It is good practice for any deviations from international standards, as well as the use of estimations and modelling to compile certain data series, to be clearly documented in metadata.

 

Next: B. Metadata: basic concepts and definitions and the role of the Statistical Data and Metadata Exchange



[1] Guidelines on Integrated Economic Statistics, para. 5.91.