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GSIM is being adopted to specify, design, and implement components that = will easily integrate into =E2=80=9Cplug=E2=80=99n=E2=80=99play=E2=80=9D so= lution architectures and seamlessly link to standard exchange formats (e.g.= DDI, SDMX). It is important to note that GSIM does not make assumptions ab= out the standards or technologies used to implement the model, which leaves= the Agency room to determine its own implementation strategy.=20
Statistics Canada is beginning to use GSIM=E2=80=99s Concepts a= nd Structures Groups as the main classifiers of metadata. These gr= oups contain the conceptual and structural metadata objects, respect= ively, that are used as inputs and outputs in a statistical business proces= s. The Structures group defines the terms used in relation to data= and their structure. The Concepts group defines the meaning of da= ta, providing an understanding of what the data are measuring.=20
Work focuses on aligning the new GSIM-based classification with other in= ternal metadata classification models currently in use. For instance, IBSP = identifies the following types of metadata:=20
- Reference met= adata: Describes statistical datasets and processes.=20
- Definitional = metadata: Description of statistical data (with meaning to business use= r community) E.g., concepts, definitions, variables, classifications, value= meanings and domains.=20
- Quality metad= ata: Quality evaluation of a dataset or individual records; helps users= assess the fitness of associated data for their specific purposes. E.g., C= V, rolling estimates, analysts comments about the quality of a set of recor= ds.=20
- Operational m= etadata: links between the concepts and the physical data.=20
- Systems m= etadata: Low-level information about files, servers and infrastructure = that allows the physical IT environment to be updated without re-specificat= ion by the end user.=20
 For example: analyst comments about their analy= sis, output of statistical processes; respondent comments, interviewer comm= ents or additional information about the respondent obtained during collect= ion.
Metadata use is not uniform across = all GSBPM phases. IMDB metadata, consisting mostly of GSIM = Concepts and Business objects, is used for survey design (pha= se 2) and dissemination (phase 7). Survey managers use the IMDB to id= entify existing variables for reuse. New variables and related questions wi= ll be soon documented and stored during questionnaire design as well, which= will then be used by collection processes across the Agency. In the = dissemination phase, the IMDB is the primary source of summary texts descri= bing surveys, definitions of variables, related methodology, and data quali= ty and questionnaire images. Most products on the Statistics Canada w= ebsite offer a link to the related IMDB survey records.
The Sy= stem of National Accounts (SNA) creates and uses metadata (classifications)= for the data integration sub-process (5.1) of the GSBPM. In particular, th= e SNA creates the Input-Output Industry Codes (IOIC), Commodity Codes (IOCC= ) and Institutional Sectors classifications. They are mainly used for the G= DP surveys (annual, quarterly and monthly). SNA classifications are being e= xported to the IMDB and integrated into data warehouses for analysis via a = classification web service). In addition, concordances to NAICS, NA= PCS and other international classifications will be maintained in a Classif= ication Management and Coding System (CMCS).
The Social Survey= Processing Environment (SSPE) has its own metadata repository (see Section= IV-B) which is used from design through dissemination, including survey an= d questionnaire metadata, codesets and codebooks. The SSPE repository does = not use the same metadata objects that are in the GSIM Business or= Structures groups.
Underlying the GSBPM is the implicit ne= ed for common semantics which require some degree of harmonization and main= tenance across all phases. Even common concepts like questionnaire= , survey, or classification mean different things across = the Agency. Enterprise Architecture Services (EAS), Methodology= and Subject Matter areas have worked collaboratively to make progress in s= emantics work for the IBSP on a number of topics, including:=20
Statistics Canada=E2=80=99s involvement in the development of the = GSIM has influenced both GSIM and the Agency=E2=80=99s internal semantic wo= rk. A case in point is the work done by EAS with IBSP and the Integrated Co= llection and Operation System (ICOS) on survey instrument and questionnaire= s, which helped identify the need for a flow decision object separated from= flow action that was included in version 1.0 (submitted to the GSIM group = for review). This semantic work has been the starting point for developing = a canonical model for survey instrument and questionnaire for the SOA= a> .
IBSP has also developed a conceptual framework and naming conve= ntion for harmonized content. SSPE has developed standardized questionnaire= modules for cross-cutting household survey variables. These modules contai= n standard concepts, definitions, classification and wording for multiple c= ollection modes.=20
 See Section IV-F-(a) for more information on this service.= p>
 It indicates the provenance of the value for data quality pu= rposes.
 See Section IV-F for more information on SOA canonical model= s.
Several projects h= ave been identified as potential content providers or consumers of the IMDB= . The IMDB now stores documentation for public use microdata files as= part of the requirements for the Data Liberation Initiative (DLI) - an ini= tiative between Statistics Canada and Canadian universities to share data f= or social science research. Statistics Canada makes available to universiti= es and colleges, by subscription, all of its statistical products including= microdata files using Data Documentation Initiative (DDI) specifications. =
Another initiative under development is the Research Data Cen= tre (RDC) Metadata Project. Rather than integrating with the IMDB on = a case-by-case basis (point-to-point integration), authorized applications = can gain access to content through IT industry standard web services in a s= tandard based format (DDI). This approach is expected to reduce devel= opment costs, allow for code and component reuse across projects and foster= the adoption of global standards across the Agency. It will also sup= port the future establishment of standard-based data and a metadata managem= ent framework.