GSIM, DDI & Standards-based Modernisation of Official Statistics

Workshop – DDI Lifecycle: Looking Forward

October 2012

Overview

• Standards-based Modernisation of Official Statistics– GSBPM (Generic Statistical Business Process Model)– GSIM (Generic Statistical Information Model)

• Brief introduction to GSIM– Motivation– Purposes– Development process– Groups – Key messages & Next steps

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Standards-based Modernisation

A response to strategic challenges and opportunitiesfor producers of official statistics

• Data deluge• Competition• Changing needs and rising expectations from users• Governments expect efficiency (“do more with less”)

High-Level Group for Strategic Developments inBusiness Architecture in Statistics (HLG-BAS) HLG-BAS Vision (condensed version)

“Statistical organisations need to work together to re-invent our products and processes and adapt to a changed world”

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HLG-BAS Vision: Modernising statistical production

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Purposes of GSIM

• Improve communication between different disciplines involved in statistical production, within and between statistical organizations; and between users and producers of official statistics.

• Generate economies of scale by enabling greater collaboration within and between organizations, especially through reuse of information, methods or technology.

• Enable greater automation of the statistical production process, thus increasing efficiency and reducing costs.

• Provide a basis for flexibility and innovation, including support for the easy deployment of new statistical products and the adoption of new types of statistical data sources

• Build staff capability by using GSIM as a teaching aid that provides a simple, easy to understand view of complex information, with clear definitions

• Validate existing information systems and compare with best practice in other organizations.

The GSBPM

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Information objects

• Information (e.g. statistical data and metadata) – Flows between GSBPM sub-processes

• e.g. data is processed/transformed between Collect & Disseminate phases

– Governs the behaviour of GSBPM sub-processes• business rules and derivation formulas apply during Run

Collection, Derive New Variables etc• rules/criteria determine which sub-process should be performed

next (e.g. whether the quality of the output is sufficient to proceed to the next step or whether some form of “remedial” processing is required)

– Describes the quality of the outcome of GSBPM sub-processes• e.g. process related quality metrics (response rates, imputation

variance etc

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Need Consistent Information• HLG-BAS Implementation Strategy seeks

i. reuse and sharing of methods, components, processes and data repositories

ii. definition of a shared “plug-and-play” modular component architecture

• Statistical business functions as described in GSBPM will help determine which components are required.

• Achieving (i) & (ii) also requires a consistent approach to information flowing in and out of functions

• DDI can provide a standard way of representing and “carrying” (at least some of) the required information– as can SDMX and …

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Early thoughts

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What is GSIM?GSIM

is a reference frameworkof information objectswhich enables generic descriptions of the definition, management, and use of data and

metadatathroughout the statistical production process.

• Sets out definitions, attributes and relationships regarding information objects

• Aligns with relevant standards such as DDI and SDMX– not directly tied to them, nor other concrete implementation details

• Provides common semantics that can be used unambiguously across and between different implementations

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How was GSIM developed?

• Pre-2012: Early project involving the NSIs of Australia, Canada, New Zealand, Sweden, UK & Norway

• February 2012: Sprint 1 hosted by NSI in Slovenia• April 2012: Sprint 2 hosted by NSI in South Korea • 4 Specification Layer Teams working remotely • September 2012: Integration Workshop hosted by

NSI in the Netherlands• 2 Teams currently working remotely on

Communication & User Guides

GSIM v0.8 Groups of information objects

Activity Production Conceptual InformationInformation Request Process Step Execution Concept Cube Data StructureChange Definition Process Step Design Classification Unit Data StructureBusiness Case Process Control Code Value Cube Data SetStatistical Program Process Input Level Unit Data SetStatistical Program Design Process Output Variable Cube Data PointStatistical Program Cycle Business Function Value Domain Unit Data PointData Resource Process Method Population Record RelationshipData Provider Rule Unit Dimension ComponentData Channel Business Service Measure ComponentProvision Agreement Instrument

Caveats1. The above table presents a selection of objects associated with each

Group – not a complete enumeration2. Identification and naming of objects is subject to further review

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Key messages & Next steps• The GSIM and DDI initiatives have many strategic aims in common.

– The initiatives present complementary, rather than competing, means to the same ends.

• GSIM is a key element of the HLG-BAS Strategy– including as an enabler for “Plug and Play” architecture

• The DDI has influenced the design of GSIM

– final alignment might be facilitated through extensions to DDI?

• Feedback on GSIM v0.8 from the DDI community– The sooner we can get feedback the better, but if we are to take it into

account for v1.0, then we need it by 31 October at the latest.

The planned release for GSIM v1.0 is December 2012

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More information on GSIM?

• International GSIM home page – New stuff is interesting stuff!

• GSIM v0.8 documentation– Brochure– Communication Layer– Specification Layer

» An extended feedback deadline for you - 31 October!