Exploring the Relationship between DDI, SDMX and the Generic Statistical Business Process Model. Arofan Gregory Open Data Foundation

Transcription

1 Exploring the Relationship between DDI, SDMX and the Generic Statistical Business Process Model Arofan Gregory Open Data Foundation

2 Outline Background: Industrializing the Production of Statistics The GSBPM DDI, SDMX, and the GSBPM Status of the Exploration: Combined Use of DDI and SDMX to Support the GSBPM

3 Background Industrializing the production of statistics is often mentioned today Organizations need to produce more data and better data, faster but they are often not being given the resources Like any other production process, there are inputs, processing, and outputs We could think of statistical production in this way The focus is placed on processing This is completely within the control of statistical organizations This is one reason for the popularity and success of the GSBPM

4 The GSBPM The Generic Statistical Business Process Model (GSBPM) is a reference model It is an agreed formalization of how organizations produce statistics It is very useful for supporting clear communications between organizations It supports efficiency improvements and shared approaches to the common mission of statistical production

5 Background: GSBPM Defining and modelling processes in statistical organisations started at least 10 years ago Statistical value chain Survey life-cycle Statistical process cycle Business process model

6 Which processes Defining and modelling processes in statistical organisations started at least 10 years ago Statistical value chain X Survey life-cycle X Statistical process cycle X Business process model X Generic Statistical Business Process Model

7 Why do we need a model? To define and describe statistical processes in a coherent way To standardize process terminology To compare / benchmark processes within and between organisations To identify synergies between processes To inform decisions on systems architectures and organisation of resources

8 Applicability All activities undertaken by producers of official statistics which result in data outputs National and international statistical organisations Independent of data source, can be used for: Surveys / censuses Administrative sources / register-based statistics Mixed sources

9 Structure of the GSBPM Process Phases Subprocesses (Descriptions)

10 Key features Not a linear model Sub-processes do not have to be followed in a strict order It is a matrix, through which there are many possible paths, including iterative loops within and between phases Some iterations of a regular process may skip certain sub-processes

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12 Links to DDI and SDMX SDMX standards refer to business processes, but do not have a model DDI has the Combined Life Cycle Model

13 Generic Statistical Business Process Model DDI 3.0 Combined Life Cycle Model 1 Specify Needs Study Concept 2 Design Repurposing (part) 3 Build 4 Collect Data Collection 5 Process Data Processing (mostly) Repurposing (part) 6 Analyse Data Discovery Data Analysis Data Processing (part) 7 Disseminate Data Distribution 8 Archive Data Archiving 9 Evaluate Quality Management Metadata Management

14 Combining standards Industrialization of statistical production GSBPM provides the framework, but more is needed: Information model Data / metadata formats Modular architecture Shared development of tools and methods

15 Data / metadata formats SDMX? Suitable for micro-data?? DDI? Suitable for exchange of statistical aggregates? Combined approach? Trial by Australian Bureau of Statistics

16 Combining standards?

17 Conclusions Too early to say for definite, but: No single standard meets all requirements Combine standards? GSBPM DDI SDMX Others? More work needed! Initial discussions between the SDMX community and the DDI community have been initiated Other related work is ongoing: GSIM, ESSnet CORE, etc.