73. The definition of Information Architecture 1 being used by CSPA is given below.
Information Architecture classifies the information and knowledge assets gathered, produced and used within the Business Architecture. It also describes the information standards and frameworks that underpin the statistical information. IA facilitates discoverability and accessibility, leading to greater reuse and sharing.

74. In other words, Information Architecture connects information assets to the business processes that need them and the IT systems that use and manage them. It includes relating the coherent and consistent definition of information assets at an enterprise level to the information needs of specific business processes and IT systems in practice.

75. It must support the needs of:

  • Business leaders, planners and process designers who are seeking to apply the Business Architecture from CSPA and who need to understand the connection between processes and information at a business level
  • Application architects and developers who are seeking to apply the Application Architecture from CSPA and who need to understand how CSPA Services interact with information

Reference frameworks and their use

76. The Information Architecture will identify common reference frameworks to be used for aligning communication and high level (conceptual) designs.

  • GSBPM will be used as a common reference when recording information in regard to business processes.
  • GSIM will be used as a common reference when defining the information input into, output from and used to support business processes.

  • CSDA 2 will be used as a common reference when designing the integration, production and dissemination of official statistics based on both traditional and new types of data sources.

  • A common reference framework to use when describing statistical methods performed by statistical services is a gap at this stage. 3

77. The completed Information Architecture will not only identify the reference frameworks which apply but also provide guidance on how they are applied, in combination, within CSPA.

The Information Architecture and CSPA

Statistical Service - Service Definition (Conceptual)

78. A major barrier to effective collaboration within and between statistical organizations has been the lack of common terminology. Using GSIM as a common language will increase the ability to compare information within and between statistical organizations. GSIM describes, at the conceptual level, the information that the statistical production process consumes, produces and is supported by.

Statistical Service - Service Specification (Logical)

79. In order for interoperability and reuse to be supported in practice when applying CSPA, the industry needs to do more than align conceptual designs using common frameworks. While GSIM describes the information objects relevant to statistical production it does not provide enough detail for implementation. When it comes to describing information objects in the real world we need to describe them in terms of standards for representing the precise logical relationships between them in a manner, which is consistent with GSIM.

80. Standards such as SDMX and DDI offer examples of such detailed logical models. They identify and use many more attributes than are defined within the GSIM model.

81. As these standards and practices have evolved independently, the objects and attributes they use are similar, but not consistent and can be implemented in many different ways. There is some overlap between the standards where a GSIM information object could be described using multiple standards and in some cases, there are information objects where neither DDI nor SDMX is appropriate.

Statistical Service - Implementation Specification (Physical)

82. Depending on what information is being represented in practice, DDI and SDMX are expected to provide the primary basis for the physical representation of statistical information (e.g. data and metadata) in CSPA.

83. A strong recommendation about specific standards for the logical and physical representation of business process information has not been stated yet 4 However, CSPA recognises that there are use cases in which process metadata would have value to the business, specifically for the use of orchestration and or workflow to execute statistical function services and the tracking of paradata for performance management. CSPA uses the business process information objects in GSIM.

84. For implementation, data and metadata may be communicated together or separately (recommended) provided that the data and metadata can be reunited when required. If the two are separated the data must contain a reconciling or correlating identifier for the metadata to enable it to be retrieved.

Implications for statistical organisations

85. Implementation specifications mean CSPA is prescriptive in regard to some practical details. While it would be simpler to align with CSPA if it was less prescriptive, the practical value from alignment would be much less. It is often the case that two developments which have a "common conceptual basis", but were implemented using completely unrelated approaches, are difficult and expensive to make interoperable and/or sharable (if it is possible at all).

86. In addition, an organization which has already implemented a different standard, or a local specification, can "map" their existing approach to the relevant implementation specification – they are not required to "rebuild" from first principles.

87. CSPA implementation specifications specify approaches which will support maximum interoperability/sharability on a cost effective basis. In particular cases it may be difficult for an organization to fully comply with a CSPA implementation specification (due to operational constraints). In these cases, compliance to the extent practical will still realize benefits. In other words, while CSPA implementation specifications provide a set of expectations, it is recognized that not all implementations may be able to achieve them fully in practice.

Information Architecture Principles


88. A number of principles which are common to most organization's information architecture (whether formally defined or not) have been agreed. These are outlined below. 

89. Principle: Manage information as an asset
Statement: Information is an asset that has value to the organization and must be managed accordingly.

90.  Principle: Manage the information lifecycle
Statement: All information has a lifecycle and should be managed to provide reliable identification, versioning and all information should be managed independently and beyond the scope of a single service. 

91.  Principle: Protect information appropriately
Statement: All personal, confidential and classified data should be protected and the data should be treated accordingly. 

92.  Principle: Use agreed models and standards
Statement: All information used as inputs and outputs to Statistical Services should be described using a common, business-oriented, reference model.

93.  Principle: Capture information as early as possible
Statement: Information should be captured in a standard and structured manner at the earliest possible point in the statistical business process to ensure it can be used by all subsequent services. 

94. Principle: Describe to ensure reuse
Statement: All information should be described in a manner that ensures information is reusable between services. Reuse is intended to reduce duplication, additional human intervention and reduce errors. 

95. Principle: Ensure there is an authoritative source
Statement: Information consumed and produced by services should be sourced and updated from a single authoritative source. Information should be consistent across all relevant services. 

96. Principle: Preserve information input into Statistical Services
Statement: Information that is input into services must be preserved to ensure no information loss. 

97. Principle: Describe information by metadata
Statement: All information consumed and produced by services must be described by sufficient metadata. 

  1. While the standards body responsible for TOGAF recognizes the term "Information Architecture", the formal model underlying TOGAF refers to "Data Architecture".  For "Data Architecture" CSPA references the Common Statistical Data Architecture (CSDA). ↩

  2. The CSDA puts the focus on Data because data is both the raw material, the components and the finished product of Statistical Organizations. Data therefore deserves to be treated as the asset it truly is. The CSDA is based on a set of Principles that stress the importance of treating data in appropriate ways.

    The Reference Data Architecture (link) focuses on the data-related functionality that statistical organisations will need for the design, integration, production and dissemination of official statistics. The document contains the description of the capabilities needed to achieve this.

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  3. The value agencies achieve through applying CSPA would be greater if such a framework existed. If a framework is agreed in future then it will be referenced in the Information Architecture. ↩
  4. The probable relevance of existing standards such as BPMN and BPEL is expected to be considered at a later stage of development of CSPA. However it is noted that while BPMN can provide a logical model of business processes it may not be directly implementable. ↩

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