Good metadata management is essential for the efficient operation of statistical business processes. Metadata are present in every phase. The key challenge is to ensure that these metadata are captured as early as possible, and stored and transferred from phase to phase with their associated data. Metadata management strategy and systems are vital.
Part A of the Common Metadata Framework identifies the following 16 core principles for metadata management, all of which are addressed in the Metadata Management process and referenced when preparing the statistical metadata system (SMS) vision and global architecture, and when implementing the SMS. The principles can be presented in the following groups: Metadata handling, metadata authority, relationship to statistical cycles/processes, and users.
i. Statistical Business Process Model: Manage metadata with a focus on the overall statistical business process model.
ii. Active not passive: Make metadata active to the greatest extent possible to ensure they are accurate and updated. Active metadata are metadata that drive other processes and actions.
iii. Reuse: Reuse metadata where possible for statistical integration as well as efficiency.
iv. Versions: Preserve history of metadata by preserving old versions.
i. Registration: Ensure the registration process/workflow associated with each metadata element is well documented so there is clear identification of ownership, approval status, date of operation, etc.
ii. Single source: Ensure that a single, authoritative source, i.e., “registration authority,” for each metadata element exists.
iii. One entry/update: Minimize errors by entering once and updating in one place.
iv. Standards variations: Ensure that variations from standards are tightly managed, approved, documented, and visible.
Relationship to Statistical Cycle / Processes
i. Integrity: Make metadata-related work an integral part of business processes across the organization.
ii. Matching metadata: Ensure that metadata presented to end-users match the metadata that drove the business process or were created during the process.
iii. Describe flow: Describe metadata flow with the statistical and business processes, data flow, and business logic.
iv. Capture at source: Capture metadata at their source, preferably automatically as a byproduct of other processes.
v. Exchange and use: Exchange metadata and use them for informing both computer-based processes and human interpretation. The infrastructure for exchange of data and associated metadata should be based on loosely coupled components, with a choice of standard exchange languages, such as XML.
i. Identify users: Ensure that users are clearly identified for all metadata processes, and that all metadata captured will create value for them.
ii. Different formats: Metadata is diverse. Different views correspond to different uses of the data; users require different levels of detail; and metadata appear in different formats depending on the processes and goals for which they are produced and used.
iii. Availability: Ensure that metadata are readily available and useable in the context of the external or internal users’ information needs.