Over the past two decades, the Meteorological Service of Canada (MSC) has made enormous strides in its technical data monitoring and production infrastructure. What only a short time ago was a manually intensive, data limited environment has been transformed to an automated infrastructure. This progress, however, was not matched by other components of MSC. Technology has outpaced underpinning structures that normally would be used as a roadmap to technical implementation. For example, a formal data management framework does not exist within MSC. Moving a piece of data from one place to another therefore tends to be considered based primarily on technology rather than information management criteria of whether the data should “go there” in the first place. This has resulted in spaghetti like architecture that affects data integrity and is more costly to maintain.

Throughout the past year, a new data management framework view has emerged for environmental data collected by the Monitoring Program of the Meteorological Service of Canada (MSC). This approach rationalizes the flow of monitoring data throughout MSC’s infrastructure and guarantees a formal life cycle management (LCM) capability for all such data being collected. This ensures the following 5 key data characteristics are achieved:

• Existence of an official value for all MSC data • Inclusion of data history • Consistent real-time QA/QC • Data availability and reliability • Long term archiving of data and metadata