Metadata are a vital component of any network’s dataset. They bring richness and integrity to data, just as careful quality assurance techniques ensure fidelity. Metadata are most effective when delivered with – or, ideally, in advance of – the data itself.

Integration of metadata into the data stream is a three-step challenge. First, metadata must be identified, which is perhaps the most difficult of the three steps. Second, metadata must be harvested in a consistent and prudent manner. Third, metadata must be conveyed in a way that is useful, understandable and timely for the data client.

Several tools for pre-assessing the robustness and density of network data have been developed at the Oklahoma Climatological Survey (OCS). They were first implemented and tested on data from the U.S. Cooperative Observer Network, but their basic tenets are applicable to any geospatial meteorological dataset. The tools are designed to assist the data client with decisions regarding the appropriateness and availability of a dataset before he/she commits to its use.

This presentation will share the methods being implemented at OCS, from the perspective of the data client.