2008-12-15 AGU DataSpaces: Using Community Workspaces to Enable Rich Air Quality Metadata

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IN03: Emerging Cyberinfrastructure for Geosciences

Abstract Accepted: Tuesday Morning, 11:35am (15 minutes, session starts at 10:20) http://www.agu.org/cgi-bin/sessions5?meeting=fm08∂=IN22A&maxhits=400

Abstract: Currently, metadata for air quality datasets is variable, distributed and normally created by the provider for the user. However, a single dataset can be used for many applications that the provider may or may not anticipate and the data may go through many value-adding processes before it reaches the "end user". Additional metadata can be created at any step along the usage chain and at this time there is no mechanism for collecting this metadata. Consequently, users don't know how a dataset has been used or what additional processing has occurred beyond the originator. One method to harvest and share metadata from all members of the usage chain is through community workspaces, DataSpaces. DataSpaces are virtual spaces for contributing and archiving metadata, discussing the dataset and harvesting distributed resources in order to capture the critical community knowledge about the dataset.

A DataSpace for a given dataset has two parts, structured, semantically rich metadata and flexible community-contributed metadata. The structured dataset description includes standard dataset metadata, data lineage, and data quality information such as provider, parameters, platform and time period. The additional value of the DataSpaces comes from the context provided by the dataset community: users, mediators and providers. This may be through links to other mediator or user-provided metadata, publications that reference the dataset or web applications and tools using the dataset. DataSpaces also provides a place where a dataset community can connect through discussion and announcements about the dataset. As DataSpaces evolves and is used more by the community, additional functionality will emerge. Currently, there are still many issues with the implementation of DataSpaces including how to link the DataSpace to the dataset as it moves along the usage chain and how material in DataSpaces can be reused in other metadata.