Table of Contents
Comments
Commenters1
In this model there is a central aggregator, with no common metadata schema defined. Each of the content owners provides their metadata in their existing format together with their schema. Examples are RepUK, Go-Geo! and VADS (though for VADS the schemas are quite standardised for image collections). This is described in the following diagram:
In this model there is a central aggregator, with no common metadata schema defined. Each of the content owners provides their metadata in their existing format together with their schema. Examples are RepUK, Go-Geo! and VADS (though for VADS the schemas are quite standardised for image collections). This is described in the following diagram:
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One example of a service could be to create a standardised schema with associated metadata from a subset of the available schemas and metadata. This would enable those with more specific needs for metadata to develop a schema based on their needs, and convert the metadata into that standardised schema accordingly. This could be of particular use in relation to subject areas with significantly differing needs, considering for example the analysis of medical images, geological images and performance art films.
One example of a service could be to create a standardised schema with associated metadata from a subset of the available schemas and metadata. This would enable those with more specific needs for metadata to develop a schema based on their needs, and convert the metadata into that standardised schema accordingly. This could be of particular use in relation to subject areas with significantly differing needs, considering for example the analysis of medical images, geological images and performance art films.5
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One participant thought that this model would become unmanageable if there were too many schemas in the aggregation, and considered that up to about six would be manageable. However, a number of the aggregators already using this model include more than six data sets, so this limit can be overcome.
One participant thought that this model would become unmanageable if there were too many schemas in the aggregation, and considered that up to about six would be manageable. However, a number of the aggregators already using this model include more than six data sets, so this limit can be overcome.7
As this model would extend to holding metadata schemas and the associated data sets for other media, this would allow for users who would like to be able to see information about their areas in more detail. One example is a researcher, who wanted to see images and films about a subject, linked to the papers in which they had been used and the books and papers that were referenced in the paper. This approach has been nicknamed the ‘pick n mix’ approach, since those who want to use the metadata can aggregate the schemas they choose in any way they choose.
As this model would extend to holding metadata schemas and the associated data sets for other media, this would allow for users who would like to be able to see information about their areas in more detail. One example is a researcher, who wanted to see images and films about a subject, linked to the papers in which they had been used and the books and papers that were referenced in the paper. This approach has been nicknamed the ‘pick n mix’ approach, since those who want to use the metadata can aggregate the schemas they choose in any way they choose.