Analytics Driving CEDAR

To make useful suggestions for metadata authors, CEDAR must anticipate their intentions, and make it easier for them to perform their tasks. The CEDAR project uniquely invests in analytics research, and especially focuses on evaluating the application of those research results to actual metadata entry in the real world. CEDAR’s success depends on the identification and application of patterns and relations in existing metadata, and we will be evaluating our success across many axes.

You are welcome to contact us if you are interested in using CEDAR’s metadata resources for your own analytics projects.

Analytics Projects Driving CEDAR

Last Updated: 
Sep 25 2020 - 11:14am
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Context-Sensitive Value Suggestions
While good metadata is essential in finding, interpreting, and reusing data, the authoring of metadata is considered tedious and is often incomplete. Towards easing the burden of authoring high quality metadata, we have developed a data-driven framework to leverage associations between data elements to suggest context-sensitive metadata values.... Read more about this concept
Incorporating Structural Knowledge
We already have some understanding of the relationship between different metadata components. For example, there is a well-defined concept of a work contact, made up of particular metadata elements like phone number and email, and associated with a particular person. While we can derive much of this information using a data mining approach, it may... Read more about this concept
Evaluating Multiple Techniques
The CEDAR researchers are likely to identify many strategies for determining likely metadata entries, or optimal value sets, under given conditions. It may not be obvious which combination of techniques is most effective, or most appealing for the end user. From a data mining standpoint, we will have the ability to assess which techniques are most... Read more about this concept