The document outlines a step-by-step approach to resource description using FRBR-based methods at Jane Austin University of Hawaii, emphasizing data structure from the RDA registry and visualization of records. It discusses workflow enhancement through the use of cache instead of traditional databases to enable better data management and automation. Key topics include data provenance, continuous improvement of data quality, and the importance of human versus machine roles in data handling.

1. A step-by-step introduction to describing the
resources swirling around Jane Austin
University of Hawaii, December 2014

2. Why RIMMF?

 Well constructed for FRBR-based description
 Data structure comes from RDA Registry
 Links to RDA Toolkit throughout data building
process
 Useful visualization of groups of records
 RDF export
 Improves discussion of issues with RDA
 Step-by-step illustration of adding a record [next]
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13. Issues for Discussion

 Record sharing
 Identification
 RDF
 Data Aggregation
 Looking more clearly at workflow and maintenance
 Provenance: who, what when, [where?]
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14. Substituting a Cache for
a Database

 Supports multiple streams of data
 Allows detailed provenance to be carried over time
 Separates services from data storage
 Allows more extensive automation (and
orchestration of services)
 Focuses valuable human effort where it’s needed:
analysis, design and implementation of
improvement services
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15. Workflow

 Obtain data (possibly as ‘records’)
 Store data as statements in cache
 Evaluate data by source or collection
 Improve data using specific services, as determined
by evaluation
 Publish improved data
 [Rinse, repeat]
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16. Developing Automated
Interaction

 Rule: Use humans for things requiring human
understanding and decision making
 Use machines for everything else
 A manual process for something a machine can do as
well or better is a failure
 Improvement services can be granular, invoked in
prescribed order, and report results for later use
 Continuous improvement necessary to respond to
continuous change
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17. Data Maintenance

• Improved data returns as statements to the data cache,
with provenance attached
• Statement strategy avoids overwriting of new data over
‘improved’ data
 Each new statement adds to what is known about a
described resource
 Statements can be cherry picked and exposed to others in
statements or records, in ‘flavors’ or as a ‘everything we
have’
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18. Contact Information
Diane Hillmann
metadata.maven@gmail.com
Links:
http://RDARegistry.info
http://marc21rdf.info
http://managemetadata.com/blog
/
The First MetadataMobile
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