The Other Side of Linked Open Data: Managing Metadata Aggregation

The Other Side of Linked Open Data: Managing Metadata Aggregation

• 1.
  The Other Sideof Linked Data: Managing Metadata Aggregation ALCTS Metadata Interest Group ALA Midwinter 2014
• 2.
  Where Are WeNow? • Major projects so far focused on exposing selected portions of their data for ‘experimentation’ – Who’s using this data? – Can LOD for libraries succeed on that basis? • LOD is not just outputs, needs actual use to inform practice – A more complete view of the environment and workflow should help
• 3.
  Outline • Limitations ofthe traditional database strategy – Including records, normalization, de-duplication, etc. • Components of a fuller view – Workflow – Inputs, outputs – Data cache and services – Need for automated orchestration – The maintenance conundrum
• 4.
  Substituting a Cachefor 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
• 5.
  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]
• 7.
  Yellow=Data we usenow Green=Data we’re adding
• 9.
  Yellow=Data we sharenow Orange=Data we propose to share Green=Data categories we can share
• 10.
  Developing and DefiningServices • Small single purpose services are easier to develop and maintain – What services you need are determined by goals, evaluation results, etc. – ‘Orchestration’ of services applies them to specific kinds of data, in order – Services can be described, and linked, to expose who, what, when and how to downstream users
• 11.
  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
• 13.
  Data Maintenance • Improveddata 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’
• 14.
  Contact Information Diane Hillmann metadata.maven@gmail.com Gordon Dunsire gordon@gordondunsire.com JonPhipps jonphipps@gmail.com The First MetadataMobile