Ensuring Data Reliability and Provenance

Provenance: what is it, why is it important

• the who, what, and when of metadata
• trusted identification of individuals/organizations
• assigning credit for creation and citation
• privacy rights
• judging the value of the data
• replicability of results
  

Provenance: how to achieve it

Data as Publication

• technology is there
• institutional change needed
• need to get institutional credit for data publication
  
• annotation/quality control
  

Handles: globally unique, persistent indentifiers for

• entities: people, organizations, roles
  
• documents
• views
• mashups
• doors

Software as a Service

• see tools group
  

Reliability

• preservation of the bits
• access,access and use, including privacy
  
• comprehensibility
• metadata and documentation
• adherence to standards (annotation, storage/retrieval/search)
  
• file format

Suggested first steps

• proactive education
• carrots
• mentors publish/share their data sets as model for next generation
• provide a "cite as" button with data
  
• service provision for data structure, integrity validation, and conversion
• sticks
• publishers/editors require provenance information
• editors and funding agencies encourage data sets to be published