Ensuring Data Reliability and Provenance

Provenance: what it is, why it is important

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

Provenance: how to achieve it

Curated data as Publication

• the technology is there
• institutional and social engagement needed
• need to get institutional credit for data publication
• encouragement of researchers to publish and cite
  
• annotation/quality control

Handles: globally unique, persistent identifiers for

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

Software as a Service

• see tools group
  

Reliability

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

Suggested first steps

• proactive education
• no linguist left behind!
  
• 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