LTER Knowledgebase for Attribute Descriptions

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LTER Knowledgebase for Attribute Descriptions

• Peter McCartney (CAP)

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Goals

• Develop Strategic plan for implementing central
  knowledge base of attribute description
  ontologies in LTER
• Mission
• Goals
• Objectives

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• Are there substantial suites of monitoring
  observations from LTER sites that could be
  described with a smaller number of shared class
  descriptions? Which are they? What miminally is
  needed to provide a useful definition?

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• Are there existing systems of measurement
  description that can be adopted or emulated? eg
  EPA Storet.

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• How do we adopt this technology to enhance what
  now do with EML? How do we decide what
  information is most usefully recorded in a
  dataset-bound EML document and what is more
  usefully stored in some central, reusable
  context? How do we reference shared ontology
  concepts from EML documents?

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• Given what we know about completing EML, what
  strategies should we pursue in introducing
  central attribute descriptions and how should
  they be populated and managed.

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• How do we expect this information to benefit us?
  What sort of features would we expect to be able
  to implement in our information systems?

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Rationale

• Enhancing EML metadata
• Improved data access interfaces
• Supporting data integration research

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EML Issues

• Poor control over enumerated vocabularies
  units, spatial rep, file formats, etc
• attribute descriptions rich in ancillary info
  yet lack core semantics
• Shared attribute ontologies would provide comment
  reference for observation descriptions and
  resolve many extensibility isses with EML

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User Interface issues

• Trends project
• annual trends in core measurements from each LTER
  site
• Identified conflicts between how scientists
  approach data search and how archives are
  organized lumping and splitting, top-down,
  core/non-core
• Discussions between Brunt, McCartney, Peters on
  restructuring data archives from an observation
  oriented perspective
• Shared Attributes would enable discovery and
  query interfaces that emphasize observations

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Integration Research

• SEEK
• ontologies to link data concepts with analytic
  and processing concepts
• search and discovery
• Integration
• Shared attribute for LTER data provide a basis
  for operationalizing these tools