HAOSCD: VO, metadata, catalogs, ontologies, querying

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HAO/SCD VO, metadata, catalogs, ontologies,
querying

• Peter Fox, Jose Garcia, Patrick West (HAO)
• Don Middleton, Luca Cinquini, Dave Brown (SCD)

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Overview

• Virtual Observatory and semantics
• CEDARWEB
• Earth System Grid
• Metadata and catalog needs
• Queries

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Recent definition

• Workshop A Virtual Observatory (VO) is a suite
  of software applications on a set of computers
  that allows users to uniformly find, access, and
  use resources (data, software, document, and
  image products and services using these) from a
  collection of distributed product repositories
  and service providers. A VO is a service that
  unites services and/or multiple repositories
  (from NASA VO workshop, October 2004)
• VxOs - x is one discipline, you may have one and
  not call it a VO
• Increasingly, the need is for VxyO - i.e.
  interdisciplinary (or VxyzO, etc.) and emphasizes
  integration (data, processes, etc.)

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CEDARWEB 2.0
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CEDARWEB 3.x
Data query, selection and retrieval interface,
with integrated tools, e.g. ability to plot
(preview) data before retrieving it.
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CEDARWEB 3.x
Ability to quickly plot data to assess
suitability, quality, and produce a quick copy
with some customization for a preliminary study.
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Virtual Observatory Need better glue

• Basic problem schema are categorized rather than
  developed from an object model/class hierarchy -
  significantly limits non-human use. However, they
  all form the basis to organize catalog interfaces
  for all types of data, images, etc.
• This limits data systems utilizing frameworks and
  prevents frameworks from truly interoperating
  (SOAP, WSDL only a start)
• Directories, e.g. NASA GCMD, CEDAR catalog, FITS
  (flat) keyword/ value pairs, are being turned
  into ontologies (SWEET, VSTO)
• Markup languages, e.g. ESML, SPDML, ESG/ncML are
  excellent bases
• Evolve, recast, merge (where appropriate) using
  formal processes, tools with use-cases - for
  interface specifications, reasoning, validation,
  verification, inference, etc. beyond the usual
  search and access

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t,X
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Earth System Grid Portal
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Metadata-centric view of ESG services
DATA TRANSPORT
USER AUTHENTICATION AND AUTHORIZATION
LOCATION METADATA
DATA ANALYSIS VISUALIZATION
ACCESS AND AUTHORIZATION METADATA
AGGREGATION METADATA
METADATA SERVICES
CATALOGUING METADATA
CONTENT METADATA
DATA BROWSING
ANNOTATION HISTORY METADATA
LOGGING METADATA
SYSTEM MONITORING AND CONTROL
DATA SEARCH DISCOVERY
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ESG CLIENTS API USER INTERFACES
PUBLISHING
ANALYSIS VISUALIZATION
SEARCH DISCOVERY
ADMINISTRATION
BROWSING DISPLAY
HIGH LEVEL METADATA SERVICES
METADATA EXTRACTION
METADATA BROWSING
METADATA SEARCH, QUERY DISCOVERY
METADATA ANNOTATION
METADATA DATA REGISTRATION
METADATA DISPLAY
METADATA VALIDATION
METADATA AGGREGATION
METADATA CONVERSION
CORE METADATA SERVICES
METADATA ACCESS (update, insert, delete, query)
SERVICE TRANSLATION LIBRARY
METADATA HOLDINGS
Replica Location Services
Metadata Cataloguing Services
THREDDS catalogs
XML DB
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Catalogs for ESG
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Metadata and catalog needs

• As we wanted to do more with the data we started
  adding more use-metadata to the SQL catalog -
  was not scaling
• Some queries that need to be asked OR some
  inference/ reasoning may depend upon
• values of the data (as distinct from metadata,
  and/or
• structure of the data, and/or
• knowledge about the data and its related elements
  and/or
• relation of this dataset/variable/attribute to
  another
• Moving to Ontologies - need is to query the
  ontology Xquery or SPARQL
• Some of this can be done internally, some must
  call the SQL catalog (due to scaling/performance)

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Virtual Observatories

• Conceptual examples
• In-situ Virtual measurements
• Related measurements
• Remote sensing Virtual, integrative measurements
• Data integration

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The active Sun