Ensure flexible data services for virtual datasets

In order for a large dataset to be effectively used by a variety of end users, the following procedures for preparing a virtual dataset are recommended:

• Identify data service users

• Define data access capabilities needed by community(s) of users. For example:
  • Spatial subsetting
  • Temporal subsetting
  • Parameter subsetting
  • Coordinate transformation
  • Statistical characterization

• Define service interfaces based upon Open Standards. For example:

  • Open Geospatial Consortium (OGC WMS, WFS, WCS)
  • W3C (SOAP)
  • IETF (REST – derived from Hypertext Transfer Protocol [HTTP])

• Publish service metadata for published services based upon Open Standards. For example:

  • Web Services Definition Language (WSDL)
  • RSS/Atom (see Service Casting reference below for an example of a model for publishing service metadata for a variety of service types)

Description Rationale

Some datasets are too large to efficiently deliver in their entirety, or are not directly usable by some users. To enable their effective use by a variety of end users, data collections may be published as “virtual” datasets that are extracted and/or processed based upon source data and pre-defined functions that deliver products derived from the source data.

Additional Information:

Web Service Definition Language
Service Casting via RSS/Atom

Cite this best practice:

DataONE Best Practices Working Group, DataONE  (July 01, 2010) "Best Practice: Ensure flexible data services for virtual datasets". Accessed through the Data Management Skillbuilding Hub at https://dataoneorg.github.io/Education/bestpractices/ensure-flexible-data on Mar 01, 2024