Towards near-real time data property specification and verification for Arctic hyperspectral sensor data

Irbis Gallegos, Santonu Goswani, Ann Q. Gates, Craig E. Tweedie, John Gamon

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Environmental scientists, especially those conducting studies in remote areas such as the Arctic, can benefit from assessing data quality from autonomous sensors in near-real time. The Data Assessment Run-Time (DART) framework was developed to allow environmental scientists to specify and verify data properties associated with autonomous sensors. Data properties are logical statements about data values associated with sensors and their relationship with other sensor output or properties derived from historical data. The properties can be verified at near-real time, i.e., as the data are being collected in the field, or through post-processing routines after the data has been collected. This paper describes a case study that evaluates the specification of data properties associated with hyperspectral sensor data and how the DART framework was used to verify these data in both near-real time and through post-processing.

Original languageEnglish (US)
Title of host publication2011 Annual Meeting of the North American Fuzzy Information Processing Society, NAFIPS'2011
DOIs
StatePublished - 2011
Externally publishedYes
Event2011 Annual Meeting of the North American Fuzzy Information Processing Society, NAFIPS'2011 - El Paso, TX, United States
Duration: Mar 18 2011Mar 20 2011

Publication series

NameAnnual Conference of the North American Fuzzy Information Processing Society - NAFIPS

Conference

Conference2011 Annual Meeting of the North American Fuzzy Information Processing Society, NAFIPS'2011
Country/TerritoryUnited States
CityEl Paso, TX
Period3/18/113/20/11

Keywords

  • data assessment
  • Data Quality
  • information quality
  • near-real time data assessment
  • sensor data assessment

ASJC Scopus subject areas

  • General Computer Science
  • General Mathematics

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