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Title: Energy-data validation: an overview and some concepts

Abstract

Energy data validation can be viewed operationally as a three-fold assessment process: (1) a determination of the quality of the data collected, i.e., an assessment of accuracy; (2) an analysis of the relevance and usefulness of the data so as to assess how closely the data collected is meeting the requirements of its users; (3) an assessment of measures that can be taken to enhance the effectiveness of the data system under study. Assessment (1) is akin to the process of critical evaluation of data in the physical sciences. Assessments (2) and (3), the more distinctive features, underlie two important goals of validation. In brief, the analyst validates both the information and the requirements for the information, and as deficiencies in these two aspects are uncovered, the validation analyst formulates and evaluates the means for correcting these deficiencies. This paper focuses upon the use of an error model for systematizing the assessment of accuracy in a data-system validation study. Other topics discussed briefly are: a capsule history of energy-data validation; ORNL studies of outlier detection methods, automatic data editing and sampling theory in support of the energy-data validation program; reviews of energy-data requirements.

Authors:
;
Publication Date:
Research Org.:
Oak Ridge National Lab., TN (USA)
OSTI Identifier:
6868004
Alternate Identifier(s):
OSTI ID: 6868004; Legacy ID: DE82020901
Report Number(s):
CONF-810842-7
ON: DE82020901
DOE Contract Number:
W-7405-ENG-26
Resource Type:
Conference
Resource Relation:
Conference: American Statistical Association meeting, Detroit, MI, USA, 10 Aug 1981; Other Information: Portions of document are illegible
Country of Publication:
United States
Language:
English
Subject:
29 ENERGY PLANNING, POLICY AND ECONOMY; 71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSICS; ENERGY INFORMATION ADMINISTRATION; STATISTICS; VALIDATION; DATA ACQUISITION; DATA ANALYSIS; DATA COVARIANCES; ERRORS; MATHEMATICS; NATIONAL ORGANIZATIONS; TESTING; US DOE; US ORGANIZATIONS 290100* -- Energy Planning & Policy-- Energy Analysis & Modeling; 657006 -- Theoretical Physics-- Statistical Physics & Thermodynamics-- (-1987)

Citation Formats

Loebl, A.S., and Cantor, S.. Energy-data validation: an overview and some concepts. United States: N. p., 1981. Web.
Loebl, A.S., & Cantor, S.. Energy-data validation: an overview and some concepts. United States.
Loebl, A.S., and Cantor, S.. Thu . "Energy-data validation: an overview and some concepts". United States. doi:.
@article{osti_6868004,
title = {Energy-data validation: an overview and some concepts},
author = {Loebl, A.S. and Cantor, S.},
abstractNote = {Energy data validation can be viewed operationally as a three-fold assessment process: (1) a determination of the quality of the data collected, i.e., an assessment of accuracy; (2) an analysis of the relevance and usefulness of the data so as to assess how closely the data collected is meeting the requirements of its users; (3) an assessment of measures that can be taken to enhance the effectiveness of the data system under study. Assessment (1) is akin to the process of critical evaluation of data in the physical sciences. Assessments (2) and (3), the more distinctive features, underlie two important goals of validation. In brief, the analyst validates both the information and the requirements for the information, and as deficiencies in these two aspects are uncovered, the validation analyst formulates and evaluates the means for correcting these deficiencies. This paper focuses upon the use of an error model for systematizing the assessment of accuracy in a data-system validation study. Other topics discussed briefly are: a capsule history of energy-data validation; ORNL studies of outlier detection methods, automatic data editing and sampling theory in support of the energy-data validation program; reviews of energy-data requirements.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Thu Jan 01 00:00:00 EST 1981},
month = {Thu Jan 01 00:00:00 EST 1981}
}

Conference:
Other availability
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