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Quality of Data Standards: Empirical Findings from XBRL

Hongwei (Harry) Zhu

University of Massachusetts Lowell; Massachusetts Institute of Technology (MIT); Old Dominion University

Liuliu Fu

affiliation not provided to SSRN

June 6, 2009

Certain data standards can help improve the quality of the data created according to the standards. But data standards do not always improve data quality. We introduce the notion of "quality of data standards" and argue that quality of data is affected by the quality of the standards used. We develop metrics for assessing quality of data standards. The metrics are evaluated empirically using company financial reports created using the eXtensible Business Reporting Language (XBRL) data standards. Our findings show the use frequency of standard data elements roughly follows a power law distribution. Tradeoffs exist between relevancy and completeness dimensions and between a single user perspective and user community perspective.

Number of Pages in PDF File: 8

Keywords: Data Quality, Interoperability, Data Standards, XBRL, Power Law Distribution, Long Tail

JEL Classification: Z00

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Date posted: February 22, 2010  

Suggested Citation

Zhu, Hongwei (Harry) and Fu, Liuliu, Quality of Data Standards: Empirical Findings from XBRL (June 6, 2009). Available at SSRN: https://ssrn.com/abstract=1556678 or http://dx.doi.org/10.2139/ssrn.1556678

Contact Information

Hongwei Zhu (Contact Author)
Old Dominion University ( email )
Norfolk, VA 23529
United States
757-683-5175 (Phone)
HOME PAGE: http://www.odu.edu/~hzhu
University of Massachusetts Lowell ( email )
One University Avenue
Lowell, MA 01854
United States
Massachusetts Institute of Technology (MIT) ( email )
Cambridge, MA 02139
United States
HOME PAGE: http://web.mit.edu/~mrzhu
Liuliu Fu
affiliation not provided to SSRN ( email )
Feedback to SSRN

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References:  14
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