TY - JOUR
T1 - An integrated view of data quality in Earth observation
AU - Yang, X.
AU - Blower, J. D.
AU - Bastin, L.
AU - Lush, V.
AU - Zabala, A.
AU - Masó, J.
AU - Cornford, D.
AU - Díaz, P.
AU - Lumsden, J.
PY - 2013/1/28
Y1 - 2013/1/28
N2 - Data quality is a difficult notion to define precisely, and different communities have different views and understandings of the subject. This causes confusion, a lack of harmonization of data across communities and omission of vital quality information. For some existing data infrastructures, data quality standards cannot address the problem adequately and cannot fulfil all user needs or cover all concepts of data quality. In this study, we discuss some philosophical issues on data quality. We identify actual user needs on data quality, review existing standards and specifications on data quality, and propose an integrated model for data quality in the field of Earth observation (EO). We also propose a practical mechanism for applying the integrated quality information model to a large number of datasets through metadata inheritance. While our data quality management approach is in the domain of EO, we believe that the ideas and methodologies for data quality management can be applied to wider domains and disciplines to facilitate quality-enabled scientific research. © 2012 The Authors.
AB - Data quality is a difficult notion to define precisely, and different communities have different views and understandings of the subject. This causes confusion, a lack of harmonization of data across communities and omission of vital quality information. For some existing data infrastructures, data quality standards cannot address the problem adequately and cannot fulfil all user needs or cover all concepts of data quality. In this study, we discuss some philosophical issues on data quality. We identify actual user needs on data quality, review existing standards and specifications on data quality, and propose an integrated model for data quality in the field of Earth observation (EO). We also propose a practical mechanism for applying the integrated quality information model to a large number of datasets through metadata inheritance. While our data quality management approach is in the domain of EO, we believe that the ideas and methodologies for data quality management can be applied to wider domains and disciplines to facilitate quality-enabled scientific research. © 2012 The Authors.
KW - Data quality
KW - Earth observation
KW - Environmental informatics
KW - Metadata
KW - Provenance
KW - Uncertainty
U2 - 10.1098/rsta.2012.0072
DO - 10.1098/rsta.2012.0072
M3 - Article
SN - 1364-503X
VL - 371
JO - Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences
JF - Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences
M1 - 20120072
ER -