Measuring Data Completeness for Microbial Genomics Database
Poor quality data such as data with missing values (or records)cause negative consequences in many application domains. An important aspect of data quality is completeness. One problem in data completeness is the problem of missing individuals in data sets. Within a data set, the individuals refer...
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| Main Authors: | , |
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| Format: | Article |
| Language: | en |
| Published: |
Springer-Verlag Berlin Heidelberg
2013
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| Subjects: | |
| Online Access: | http://eprints.utem.edu.my/id/eprint/10960/1/nurulACIIDS2012.pdf http://eprints.utem.edu.my/id/eprint/10960/ |
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| Summary: | Poor quality data such as data with missing values (or records)cause negative consequences in many application domains. An important aspect of data quality is completeness. One problem in data completeness is the problem of missing individuals in data sets. Within a data
set, the individuals refer to the real world entities whose information is recorded. So far, in completeness studies however, there has been little discussion about how missing individuals are assessed. In this paper, we propose the notion of population-based completeness (PBC) that deals
with the missing individuals problem, with the aim of investigating what is required to measure PBC and to identify what is needed to supportPBC measurements in practice. This paper explores the need of PBC in the microbial genomics where real sample data sets retrieved from a microbial database called Comprehensive Microbial Resources are used(CMR). |
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