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Visualising Inconsistency and Incompleteness in RDF Gene Expression Data using FCA

Visualising Inconsistency and Incompleteness in RDF Gene Expression Data using FCA

Honour Chika Nwagwu
Copyright: © 2014 |Volume: 2 |Issue: 1 |Pages: 15
ISSN: 2166-7292|EISSN: 2166-7306|EISBN13: 9781466653375|DOI: 10.4018/ijcssa.2014010105
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MLA

Nwagwu, Honour Chika. "Visualising Inconsistency and Incompleteness in RDF Gene Expression Data using FCA." IJCSSA vol.2, no.1 2014: pp.68-82. http://doi.org/10.4018/ijcssa.2014010105

APA

Nwagwu, H. C. (2014). Visualising Inconsistency and Incompleteness in RDF Gene Expression Data using FCA. International Journal of Conceptual Structures and Smart Applications (IJCSSA), 2(1), 68-82. http://doi.org/10.4018/ijcssa.2014010105

Chicago

Nwagwu, Honour Chika. "Visualising Inconsistency and Incompleteness in RDF Gene Expression Data using FCA," International Journal of Conceptual Structures and Smart Applications (IJCSSA) 2, no.1: 68-82. http://doi.org/10.4018/ijcssa.2014010105

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Abstract

The integration of data from different data sources can result to the existence of inconsistent or incomplete data (IID). IID can undermine the validity of information retrieved from an integrated dataset. There is therefore a need to identify these anomalies. This work presents SPARQL queries that retrieve from an EMAGE dataset, information which are inconsistent or incomplete. Also, it will be shown how Formal Concept Analysis (FCA) tools notably FcaBedrock and Concept Explorer can be applied to identify and visualise IID existing in these retrieved information. Although, instances of IID can exist in most data formats, the investigation is focused on RDF dataset.

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