Using Concept Lattices to Reconcile Semantic Heterogeneity in Data

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In modern information systems, data capture often cannot be closely controlled by traditional organizational mechanisms intended to enforce common meaning. Additionally, data are no longer used only for established and predetermined purposes. Indeed, one of the key promises of Big Data and Open Data is the opportunity to repurpose data for uses that were not anticipated when systems to collect and store the data were designed. This increasingly diverse information landscape creates significant challenges in integrating or combining information from various sources in ways that retain the semantics (meaning) of the underlying data. Integration difficulties arise from the independence of sources, resulting in a high level of semantic heterogeneity between sources. Achieving high-quality semantic integration is essential to take full advantage of the opportunities afforded by Big Data to support decision-making.