Semantic Integration of Data: From Theory to Social Research Practice

Aggeliki Kazani, George Filandrianos, Maria Symeonaki () and Giorgos Stamou ()
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Aggeliki Kazani: Panteion University of Social and Political Sciences, Department of Social Policy
George Filandrianos: School of Electrical and Computer Engineering, National Technical University of Athens
Maria Symeonaki: Panteion University of Social and Political Sciences, Department of Social Policy
Giorgos Stamou: School of Electrical and Computer Engineering, National Technical University of Athens

Chapter Chapter 23 in Quantitative Demography and Health Estimates, 2023, pp 303-314 from Springer

Abstract: Abstract As mixed methodologies in social science research gain growing attention, the need to provide an integrated framework for combining qualitative, quantitative, and in general diverse types of data, is rapidly and analogously increasing. Semantic integration of data, a process of interrelating information from diverse sources and consolidating it into meaningful and valuable information using formal specifications of domain conceptualisations, i.e., taxonomies, can constitute a very valuable approach and an alternative view regarding mixed methods in social research. The present paper firstly outlines the basic theoretical definitions linked to semantic integration of data and then delves deeper into elements and assumptions that underlay the use of this specific methodology for organising and analysing social data from diverse sources made available through empirical social research. Finally, the study closes with the description of a recent, enlightening application in the field of ICT use and the digital transformations context.

Keywords: Machine learning; Semantic integration; Ontology; Social research; Taxonomies; ICT use (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:spr:ssdmcp:978-3-031-28697-1_23

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DOI: 10.1007/978-3-031-28697-1_23

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