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Title:
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A SEMANTIC DATA MODEL FOR EFFICIENCY ENHANCEMENT OF THE HARMONIZED SURVEY ON HOUSEHOLDS LIVING STANDARDS |
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Author(s):
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Marc Mfoutou Moukala, Macaire Ngomo and Régis Freguin Babindamana |
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ISBN:
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978-989-8704-62 |
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Editors:
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Paula Miranda and Pedro Isaías |
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Year:
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2024 |
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Edition:
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Single |
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Keywords:
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Knowledge Documentation, Semantic Data Modeling, RDF Ontology, Harmonized Survey on Households Living
Standards, Survey Efficiency Enhancement |
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Type:
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Full |
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First Page:
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109 |
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Last Page:
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116 |
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Language:
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English |
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Cover:
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Full Contents:
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click to dowload 
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Paper Abstract:
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The Harmonized Survey on Households Living Standards (HSHLS) is the main housing statistical survey conducted by
French-speaking countries in West and Central Africa since the year 2018, which aims to capture household living
conditions information. The results of this survey are used by public authorities and development partners to identify areas
where necessary solutions can be provided to households or communities. The related questionnaires are administered
electronically in the form of Computer-Assisted Personal Interview (CAPI) using tablets and telephones, that helps reduce
errors during data collection because some data consistency checks are managed automatically through the data collection
application used, based on a set of prior real-world information. However, during data cleaning works, discrepancies are
sometimes observed between the methodology and the actual collected data. Moreover, data processing teams are often
forced to manually check methodologic documents for analysis purposes, this is a time-consuming task. In this paper, we
design and implement a semantic data model to represent the survey questionnaire's methodological information, based on
an ontology built using Resource Description Framework (RDF) and its extension, RDF Schema. By documenting
knowledge and data consistency constraints in a human and computer-readable way, this model allows minimizing errors
during data collection thanks to the defined constraints, and facilitates questionnaire's information retrieval. Therefore, the
proposed model improves the efficiency of the survey. |
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