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Ontological Considerations When Modeling Missing Data With Relational Databases
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DOI：10.1177/0894439314521988.png)
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Abstract
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SQL's use of nulls to indicate missing data in relational databases has been criticized as violating the relational model. In this article, I review this critique and two popular recommendations of resolution. The first is to retire SQL's multivalued logic and replace it with a conventional binary logic. The second is to revise SQL's implementation of multivalued logic so that it can recognize tautological propositions. I argue that underlying this debate is an ontological disagreement about how to properly model missing data and, more generally, social reality. I demonstrate that the relational model provides useful tools for modeling different types of missing data in different ways and, furthermore, offers a useful foundation upon which to conduct social research, one that supports both variable-oriented and case-oriented analysis.
Keywords:
relational databases
SQL
nulls
missing data
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