Ontological Considerations When Modeling Missing Data With Relational Databases

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.

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