Object oriented programming and relational databases create a certain mental model regarding how we think about data and its context–they both are oriented around the idea that context has data. In OOP, a class has fields, thus we think of the class as the context for the data. In an RDBMS, a table has columns and again our thinking is oriented to the idea that the table is the context for the data, the columns. Whether working with fields or record columns, these entities get reduced to native types — strings, integers, date-time structures, etc. At that point, the data has lost all concept as to what context it belongs! Furthermore, thinking about context having data, while technically accurate, can actually be quite the opposite of how we, as human beings, think about data. To us, data is pretty much meaningless without some context in which to understand the data. Strangely, we’ve ignored that important point when creating programming languages and databases — instead, classes and tables, though they might be named for some context, are really nothing more than containers.
Contextual data restores the data’s knowledge of its own context by preserving the information that defines the context. This creates a bidirectional relationship between context and data. The context knows what data it contains and the data knows to what context it belongs. In this article, I explore one approach to creating this bidirectional relationship — a declarative strongly typed relational contextual system using C#. Various points of interest such as data types and context relationships (“has a”, “is a”, “related to”) are explored. Issues with such a system, such as referencing sub-contexts in different physical root-level contexts, are also discussed.
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