  The relational data model offers unrivaled rigor and precision in defining
data structure and querying complex data. Yet the use of relational databases
in scientific data pipelines is limited due to their perceived unwieldiness. We
propose a simplified and conceptually refined relational data model named
DataJoint. The model includes a language for schema definition, a language for
data queries, and diagramming notation for visualizing entities and
relationships among them. The model adheres to the principle of entity
normalization, which requires that all data -- both stored and derived -- must
be represented by well-formed entity sets. DataJoint's data query language is
an algebra on entity sets with five operators that provide matching
capabilities to those of other relational query languages with greater clarity
due to entity normalization. Practical implementations of DataJoint have been
adopted in neuroscience labs for fluent interaction with scientific data
pipelines.
