DataKnots implements an algebraic query interface of Query Combinators. This algebra’s elements, or queries, represent relationships among class entities and data types. This algebra’s operations, or combinators, are applied to construct query expressions.

We seek to prove that this query algebra has significant advantages over the state of the art:

• DataKnots is a practical alternative to SQL with a declarative syntax; this makes it suitable for use by domain experts.

• DataKnots' data model handles nested and recursive structures (unlike DataFrames or SQL); this makes it suitable for working with CSV, JSON, XML, and SQL databases.

• DataKnots has a formal semantic model based upon monadic composition; this makes it easy to reason about the structure and interpretation of queries.

• DataKnots is a combinator algebra (like XPath but unlike LINQ or SQL); this makes it easier to assemble queries dynamically.

• DataKnots is fully extensible with Julia; this makes it possible to specialize it into various domain specific query languages.

This talk will provide a conceptual introduction to DataKnots.jl with applications in medical informatics.