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A novel method to infer logical relationships between sets is presented.These sets can be any collection of elements, for example astronomical catalogsof celestial objects. The method does not require the contents of the sets tobe known explicitly. It combines incomplete knowledge about the relationshipsbetween sets to infer a priori unknown relationships. Relationships betweensets are represented by sets of Boolean hypercubes. This leads to deductivereasoning by application of logical operators to these sets of hypercubes. Apseudocode for an efficient implementation is described.  The method is used in the Astro-WISE information system to inferrelationships between catalogs of astronomical objects. These catalogs can bevery large and, more importantly, their contents do not have to be available atall times. Science products are stored in Astro-WISE with references to otherscience products from which they are derived, or their dependencies. Thiscreates full data lineage that links every science product all the way back tothe raw data. Catalogs are created in a way that maximizes knowledge abouttheir relationship with their dependencies. The presented algorithm is used todetermine which objects a catalog represents by leveraging this information.

Leveraging Data Lineage to Infer Logical Relationships between Astronomical Catalogs