  The steadily growing number of linked open datasets brought about a number of
reservations amongst data consumers with regard to the datasets' quality.
Quality assessment requires significant effort and consideration, including the
definition of data quality metrics and a process to assess datasets based on
these definitions. Luzzu is a quality assessment framework for linked data that
allows domain-specific metrics to be plugged in. LQML offers notations,
abstractions and expressive power, focusing on the representation of quality
metrics. It provides expressive power for defining sophisticated quality
metrics. Its integration with Luzzu enables their efficient processing and
execution and thus the comprehensive assessment of extremely large datasets in
a streaming way. We also describe a novel ontology that enables the reuse,
sharing and querying of such definitions. Finally, we evaluate the proposed DSL
against the cognitive dimensions of notation framework.
