QTrail-DB: A Query Processing Engine for Imperfect Databases with Evolving Qualities

Maha Asiri, Mohamed Y. Eltabakh

Abstract: Imperfect databases are very common in many applications due to various reasons ranging from data-entry errors, transmission errors, and wrong instruments’ readings, to faulty experimental setups leading to incorrect results. The management and query processing of imperfect databases is a very challenging problem requires incorporating the data’s qualities within the database engine. Even more challenging, the qualities are not static and may evolve over time. Unfortunately, most of the state-of-art techniques deal with the data quality problem as an offline task. In this paper, we propose the “QTrail-DB” system that introduces a new quality model based on the new concept of “Quality Trails”, which captures the evolution of the data’s qualities over time. QTrail-DB extends the relational data model to incorporate the quality trails within the database system. We propose a new query algebra, called “QTrail Algebra”, that enables transparent propagation and derivations of the data’s qu