Md. Salah Uddin¹, Dmitry V. Alexandrov¹ and Armanur Rahman², ¹National Research University Higher School of Economics (NRU HSE), Russian Federation and ²BJIT Limited, Bangladesh

Day by day data is increasing, and most of the data stored in a database after manual transformations and derivations. Scientists can facilitate data intensive applications to study and understand the behaviour of a complex system. In a data intensive application, a scientific model facilitates raw data products to produce new data products and that data is collected from various sources such as physical, geological, environmental, chemical and biological etc. Based on the generated output, it is important to have the ability of tracing an output data product back to its source values if that particular output seems to have an unexpected value. Data provenance helps scientists to investigate the origin of an unexpected value. In this paper our aim is to find a reason behind the unexpected value from a database using query inversion and we are going to propose some hypothesis to make an inverse query for complex aggregation function and multiple relationship (join, set operation) function.

Data Provenance, Structured Query Language (SQL), Query Processing, Query Inversion.