Problem description
As part of the Government’s Action Program, since the beginning of 2020, a National Database of energy and operational characteristics of buildings has been created in Ukraine, which includes the collection and accumulation of information on technical and operational characteristics of buildings. At the same time, the quality of the information used is extremely important for performing a correct analysis of the entered data, identifying the dynamics and trends in energy consumption, planning energy efficiency measures and verifying the results obtained.
Ways to solve the problem
Therefore, in order to achieve maximum efficiency of data analysis, we have implemented a system of data quality control, which includes checking the information on the technical characteristics of buildings, energy consumption and providing recommendations for correcting erroneous data.
The technical characteristics and energy consumption of buildings in all regional state administrations of the 1st group were analyzed in detail. Much attention was paid to the analysis of the correctness of the basic values, such as the heating volume and the heating area, because these values are the basis for calculating the specific consumption for comparison. All buildings were examined in detail with a search for common mistakes. A description of what needs to be checked and corrected was provided for each building. A link to video instructions on typical errors that occur when entering data into the National Database has been added to the list with comments. Video instructions are one of the important components of data quality control and will increase the level of user knowledge and help to correct mistakes.
Results and benefits
31% of the regional state administration institutions of the first group were involved in data correction as a result of data quality control. The mistakes were corrected, which significantly affected the energy efficiency ratings of buildings.
As a result of long work with a large data set, it can be argued that unverified data is not reliable data. Therefore, there must be a systematic quality control of the data for the possibility of their further use.