Data correction refers to the process of identifying and rectifying errors or inconsistencies in data. This process involves cleaning, validating, and transforming data to ensure its accuracy and reliability for analysis and decision-making purposes. Data correction may involve tasks such as removing duplicate entries, correcting misspellings, filling in missing values, and standardizing formats. This area of research focuses on developing methods, algorithms, and tools to effectively and efficiently correct data errors to improve the quality and integrity of datasets.