Data Quality and Management

Data Quality and Management is a research topic within Management Science and Operations Research. Science Explorer counts 26k research works in it since 1953. 9.9% of them reached the world's top 10% most cited for their field and year.

This cluster of papers focuses on data quality assessment, improvement, and related techniques such as record linkage, data cleaning, entity resolution, information quality benchmarks, and privacy-preserving record linkage. It also covers topics like name disambiguation, data integration, and the challenges of data quality in the era of big data.

• Record Linkage
• Data Cleaning
• Entity Resolution
• Information Quality
• Duplicate Detection
• Name Disambiguation
• Data Integration
• String Similarity
• Big Data
• Privacy Preserving