Abstract

Techniques for linking and integrating data from different sources are becoming increasingly important in many application areas, including health, census, taxation, immigration, social welfare, in crime and fraud detection, in the assembly of national security intelligence, for businesses, in bibliometrics, as well as in the social sciences.

In today's Big Data era, data linkage (also known as entity resolution, duplicate detection, and data matching) not only faces computational challenges due to the increasing size of data collections and their complexity, but also operational challenges as many applications move from static environments into real-time processing and analysis of potentially very large and dynamically changing data streams, where real-time linking of records is required. Additionally, with the growing concerns by the public of the use of their sensitive data, privacy and confidentiality often need to be considered when personal information is being linked and shared between organisations.

In this talk I will present a short introduction to data linkage, highlight recent developments in advanced data linkage techniques and methods – with an emphasis on work conducted in the computer science domain – and discuss future research challenges and directions.