Logic and the Automatic Acquisition of Scientific Knowledge

This paper is a manifesto. It argues that: Science is experiencing an unprecedented "explosion" in the amount of available data. Traditional data analysis methods cannot deal with this increased quantity of data. There is therefore an urgent need to automate the process of refining scientific data into scientific knowledge. Inductive logic programming (ILP) is the data analysis framework best suited for this task. We describe an example of using ILP to analyse a large and complex bioinformatic database which produced unexpected and interesting scientific results. We then point a possible way forward to integrating machine learning with scientific databases to form intelligent inductive databases.