We review the main components of autonomous scientific discovery, and how they lead to the concept of a Robot Scientist. This is a system which uses techniques from artificial intelligence to automate all aspects of the scientific discovery process: it generates hypotheses from a computer model of the domain, designs experiments to test these hypotheses, runs the physical experiments using robotic systems, analyses and interprets the resulting data, and repeats the cycle. We describe our two prototype Robot Scientists: Adam and Eve. Adam has recently proven the potential of such systems by identifying twelve genes responsible for catalysing specific reactions in the metabolic pathways of the yeast Saccharomyces cerevisiae. This work has been formally recorded in great detail using logic. We argue that the reporting of science needs to become fully formalised and that Robot Scientists can help achieve this. This will make scientific information more reproducible and reusable, and promote the integration of computers in scientific reasoning. We believe the greater automation of both the physical and intellectual aspects of scientific investigations to be essential to the future of science. Greater automation improves the accuracy and reliability of experiments, increases the pace of discovery and, in common with conventional laboratory automation, removes tedious and repetitive tasks from the human scientist.

Motivation: Many published manuscripts contain experiment protocols which are poorly described or deficient in information. This means that the published results are very hard or impossible to repeat. This problem is being made worse by the increasing complexity of high-throughput/automated methods. There is therefore a growing need to represent experiment protocols in an efficient and unambiguous way.

Results: We have developed the Experiment ACTions (EXACT) ontology as the basis of a method of representing biological laboratory protocols. We provide example protocols that have been formalized using EXACT, and demonstrate the advantages and opportunities created by using this formalization. We argue that the use of EXACT will result in the publication of protocols with increased clarity and usefulness to the scientific community.

Availability: The ontology, examples and code can be downloaded from http://www.aber.ac.uk/compsci/Research/bio/dss/EXACT/

Contact: Larisa Soldatova lss@aber.ac.uk