A framework for translating the write-ups of experiments into a format that can be processed by computers has been developed by academics.

The new tool could revolutionise the way scientific papers are written and help scientists make creative leaps, researchers say.

Computers already help scientists by performing complex calculations and making information easier to analyse. But they are less suited to analysing and comparing experimental results.

"Computers are not very good with natural language, they need to have things as formalised as possible," says Ross King, a researcher at Aberystwyth University in Wales, who developed the framework with colleague Larisa Soldatova.

Called EXPO, it can be used to translate scientific experiments into a format that can be interpreted by a computer. The researchers have published the software code online so that anyone can use and modify it.

Quick comparison

"If lots of scientific papers were written in this way you could very quickly see whether an experiment has contradictions or agreements with other work," King told New Scientist. "It would also allow much more sophisticated search engines to find what you're looking for."

EXPO provides a descriptive framework, or ontology, to represent different stages of an experiment and the relationships between these stages. It also includes ways to define the hypothesis tested, the way results are analysed, and the conclusion drawn.

Researchers already use similar methods to represent specialised information, such as the genetic properties of different fly species, so that these can be stored in a computer database and accessed easily. However, EXPO is the first attempt to apply such an ontological framework across different sciences.

This means it can be used to compare the experimental methods used in very different scientific papers. The researchers used two existing papers to test EXPO – one on particle physics and one on evolutionary science.

Common ground

Translating the papers using EXPO made it possible for a computer to pick out similarities that might otherwise go unnoticed. For example, it revealed that both papers used a method of analysis known as a "statistical branching model".

"I don't suppose many particle physicists read evolution papers, but I'm sure both sides have done work that could be useful to the other," King says. "The maths is very similar – it is just used at very different time scales."

Ian Horrocks, an information management expert at Manchester University, UK, who was not involved with the research says it could prove useful in many practical situations.

"I have been involved with one large pharmaceutical company very interested in using ontologies to describe the work in its labs," he says. "They do so much at sites across the world that they often end up doing the same experiment twice, even in the same lab."

If computers could read experimental write-ups, such duplication would be avoided, he says: "It could save huge amounts of time, effort and money. They could avoid repeating what’s been done before and make better use of the knowledge that already exists."

King admits that for the moment using EXPO is time-consuming because experimental write-ups must be translated by hand. Software to speed up this process could be a big boost, he says: "Journals could also insist that researchers submit papers in EXPO as well as written normally."