A case study presented at UX Cambridge 2016.
For hundreds of years, discoveries in science have been discussed, debated and advanced within the scientific literature. Finding evidence in the literature, to test a hypothesis, is fundamental to scientific research.
But finding evidence in scientific literature can be time consuming and difficult, especially as the number of published articles increases significantly each year. Advances in text mining technology offer the potential to make this task easier and quicker. Text miners are software engineers and subject experts who write algorithms to find useful information in vast amounts of unstructured text content. Deciding what information is useful to end users, and presenting it in an intuitive way, at the right point in time, is where UX can help.
This is a case study about annotating scientific terms and concepts in millions of research articles, with the goal to help life science researchers identify relevant information in articles quickly and easily. We explain how text miners, UX and developers collaborated; what we discovered about user needs; challenges and constraints we faced and iterative improvements we have made to the design.