As recent developments in text mining, natural language processing and machine learning are becoming more mainstream, the task of generating data driven insights and learning from health and safety operational intelligence, particularly from free text, is now far easier than it was before.
Therefore, rather than reviews of operational intelligence being based on small samples of available data and largely manual and qualitative exercises, entire corpuses of information can now be analysed quickly and with increasingly fine granularity. Interrogating health and safety operational intelligence, including that held in free text formats with the help of text mining and natural language processing tools, has the potential to yield a range of different types of learning for organisations beyond that generated using traditional approaches used by organisations.
For example, rather than routine datasets merely being used largely for operational reporting purposes, essentially to profile what has gone wrong from a health and safety perspective and where, when and to whom, use of text mining opens up opportunities to address other key health questions in an automated way, such as how and why specific health and safety failures happened and to discover new and emerging problems in workplaces and even to predict future failure events.
The text mining project being delivered as part of Discovering Safety will use existing state of the art in text mining and natural language processing as a start point and develop analytic tools and techniques for specific use in health and safety contexts.