BackgroundFree-text data represent a vast, untapped source of rich information to guide research and public service delivery. Free-text data contain a wealth of additional detail that, if more accessible, would clarify and supplement information coded in structured data fields. Personal data usually need to be de-identified or anonymised before they can be used for purposes such as audit and research, but there are major challenges in finding effective methods to de-identify free-text that do not damage data utility as a by-product. The main aim of the TexGov project is to work towards data governance standards to enable free-text data to be used safely for public benefit.
 MethodsWe conducted: a rapid literature review to explore the data governance models used in working with free-text data, plus case studies of systems making de-identified free-text data available for research; we engaged with text mining researchers and the general public to explore barriers and solutions in working with free-text; and we outlined (UK) data protection legislation and regulations for context.
 ResultsWe reviewed 50 articles and the models of 4 systems providing access to de-identified
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