it can be used for both negative and positive continuous values

http://support.minitab.com/en-us/minitab/17/topic-library/quality-tools/capability-analyses/distributions-and-transformations-for-nonnormal-data/data-transformations/#what-does-the-johnson-transformation-do

https://www.unistat.com/guide/quality-control-data-transformation/#u9371

Many thanks  Faye Anderson, much appreciated

do not use transformation

Article TO DETERMINE SKEWNESS, MEAN AND DEVIATION WITH A NEW APPROAC...

Thank you very much  Guven Mehmet Gunver

The Johnson transformation will be unable to "normalise" data which is multimodal, although it might be able to "improve" certain properties, depending on why you are trying to normalise the data. Similarly, it is not immediately suitable for discrete-valued data unless you are willing/able to deal with moving from a regular to an irregular grid of possible values ... which might  mean just treating the data as if they were continuous-valued (which may be reasonable in some cases).

 Dear David A. Jones, many thanks for your help, much appreciated

For a very interesting discussion see thelink below. Broadly I agree with the thrust of their argument that not all data is suitable for normalisation and even if it is  normalising it may hide important trends. Also it isoften possible to use non-parametric methods which do not rely on assuming a data distribution.