How contribution in "data analysis" and "data interpretation" are different, for a scientific paper? When submitting a paper to a highly profiled publication, like Nature or Science, author contributions must be clarified. This may include study design; data acquisition, analysis, and interpretation; draft preparation and/or critical editing and review of the manuscript.
Among these aspects, I was wondering how data analysis and data interpretation are different? Consider the boundaries may not be quit clear, because more often it is difficult to analyze data to find true patterns without being able to interpret those patterns.
I agree that the boundaries are not quite clear in that it is impossible to analyse a set of data without giving some sort of interpretation to them at the same time. 

The requirement however doesn't mean that you have to identify a single author for each contribution. For example, you can say that author A contributed to data acquisition, author B to both data analysis and interpretation. 

In an experiment, data acquisition can simply mean running the tests without processing the data into more meaningful plots or graphs. The latter falls into the category of data analysis. Discussing what the data mean comes into interpretation. While interpretation cannot be absent in any analysis, and so I cannot imagine an author contributing to analysis but not to interpretation, the reverse may be possible. An author can contribute to interpretation without contributing to analysis.