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This talk addresses a wide range of issues in computer science education. The primary argument is that there are a set of skills that transcend the discipline and should be part of everyones skill set. I see lots of parallels with data literacy.  Presented by Mark Guzdial, a professor in the School of Interactive Computing at Georgia Institute of Technology.

This is a very public effort to promote the discussion of computational thinking. In the video they make the following statement, "Many teachers may already be teaching these skills. Computational thinking provides shared vocabulary and a framework to unify teachers' efforts." which I think is a great way to connect with what is already going on.

I think that this has some deep parallels to scientific data literacy. The focus on pedagogy is very interesting.

This article has descriptions of estimated changes in the expense and speed for genomic sequencing and interpretation.

This post describes a course built around the philosophy that students should be working with real data and solving real problems. 

I think this argument about pedagogical content knowledge has direct relevance to teaching scientific data literacy skills. We don't even have clear ideas about what our goals are - making it very difficult to build expertise in this area.