We present a perspective on an approach to data sharing in scientific publications we have been developing in our group. The essence of the approach is that data can be embedded in a human-readable and machine-addressable way within the traditional publishing environment. We show this by example for both computational and experimental data. We articulate a need for new authoring tools to facilitate data sharing, and we discuss the tools we have been developing for this purpose. With these tools, data generation, analysis, and manuscript preparation can be deeply integrated, resulting in easier and better data sharing in scientific publications.