As Earth and space science research organizations try to adapt to the pace of Web and Internet technology change, they also seek to utilize new means of managing complex data and information streams. Whether the people in these organizations serve their own needs, those of external communities, or both, the inevitable challenge to balance a stable working environment with the evolving ecosystems of highly heterogeneous data and information repositories and networks of people and organizations, remains.
In addition, as we become increasingly aware that people and other organizational entities and resources never really should have become decoupled from our data and information environments, architects are turning to an increasing set of common informatics approaches to co-design and co-evolve the needed platforms for science data.
In this contribution, we present the current state-of-the-art informatics methods for modeling, implementing and evolving data science and information architectures in the context of a new and ambitious decade-long activity; the Deep Carbon Observatory (funded by the AP Sloan Foundation). We conclude by presenting a discussion of how interworkability (cf. interoperability) may be an essential shift in thinking about the embedded role of people in science data platforms.