Taking Another Look at the Data Management Life Cycle: Deconstruction, Agile, and Community
Friday, 19 December 2014
The data life cycle has figured prominently in describing the context of digital scientific data stewardship and cyberinfractructure in support of science. There are many different versions of the data life cycle, but they all follow a similar basic pattern: plan, collect, ingest, asses, preserve, discover, and reuse. The process is often interpreted in a fairly linear fashion despite it being a cycle conceptually. More recently at GeoData 2014 and elsewhere, questions have been raised about the utility of the data life cycle as it is currently represented. We are proposing to the community a re-examination of the data life cycle using an agile lens. Our goal is not to deploy agile methods, but to use agile principles as a heuristic to think about how to incorporate data stewardship across the scientific process from proposal stage to research and beyond. We will present alternative conceptualizations of the data life cycle with a goal to solicit feedback and to develop a new model for conceiving and describing the overall data stewardship process. We seek to re-examine past assumptions and shed new light on the challenges and necessity of data stewardship. The ultimate goal is to support new science through enhanced data interoperability, usability, and preservation.