- web orientation
- researcher identity management
- authoring support
- object disclosure control
- data management support
- persistent storage
- full preservation archive, and
It is essential that the Data Management elements support current, dynamic data, not just static data. You may need to capture data from instruments, process it through workflow pipelines, or simply sit and edit objects, eg correcting database entries. Data Management also needs to support the opposite: persistent data that you want to keep un-changed (or perhaps append other data to while keeping the first elements un-changed).
One important element could be the ability to check-point dynamic, changing or appending objects at various points in time (eg corresponding to an article). In support of an article, you might have a particular subset available as supplementary data, and other smaller subsets to link to graphs and tables. These checkpoints might be permanent (maybe not always), and would require careful disclosure control (for example, unknown reviewers might need access to check your results, prior to publication).
Some parts of Data Management might support laboratory notebook capabilities, keeping records with time-stamps on what you are doing, and automatically providing contextual metadata for some of the captured datasets. Some of these elements might also provide some Health and Safety support (who was doing what, where, when, with whom and for how long).