Active Data Management Plans IG
The proposed activity of this group is to act as a nucleus for discussing requirements for and identifying developments needed to support active (i.e. able to evolve and be monitored) data management planning. Working groups will be proposed to carry out work on specific areas of interest.
Currently research data management plans (DMP), created at the proposal stage of a project, do not evolve and cannot be monitored in any detail. The DMP should begin at the planning stage for any dataset, evolving through its entire lifecycle and is therefore fundamental to ensuring that data is appropriately managed, archived, preserved and available for re-use.
There is very broad interest and willingness to contribute to the work. Preliminary ideas around the concept of ADMPs and potential topics for the working groups have been identified. These include specifying practical tools and services to support the data creators and their organisations in managing and making their data re-usable and also as the data managers and funders that have a requirement to administer and monitor these plans. The ADMP IG is distinct from, but will need to work with, many other groups including those on certification, domain repositories, metadata and preservation e-infrastructures.
TAB Review: https://rd-alliance.org/group/rda-technical-advisory-board-tab/wiki/tab-...
Author: Anna Clements
Date: 11 Mar, 2015
I think this is an important area for RDA to work in and should complement/support prospective/planned? work going on at DCC in UK on adding workflow to their DMPOnline tool. Will also be of interest to the CASRAI-UK DMP Working Group.
Author: Siri Jodha Khalsa
Date: 21 Mar, 2015
I understand why "active" is used as the modifier of DMP, to place it in contrast with a "static" DMP that is prepared at the befginning of a project and never changes. But there is a large body of work concerning the data lifecycle, which accounts for the dynamic nature of data and its management. Why not call the IG Lifecycle Data Management? Or is the focus entirely on a mechanisms for generating and maintaining a document (the DMP)?
Author: Peter Wittenburg
Date: 19 Aug, 2015
The question raised in the last comment is a very good one since it points to the two different sources of motivation:
- DMPs were invented by funders with the "good" intention to raise awareness about data issues and ask for explicit statements on how data will be treated within projects.
- Lifecyce DM aspects are certainly being discussed in advanced projects by scientists, data managers/curators etc. for intrinsic motivations
At the recent "Leading Scientist" workshop in Geneva this difference was pointed out very clearly when several scientists expressed their concerns about the current DMP activities (on purpose I use a very provocative style):
- they don't know how to fill them in usefully giving the huge variety in "data projects"
- for them currently DMPs are formal acts to create a piece of paper for evaluators to get the grants, so in scientists view this is a piecce of overhead that needs to be done and where they look for templates they can easily copy
- In many cases there are no clear services scientists can use for storing/managing/curating data and the costs are widely unknown
How can we bridge this gap to make DMPs useful and bring them close to LCDM which have an intrinsic motivation. Certainly accepting that DM is something active and that requirements are changing over project time is important, i.e. talking about active data management is essential and many of us know from own projects how dynamic the needs for data and their management are. However, I believe that we need to understand the deficits of the current DMPs before we move towards ADMPs. If we do not have a good understanding of these deficits (which requires interactions with scientists) we risk to even create more overhead for projects.
Funders want to have proper mechanisms for evaluating the seriousness of projects wrt their data. Thus they would like to have more useful DMPs allowing a better evaluation - not only at project start, but also during the projects and at the end of projects. Researchers hate useless overhead. How can the ADMP IG help to bridge this gap without creating just more overhead?