As I am putting together resources for the IMA cohort on creating a DMP to conduct impact measurement research and reporting in their makerspaces, I thought others may find some of this information useful as well.
I have spent many years in academia, as a faculty member, research librarian, and doctoral-level educational policy researcher. I understand research as a full cycle and process, and know the scholarly publishing model in great depth, including how overwhelmingly complex and difficult to navigate it can be. This difficulty, combined with closed publishing practices and a dearth of cross-sector collaboration and communication, leaves knowledge production in the scholarly corpus beyond the reach of the majority of society.
As many funders are requiring evidence-informed applications, this is a BIG problem; the current bias and skew within academic research leaves a big part of the world out of the discussion, since it is currently still a predominantly closed system. Frequently more closed to some populations than others, particularly women in STEM.
As a part of my role in supporting programming to increase research capacity at the local level, it is my goal to make social research methods concepts and tools understandable by everyone to empower the public sector to engage in scholarly research, regardless of whether or not they have an affiliation with an academic institution. And, my aim is to keep it as simple as possible - simplicity within a complex system can be tough.
As someone who has personally taught workshops in makerspaces on topics from learning the basics of simple circuits to backward engineering an air quality sensor for deployment in local townships, I have a deep appreciation for the limited amount of time and bandwidth there is to dedicate to research when you are already busy doing the thing you are trying to measure! I share with you all the below information in the hopes that you may find it useful, and, I welcome your comments, suggestions, and other resources you would like to share.
More on the DMP - What it is and why it is becoming increasingly important
A data management plan (DMP) is a formal statement describing how research data will be
managed and documented throughout a research project. This includes terms regarding the
subsequent deposit of the data for long-term management, preservation, and sharing of the
Data Management Plans are designed to be working documents and should be updated
as the project proceeds or if there are any significant changes to the initial project plan.
Below is a resource list I have started curating, bringing together information and recommendations from research institutions (predominantly African universities) that offer guidance on creating a DMP, providing a mapping to local research initiatives such as DRISA, for example.
For my own curiosity, I would be interested to know how many people in general have heard of or have used DMPTool before:
- I have used DMPTool to create a Data Management Plan
- I have heard of DMPTool, but have never used it
- I am not familiar with DMPTool
Feel free to drop additional links in this thread, of resources you’d like to share, or comments. I am always open for discussion.
Getting Started with DMPs: Resource List:
Federation of American Societies for Experimental Biology (FASEB)
Writing a Data Management Plan
Memorial Sloan Kettering Cancer Center
Example Data Management Plans (DMPs)
Nelson Mandela University
A Guide to Research Data Management
Research Data Management Planning: Research Data Management
University of South Africa
Research Data Management: Data Management and the Data Plan
University of Southampton
Research Data Management Planning Policies
University of Victoria
A Guide to Data Management Planning
University of Witwatersrand (WITS), Johannesburg:
A Guide to Digitisation, Preservation, Curation and Data Management
Vrije Universiteit Amsterdam
Research Data Management Overview