A Conceptual Model and Database to Integrate Data and Project Management

Abstract:

Data management is critically foundational to doing effective science in our data-intensive research era and done well can enhance collaboration, increase the value of research data, and support requirements by funding agencies to make scientific data and other research products available through publically accessible online repositories. However, there are few examples (but see the Long-term Ecological Research Network Data Portal) of these data being provided in such a manner that allows exploration within the context of the research process – what specific research questions do these data seek to answer? what data were used to answer these questions? what data would have been helpful to answer these questions but were not available? We propose an agile conceptual model and database design, as well as example results, that integrate data management with project management not only to maximize the value of research data products but to enhance collaboration during the project and the process of project management itself.

 In our project, which we call ‘Data Map,’ we used agile principles by adopting a user-focused approach and by designing our database to be simple, responsive, and expandable. We initially designed Data Map for the Idaho EPSCoR project “Managing Idaho’s Landscapes for Ecosystem Services (MILES)” (see https://www.idahoecosystems.org//) and will present example results for this work. We consulted with our primary users– project managers, data managers, and researchers to design the Data Map. Results will be useful to project managers and to funding agencies reviewing progress because they will readily provide answers to the questions “For which research projects/questions are data available and/or being generated by MILES researchers?” and “Which research projects/questions are associated with each of the 3 primary questions from the MILES proposal?” To be responsive to the needs of the project, we chose to streamline our design for the prototype database and build it in a way that is modular and can be changed or expanded to meet user needs. Our hope is that others, especially those managing large collaborative research grants, will be able to use our project model and database design to enhance the value of their project and data management both during and following the active research period.