Data-guided research development

Advances in data science are transforming the research ecosystem at unprecedented rates. While universities are central in those advancements, their administrative systems may lag considerably, precluding even basic analytical approaches to strategic development. In some cases, necessary data do not exist− in other cases, it may exist across isolated systems that are not readily interoperable. I combine distributed sources of data to approach research development through a business intelligence framework. 

Relevant presentations:​

  • Demes, K & Mameni, M. 2019. Linking data across university silos to support data-driven research development strategies. BCNET Shared IT Services for Higher Education and Research. [link]

  • Locher, J, E Barsky, and KW Demes. 2018. Connecting the Data Dots to Identify Research Expertise in Large Universities. BCNET Shared IT Services for Higher Education and Research. [link]

 

Examples of former projects include:

  • Identification of funding programs where institutions are under-performing to guide support allocation

  • Developing metrics to inform and support assertions in grant proposals

  • Developing models to identify competitive award candidates

  • Assessing trends in collaboration to guide development of interdisciplinary research teams