A new initiative funded by the NIH is working to better connect research data between programs to help scientists uncover relationships across studies and make better use of existing research.
The NIH Common Fund Data Ecosystem brings together research resources spanning human genetics, the microbiome and emerging technologies across 18 NIH to make datasets easier to find, connect and analyze.
Understanding a disease or identifying a promising drug target may require scientists to connect genetic information with molecular measurements, tissue data and results from drug-screening experiments. When these resources can be explored together, researchers may be better equipped to understand biological mechanisms, identify meaningful patterns and investigate promising directions for further study.
“Scientific discovery rarely happens in isolation. A finding in one dataset may become much more meaningful when it can be examined alongside evidence from another study or another area of biology,” said Julie Jurgens, associate director of scientific delivery for the Knowledge Portal Network at the Broad Institute of MIT and Harvard and study corresponding author. “Building the connections between these resources can help researchers spend less time navigating fragmented systems and more time asking important scientific questions.”
The team is also evaluating indicators of research engagement and impact, including how often scientists use the ecosystem's online resources and cite related publications. Preliminary findings suggest that related research publications may receive more citations than comparable papers, although additional analysis is needed to understand the significance of those differences. These evaluation efforts are intended to help determine how the ecosystem can remain useful, accessible and valuable to researchers over time.
As artificial intelligence becomes more prominent in scientific research, well-organized and connected datasets could also help computational tools analyze scientific information more effectively.
Data from University of Colorado Anschutz