Data should be treated as a first class asset. In fact, for the most part, data are the only output of our work. Data costs enormous amounts of time and money to generate and analyze, and the never go bad. Data can be repurposed for research into other disease areas. And, as we prepare for the lab of the future, data will need to be harmonized and aggregated so that AI algorithms can help with analysis.
However, most organization treat data as a side products that were created to generate reports and academic papers. The source data are put in share folders and often used only once. The source data itself are often fragmented and not harmonized and can never be reused because they are not annotated with standard vocabularies.