DataScience@NIH reflects a shared commitment to fostering discovery through data. Our Institutes and Centers are looking for ways to harness the computational and quantitative sciences to elevate the impact and efficiency of biomedical research.
We learned many lessons about managing large data sets through the first phase of the Big Data to Knowledge (BD2K) program, the NIH cornerstone of data science initiatives. But we have much more to learn and a long road ahead, a journey made all the more challenging by the accelerating pace of data creation.
Obviously, we’ll be learning as we go—just as science always has.
Among the questions we’ll be asking are:
- How should NIH ensure its data sets remain findable, accessible, interoperable and reusable?
- How do we develop a workforce skilled in evaluating and analyzing data sets?
- How do we stimulate innovative analytical strategies?
- And how can we balance public-private partnerships for data sustainability?
I don’t have the answers yet, but I do have a sense of the direction we’re heading.
More importantly, I have several assets to help move the NIH further along the path of data-driven discovery.
First, I have the support of the NIH Institute and Center directors and executive leadership. Through near-weekly meetings, we are planning activities and investments to help maintain the momentum BD2K has generated around data science.
Second, we have broad agreement on our key activities—acquiring, curating, and preserving data sets—so we know where to invest our energies.
Third, we have a host of NIH staff already involved in BD2K initiatives who are ready to help us pivot toward the future. Their experience is invaluable.
We have yet to define specific projects, but over the next few weeks and months I will share some of our thinking. I hope you’ll travel with me and offer your ideas of where we ought to go and the best way to get there.