Sharing Data to Improve R&D Outcomes

2:00 PM - 3:20 PM

Balcony A


Abstract:
Sharing data and samples accelerates research and development outcomes. This session will discuss current data sharing practices, limitations, and strategies to maximize output. Case studies will include discussions around data sharing in the health, space, and other sectors.

Presentations:

Rebecca Dikow,

Smithsonian Institution:

will discuss biodiversity genomics and museum collections data.


[presenter materials]

Robert Hanisch,

NIST:

will discuss data repositories, and lessons learned from U.S. Virtual Astronomical Observatory & Materials Genome Initiative


[presenter materials]

Dina Paltoo,

NIH:

will discuss approaches to providing biomedical data, limitations, participant privacy, and lessons learned


[presenter materials]

Discussion Questions:

  • The FAIR (Findable, Accessible, Interoperable, and Reusable) initiative is pre-eminent in data sharing discussions.  How important and how feasible is it to make all shared data FAIR?
  • Funding is required for sustainment functions such as the maintenance of repositories, access protocols, and data curation.  To what extent have organizations committed to provide such funding? How can the situation be improved?
  • In planning for the future, what infrastructure capabilities/ functionalities should be in place?  To what extent should there be broader participation in developing repositories?  Where are the viable places for storing data?
  • What is the value of success stories in establishing and sustaining an infrastructure for data management?  What are some other important considerations?
  • How do you measure the success of data policy and data infrastructure?  Quantitatively?  Qualitatively?  Are numerical scores for FAIRness useful?