A June ’22 Nature article reveals the tensions between data sharing, the willingness of researchers to share their data, and the actual access to data behind data availability statements. Within the US, it will be interesting to see how the forthcoming NIH policy changes and the OSTP Nelson memo help make data more accessible.
A recent Wired article highlights the issues that come with the rise of the use of machine learning in research and some researchers are worried it’s causing a reproducibility crisis. Like all tools and methods, it’s important to understand how they work and when to use them. And as one researcher in the article calls out – these new methods lend well to collaborative and interdisciplinary opportunities.
In “The Kidney Transplant Algorithm’s Surprising Lessons for Ethical A.I.“, David G. Robinson talks about the real life implications of seemingly neutral technical details, moral humility, and the impact of factoring in public input in designing an algorithm that decides who should receive a kidney.
Read about how researchers in the UW—Madison American Family Insurance Data Science Institute (DSI) and Department of Geography were recently awarded grants from the National Science Foundation (NSF) to advance good data management and open-science practices. The project will implement the FAIR (Findable, Accessible, Interoperable, Reusable) data principles and the CARE (Collective Benefit, Authority to Control, Responsibility and Ethics) principles for Indigenous Data Governance to support equity and access.
Librarians have the perfect skills to help with systematic reviews! Find out how they can help in this article about how a research team at UW-Madison partnered with librarians Barbara Sisolak, Jessica Newman, and Angel Tang to make this process much more manageable.
The U.S. Chief Data Scientist Denice Ross is pushing for agencies to disaggregate their data, which she describes as “the next generation of open data,” in order to lead to more equitable outcomes for Americans.