Commitment to Diversity, Equity, and Inclusion
As the NSF’s preeminent US national center for ground-based, nighttime optical and infrared astronomy, adhering to the principles of diversity, equity, inclusion and the practice of ethical science are part of how NOIRLab conducts all of its business. The NOIRLab Mission supports these principles and practices. Diversity, Equity, Inclusion and ethical scientific practice are the foundations of the NOIRLab Mission to support community access to telescopes and astronomical data.
NOIRLab’s Time Allocation Committee Process
The Time Allocation Committee (TAC) process is a core function of NOIRLab and is used to allocate time on both NOIRLab and privately operated telescopes. As part of our TAC modernization, we will be moving to a 2-stage review process, beginning as soon as the 2022B semester.
After an internal review covering 17 semesters of proposals, it was determined that for all but 4 of those semesters, female principal investigators (PIs) had a lower than expected acceptance rate. After examining best practices of other institutions, balanced against the particular needs of NOIRLab, including support for thesis datasets and provision of access to researchers at small and underserved institutions, a 2-stage process was developed. The first stage includes a review of anonymized proposals and the second stage, after a proposal team reveal, allows for ranking adjustments that support NOIRLab mission priorities.
Read more about this process in The NOIRLab Mirror article “TAC Modernization” (begins on page 40)
Rubin’s Data Preview delegate selection process
Leading up to operations, Rubin Observatory is planning for three data previews. The first of these, Data Preview 0 (DP0), supported a limited number of accounts in the Rubin Science Platform for scientists and students. As a result, the applications for those accounts were oversubscribed. Instead of allocating those accounts via a competitive proposal process, research inclusion was used as the sole factor in determining DP0 participants. An algorithm was used to choose a diverse set of delegates characterizing a range of under-represented identities in astronomy as well as a variety of career stages and science interests.