2019/07/25 by Joan Najita, Najita, Joan R.
Decision Sciences · Medicine · #Astrophysics of Galaxies (astro-ph.GA) #Cosmology and Nongalactic Astrophysics (astro-ph.CO) #FOS: Physical sciences #Health and Medical Research Impacts #Instrumentation and Methods for Astrophysics (astro-ph.IM) #Scientific Computing and Data Management #Solar and Stellar Astrophysics (astro-ph.SR) #scientometrics and bibliometrics research
paper · pdf · doi:10.48550/arxiv.1907.11700
openalex publication_date 2019/07/25 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
How should we invest our available resources to best sustain astronomy's track record of discovery, established over the past few decades? Two strong hints come from (1) our history of astronomical discoveries and (2) literature citation patterns that reveal how discovery and development activities in science are strong functions of team size. These argue that progress in astronomy hinges on support for a diversity of research efforts in terms of team size, research tools and platforms, and investment strategies that encourage risk taking. These ideas also encourage us to examine the implications of the trend toward "big team science" and "survey science" in astronomy over the past few decades, and to reconsider the common assumption that progress in astronomy always means "trading up" to bigger apertures and facilities. Instead, the considerations above argue that we need a balanced set of investments in small- to large-scale initiatives and team sizes both large and small. Large teams tend to develop existing ideas, whereas small teams are more likely to fuel the future with disruptive discoveries. While large facilities are the "value" investments that are guaranteed to produce discoveries, smaller facilities are the "growth stocks" that are likely to deliver the biggest science bang per buck, sometimes with outsize returns. One way to foster the risk taking that fuels discovery is to increase observing opportunity, i.e., create more observing nights and facilitate the exploration of science-ready data.