Reengineering observatory operations for the time domain

Abstract

Observatories are complex scientific and technical institutions serving diverse users and purposes. Their telescopes, instruments, software, and human resources engage in interwoven workflows over a broad range of timescales. These workflows have been tuned to be responsive to concepts of observatory operations that were applicable when various assets were commissioned, years or decades in the past. The astronomical community is entering an era of rapid change increasingly characterized by large time domain surveys, robotic telescopes and automated infrastructures, and -most significantly -of operating modes and scientific consortia that span our individual facilities, joining them into complex network entities.Observatories must adapt and numerous initiatives are in progress that focus on redesigning individual components out of the astronomical toolkit. New instrumentation is both more capable and more complex than ever, and even simple instruments may have powerful observation scripting capabilities. Remote and queue observing modes are now widespread. Data archives are becoming ubiquitous. Virtual observatory standards and protocols and astroinformatics data-mining techniques layered on these are areas of active development. Indeed, new large-aperture ground-based telescopes may be as expensive as space missions and have similarly formal project management processes and large data management requirements.This piecewise approach is not enough. Whatever challenges of funding or politics facing the national and international astronomical communities it will be more efficient -scientifically as well as in the usual figures of merit of cost, schedule, performance, and risks -to explicitly address the systems engineering of the astronomical community as a whole.

The Virtual Astronomical Observatory: Re-engineering access to astronomical data

“…• An increasing expectation that new telescopes and facilities incorporate VO capabilities during the design of their data management systems (e.g., Mahabal et al, 2011;Graham et al, 2012;Juric et al, 2013;Anderson et al, 2013;Seaman et al, 2014).…”