TY - DATA T1 - Reusable Image Analytics Pipelines PY - 2018/04/23 AU - Andrew Connolly AU - Dino Bektesevic AU - Mario Juric AU - Magda Balazinska AU - Alvin Cheung UR - https://figshare.com/articles/journal_contribution/Reusable_Image_Analytics_Pipelines/6171611 DO - 10.6084/m9.figshare.6171611.v1 L4 - https://ndownloader.figshare.com/files/11172971 KW - NSF-SI2-2018 KW - Instrumentation, Techniques, and Astronomical Observations KW - Astrophysics KW - Artificial Intelligence and Image Processing KW - Distributed Computing N2 - The Large Synoptic Survey Telescope (LSST) is an 8-m optical ground-based telescope being built on Cerro Pachón in Chile. LSST will survey half the sky every few nights in six optical bands for ten years (imaging each part of the sky about 1000 times). The pipelines developed for LSST boast state-of-the-art image processing algorithms, many of which were developed specifically for the high throughput data. While developed for a specific surveys these algorithms have the potential for broad uptake in the astronomical community if they can be made easily acessible and usable. We introduce here a scalable framework for the analysis of large imaging surveys, designed to operate as a cloud service, incorporate new or legacy image processing algorithms, and to support and optimize complex analysis workflows. ER -