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  1. Large scientific facilities are unique and complex infrastructures that have become fundamental instruments for enabling high quality, world-leading research to tackle scientific problems at unprecedented scales. Cyberinfrastructure (CI) is an essential component of these facilities, providing the user community with access to data, data products, and services with the potential to transform data into knowledge. However, the timely evolution of the CI available at large facilities is challenging and can result in science communities requirements not being fully satisfied. Furthermore, integrating CI across multiple facilities as part of a scientific workflow is hard, resulting in data silos. In this paper,more »we explore how science gateways can provide improved user experiences and services that may not be offered at large facility datacenters. Using a science gateway supported by the Science Gateway Community Institute, which provides subscription-based delivery of streamed data and data products from the NSF Ocean Observatories Initiative (OOI), we propose a system that enables streaming-based capabilities and workflows using data from large facilities, such as the OOI, in a scalable manner. We leverage data infrastructure building blocks, such as the Virtual Data Collaboratory, which provides data and comput- ing capabilities in the continuum to efficiently and collaboratively integrate multiple data-centric CIs, build data-driven workflows, and connect large facilities data sources with NSF-funded CI, such as XSEDE. We also introduce architectural solutions for running these workflows using dynamically provisioned federated CI.« less
  2. Given the highly empirical nature of research in cloud computing, networked systems, and related fields, testbeds play an important role in the research ecosystem. In this paper, we cover one such facility, CloudLab, which supports systems research by providing raw access to programmable hardware, enabling research at large scales, and creating as hared platform for repeatable research.We present our experiences designing CloudLab and operating it for four years, serving nearly 4,000 users who have run over 79,000 experiments on 2,250 servers, switches, and other pieces of datacenter equipment. From this experience,we draw lessons organized around two themes. The first setmore »comes from analysis of data regarding the use of CloudLab:how users interact with it, what they use it for, and the implications for facility design and operation. Our second set of lessons comes from looking at the ways that algorithms used“under the hood,” such as resource allocation, have important—and sometimes unexpected—effects on user experience and behavior. These lessons can be of value to the designers and operators of IaaS facilities in general, systems testbeds in particular, and users who have a stake in understanding how these systems are built.« less