4.6 Article

A Quantitative Framework to Inform Cloud Data System Architecture and Services Requirements Based on User Needs and Expected Demand

期刊

IEEE ACCESS
卷 8, 期 -, 页码 138088-138101

出版社

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/ACCESS.2020.3012054

关键词

Earth; geographic information systems; geospatial analysis; lakes; market research; oceans; requirements engineering; rivers; sea surface; technical requirements; system of systems

资金

  1. Jet Propulsion Laboratory, California Institute of Technology
  2. National Aeronautics and Space Administration (NASA) [80NM0018D0004]

向作者/读者索取更多资源

The NASA open data policy and the increases in data volume from recent and future missions have resulted in a need to re-evaluate data archive information systems and services. For example, the Surface Water Ocean Topography mission (SWOT) will produce similar to 15 TB of data every day that needs to be freely and openly accessible through the NASA Physical Oceanography Distribute Active Archive Center (PO.DAAC). Because of the computational, and distribution challenges associated with making such volumes of Earth Observation data publicly available, the NASA Earth Science Data Information System (ESDIS) is moving their archive systems, like PO.DAAC, to the cloud. To facilitate this migration, system requirements need to accommodate expected use. As such, the objective of this study was to assesses expected user needs and develop a quantitative framework that can be traced to requirements for the cloud-based data archive system architecture and services that enable data discovery, access and utility. We used a two-tier data gathering method that included a short survey of potential users (identified at professional meetings and community listservs) and in-depth interviews. The survey provided a means for scaling findings from the in-depth interviews to a more representative sample, thus enabling assessment of expected impact to various user communities for different services that could be provided. This framework enables traceability for setting priorities for data services development to requirements for a cloud-based data archive system and services that enable data discovery, access and utility.

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