A confluence of technologies is leading towards revolutionary new interactions between robust data sets, state-of-the-art models and simulations, high-data-rate sensors, and high-performance computing. Data and data systems are central to these new developments in various forms of eScience or grid systems. Space science missions are developing multi-spacecraft, distributed, communications- and computation-intensive, adaptive mission architectures that will further add to the data avalanche. Fortunately, Knowledge Discovery in Database (KDD) tools are rapidly expanding to meet the need for more efficient information extraction and knowledge generation in this data-intensive environment. Concurrently, scientific data management is being augmented by content-based metadata and semantic services. Archiving, eScience and KDD all require a solid foundation in interoperability and systems architecture. These concepts are illustrated through examples of space science data preservation, archiving, and access, including application of the ISO-standard Open Archive Information System (OAIS) architecture.
Eastman TE, Borne KD, Green JL, Grayzeck EJ, McGuire RE, Sawyer DM. eScience and archiving for space science. Data Science Journal. 2006;4:67–76. DOI: http://doi.org/10.2481/dsj.4.67
Eastman, T. E., Borne, K. D., Green, J. L., Grayzeck, E. J., McGuire, R. E., & Sawyer, D. M. (2006). eScience and archiving for space science. Data Science Journal, 4, 67–76. DOI: http://doi.org/10.2481/dsj.4.67
Eastman, Timothy E, Kirk D Borne, James L Green, Edwin J Grayzeck, Robert E McGuire, and Donald M Sawyer. 2006. eScience and archiving for space science 4: 67–76. DOI: http://doi.org/10.2481/dsj.4.67