DataHub: knowledge-based science data management for exploratory data analysis

Thomas H. Handley Jr.; Mark R. Rubin; Y. Philip Li

doi:10.1117/12.161564

15 November 1993 DataHub: knowledge-based science data management for exploratory data analysis

Thomas H. Handley Jr., Mark R. Rubin, Y. Philip Li

Proceedings Volume 1938, Recent Advances in Sensors, Radiometric Calibration, and Processing of Remotely Sensed Data; (1993) https://doi.org/10.1117/12.161564
Event: Optical Engineering and Photonics in Aerospace Sensing, 1993, Orlando, FL, United States

Abstract

It is our belief that new modes of research and new tools are required to handle the massive amount of diverse data that is to be stored, organized, accessed, distributed, visualized, and analyzed in this decade. The fundamental innovation required is the integration of three automation technologies: viz. knowledge-based expert systems, science visualization and science data management. This integration is based on a concept called the DataHub. In order to prove the concept, a series of software prototypes are being implemented. On the basis of used comments DataHub is continually changing. The current changes in philosophy and design are described here, including two major changes made to the Motif/X Windows DataHub interface. Additionally, because of the drawbacks of the current implementation in label or file recognition, an expert system is being investigated. Finally, short and long term design and implementation issues are discussed.

Citation Download Citation

Thomas H. Handley Jr., Mark R. Rubin, and Y. Philip Li "DataHub: knowledge-based science data management for exploratory data analysis", Proc. SPIE 1938, Recent Advances in Sensors, Radiometric Calibration, and Processing of Remotely Sensed Data, (15 November 1993); https://doi.org/10.1117/12.161564

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