Engineering topics

Roelofs, Larry

Publications and source records attributed to Roelofs, Larry.

3 records

NASA NTRS2002

Conceptual Study of Intelligent Data Archives of the Future

A conceptual architecture study is under way to address the problem of getting the most scientific value from the large volumes of Earth and space science data that NASA expects to accumulate in the future. This involves efficient storage and access, but goes beyond that to facilitate intelligent data understanding and utilization through modeling realistic virtual entities with predictive capabilities. The objective of the study is to formulate ideas and concepts and to provide recommendations that lead to prototyping and implementation in the period from 2010 to 2020. The approach consists of the definition of future scenarios and needs for data usage in applications (in consultation with scientific and applications users), projection of advances in technologies, and an abstraction of an intelligent archive architecture. Strategic evolution is considered in various areas such as storage, data, information and knowledge management, data ingest and mining, user interfaces, and advances in intelligent data understanding algorithms.

Ramapriyan, H. K.↗

NASA NTRS1988

Automated cataloging and characterization of space-derived data

One of the most significant technical issues that NASA must address and resolve is the problem of managing the enormous amounts of scientific and engineering data that will be generated by the next generation of remote sensing systems such as the Hubble Space Telescope (HST) and the Earth Observing System (EOS). The amount of data these sensors are expected to produce will be orders of magnitude greater than NASA has ever experienced. Consequently new solutions must be developed for managing, accessing, and automatically inputting the data into a database in some expressive fashion that will provide a meaningful understanding and effective utilization of this data in a multidisciplinary environment. Presently, scientific data provided by satellites and other sources are processed, cataloged, and archived according to narrow mission or project-specific requirements with little regard to the semantics of the overall research. Scientists therefore lack knowledge of or access to potentially valuable data outside their own field. What is needed is an innovative approach that will allow collected data to be automatically cataloged, characterized, and managed in a domain-community. A concept and design approach that employs expert system-based knowledge controllers combined with advanced spatial database systems and graphical data structures is discussed.

Campbell, William J.↗

NASA NTRS1988

Automated cataloging and characterization of space-derived data

One of the most significant technical issues that NASA must address and resolve is the problem of managing the enormous amounts of scientific and engineering data that will be generated by the next generation of remote sensing systems such as the Hubble Space Telescope (HST) and the Earth Observing System (EOS). The amount of data these sensors are expected to produce will be orders of magnitude greater than NASA has ever experienced. Consequently, new solutions must be developed for managing, accessing, and automatically inputting the data into a database in some expressive fashion that will provide a meaningful understanding and effective utilization of this data in a multidisciplinary environment. Presently, scientific data provided by satellites and other sources are processed, cataloged, and archived according to narrow mission or project-specific requirements with little regard to the semantics of the overall research. Scientists therefore lack knowledge of or access to potentially valuable data outside their own field. What is needed is an innovative approach that will allow collected data to be automatically cataloged, characterized, and managed in a domain-community. A concept and design approach that employs expert system-based knowledge controllers combined with advanced spatial database systems and graphical data structures is discussed.

Campbell, William J.↗