The application of the SequenceL language to complicated database applications

There is an ongoing discussion at the highest levels of the government concerning data morgues. The concern has to do with the current hardware capabilities that permit the acquisition and storage of vast amounts of data and the inability of scientists armed with current software technology to process and analyze the data. The current problem actually demonstrates that advances in computer software have not kept pace with advances in computer hardware. If corresponding software advances can be made, the data may be found to be comatose, rather than dead. Among other root problems, the comatose data is symptomatic of the fact that currently available software technology is not based upon abstractions that appropriately simplify approaches to complex problems and data sets. In order to analyze the large data sets containing, e.g., telemetry data, exploratory or data mining programs must be written. When written in traditional computer languages, these programs require scientists to work with computer specialists and, therefore, require much time to deploy. Higher level languages could well support this activity, particularly languages providing abstractions that scientists could employ without the assistance of specialists. If more exploratory programs can be written in a reduced amount of time, more of the comatose data can be analyzed. Furthermore, new abstractions may provide new points of view. The differing points of view may lead to new insights into how the data can be best analyzed. At the root of any technical solution to the comatose data problem will be a computer language. The higher the level of the root language, the faster the technical solutions will be found. This research effort is focused on computer language improvement