Future Directions for Data Compilations

Abstract

As the world's supply of thermophysical property data that emerges from the laboratory increases, users of data become more dependent on evaluated compilations. However, the cost of producing and maintaining such compilations by traditional methods is becoming prohibitively expensive. The traditional compiler searches the literature, extracts, evaluates, and analyzes pertinent data and gathers it into a document or electronic database that reflects the state of knowledge of a particular subject at a particular time. Because clef the inherent time lag, it never catches up to the current state. The attempt to catch up requires that the whole procedure be repeated at intervals, with greater cost for each cycle. A more cost-effective procedure, called dynamic compilation is described. Here the user produces a compilation to-order at the time of need. It uses a suitable archive of experimental data maintained up-to-date, an automated procedure for extracting and selecting the best pertinent data, and procedures for fitting the pieces to suitable models that furnishes parameters for internally consistent data sets. With proper design of components this procedure is more economical than and superior to the traditional static compilations.