Transactions of the Materials Research Society of Japan 29 [1] 293-296 (2004) Multi-dimensional data management by virtual sample library written in object-oriented script language Ruby Shin-ichi Todoroki * and Satoru Inoue Advanced Materials Laboratory, National Institute for Material Science 1-1 Namiki, Tsukuba, Ibaraki 305-0044, Japan Fax: 81-29-854-9060, e-mail: TODOROKI.Shin-ichi at nims.go.jp Virtual sample library (VSL) is developed for accessing multi-dimensional data acquired from several measurements on a single combinatorial sample library. Management of such data is generally very hard because each data is stored independently in various format. The data is structuralized and standardized by VSL, which has a hierarchy structure whose top layer has the same geometry of the combinatorial sample library. Each data is stored into the VSL systematically according to their coordinates in the library, the name of the measurements, and the dimension of the data. Thus, VSL can provide any data for analysis and visualization by specifying their identifying information. An actual example is demonstrated for the case of one-dimensional combinatorial glass sample li- brary. Some tellurite glass libraries containing Er and F are annealed in a temperature-gradient fur- nace and the decay curves of 1.5μm-fluorescence of Er 3+ are recorded along the libraries in order to find annealing conditions for precipitation of Er-containing fluoride crystals. Their fluorescence spec- tra, fluorescence lifetime, state of precipitates as a function of annealing conditions (7-dimensional data) are plotted in two figures through VSL. Key words: multi-dimensional data, virtual sample library, object-oriented, informatics 1. INTRODUCTION Combinatorial technology brings about significant ad- vantages to our research activities provided we can af- ford to analyze large amount of data obtained. When we are to make several kinds of measurements on one combinatorially-integrated sample library, the obtained data become multi-dimensional and quite hard to deal with by ordinary spreadsheet programs. For example, suppose that we have a 2-dimensional(2D) sample array on which three kinds of measurements are performed, and each measurement gives us data in scalar, 2D, and 3D for- mat per pixel, respectively. This situation is illustrated in Fig. 1. Then we obtain 3D, 4D and 5D data from these measurements. Since the coordinates in the sample array are temporary parameters for us, they should be converted to appropriate physical quantities (e.g. composition, annealing temper- ature, etc...) according to the fabrication condition of the sample library. Moreover, when we need to see the cor- relation between these measurements, we have to merge and re-compile the whole data so that the individual data measured at the same pixel are related. These time-consuming editing jobs would be reduced if we could treat the whole data in one format, in which each data is linked with the corresponding coordinate and physical quantity. This paper demonstrates that such a multi-dimensional data management is possible through “virtual sample library”(VSL), which is a data medium used in software programs for analysis and/or visualiza- tion. ??? Position (x, y) 2.19 Sample library Measurement A Measurement B Measurement C fA(x, y) fB(x, y, λ) fC(x, y, λ, t) λ λ t Fig. 1: Illustration showing a situation of treating multi- dimensional data obtained from several measurements on a combinatorially-integrated sample library (see text). 2. WORKING HYPOTHESIS First of all, let us discuss what kind of format is fea- sible for us to store the whole multi-dimensional data and access any of them easily. Considering the coordi- nates in the library are common information among the data obtained from each measurement, it is reasonable to store the data under the individual coordinates hierarchi- cally. After specifying an arbitrary position in the library, we naturally notice what kind of measurements are per- formed there or what is the fabrication condition there. Finally, we can access data for the specified measurement or fabrication condition. One example of this hierarchy structure is visualized 293