IDACT: Automating Scientific Knowledge Discovery

B. Hay and K.L. Nance (USA)

Keywords

: Automation and Information Technologies, Data Discovery, Data Transformation, XML, XSLT.

Abstract

: Current scientific research often requires the use of increasing volumes of data, much of which is held in geographically diverse, heterogeneous archives. In order to fully utilize these valuable reserves, researchers are often required to become, or at least to employ, data experts capable of interacting with a variety of data storage systems, ranging from basic directory structure and FTP sites, to complex database systems, each of which has its own access mechanisms. However, data acquisition is only part of the problem, as it is common to find that the native storage format and the format required by models and analysis tools are incompatible, requiring more effort on the part of the researcher to find and apply a suitable conversion. The IDACT system addresses these issues by providing automated tools that guide the user through the process of locating, acquiring, and converting data, allowing them to leverage work done by others, and learning from new techniques that may be supplied by the user. One of the core IDACT components, the Data Transformation Manager, focuses on the task of data format conversion, allowing data consumers to easily utilize data in the format that is most suitable to their needs.

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