An Integration-Based Conceptual Framework for Scientific Information Analysis

The era of big data brings both opportunities and challenges to scientific information analysis (SIA) and intelligent information services performed at the National Science Library, Chinese Academy of Sciences (NSLC). We are in urgent need of developing a new SIA framework to expedite big data acquisition and processing, and to improve the quality of information services. This paper describes the traditional SIA workflow currently applied at NSLC with a case study. It also reviews progresses on massive heterogeneous data integration, data management and analytics methods, and their applications. We then propose an integration-based conceptual framework for SIA through an examination of the limitations of current workflow. The new framework is characterized with the development of a Knowledge Resources Integration System (KRIS) that can store, organize, process, and visualize heterogeneous data. We explain the functions and characteristics of the proposed framework and strategies to implement a web-based data warehouse system based on it. The paper concludes with a discussion of future research to implement KRIS for SIA.

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