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由于学科的自身特点和统计源的学科结构特点，不同学科期刊具有显著差异。但由于期刊数量庞大，评价指标多种多样，很难从宏观上把握各学科期刊的整体特点，对学科间差异给出科学的判断。本文以SCI期刊为研究对象，用区间数据代表各学科期刊，采用因素区间数据PCA算法探寻反映期刊水平的关键指标，并利用区间数据投影的方式绘制主平面图，反映各学科期刊的整体特点及我国期刊在国际上的地位。“,”Due to different characteristics of disciplines and different structures of databases, journals from different disciplines vary widely in the bibliometric indexes. However, it is difficult to obtain a general overview of the development of each discipline and to explore the differences between different disciplines, since there exists a huge number of journals featured by a variety of indicators. This paper packs Chinese SCI journals from the same discipline into an interval-valued observation, and performs Factor Interval Data Analysis on all the observations to find out the key indicator that accurately describes development condition of journals. The plane of first two factor is then displayed to show the current status of journals from different disciplines. It also helps describe how well Chinese SCI journals perform in the international sphere.