[Purpose/significance] Under the big data environment, resource aggregation becomes the effective way to meet the needs of users of digital libraries, but the research results of resource aggregation quality evaluation are few. From the perspective of meterage and the semantic study, this paper tries to deep the related theory, also to take effective measures in practice to guide the digital library to enhance the resource aggregation quality.[Method/process] Based on the literature at home and abroad, combined with the characteristics of big data era, from the perspective of meterage and semantic, it uses inductive deduction and system theory method to build the evaluation index system which includes 11 primary indicators and 26 secondary indicators. And then on the basis of the index system, the paper expounds the data collection assessment and indicators measurement.[Result/conclusion] The quality evaluation index of digital library resource aggregation is constructed, and the evaluation index system is explained in detail. The optimization strategy of digital library resource aggregation quality is put forward. The results show that under large data environment, through semantic and meterage method to build the quality evaluation index system of digital library resource aggregation, the theory basis is sufficient, and index system is complete and reasonable. There is certain value of theoretical innovation in the paper.
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