[目的/意义]探讨相关多维动态大数据特征以及在新兴产业技术预测分析中的作用，从而整合多维动态 大数据信息知识，为新兴产业技术预测分析提供框架支持。[方法/过程]首先通过探究分析专利大数据、论文大数 据、奖励大数据以及经济大数据各自的知识特征及优势互补，进而提出多维动态大数据关联模式架构。在此基础 上，通过“人”和“事”的综合分析，量化给定产业技术的新兴指数。[结果/结论]实验结果表明，文章提出的预测分 析框架充分利用了多维动态大数据信息较高的知识密度和广度，能够为新兴产业技术预测提供更为全面的多模 态决策支持。

[Purpose/significance] The paper mainly discusses the characteristics of related multi- dimensional dy? namic big data and its utilizations in the emerging technology prediction. This research helps to integrate multi-dimen? sional dynamic big data and then provide frame support for emerging technology prediction. [Method/process] This pa? per firstly proposes a multi-dimensional dynamic big data association structure by exploring and analyzing the knowl? edge characteristics and complementary advantages of patent big data, paper big data, reward big data and economic big data. On this basis, the emerging index of a given industrial technology is quantified through a comprehensive analy? sis of "people" and "things". [Result/conclusion] The experiment results shows that prediction and analysis frame? work proposed in this paper makes full use of multi-dimensional dynamic big data information, which has high knowl? edge density and breadth, and this can provide more comprehensive multi-modal decision support for emerging tech? nology prediction.