The Cognitive Enhancement Process of Scientific Data Retrieval
Jianping Liu, Jian Wang, Guomin Zhou, Guilan Zhang, Yunpeng Cui, Juan Liu · Proceedings of the 3rd International Conference on Computer Science and Application Engineering · 2019
Is there a stable cognitive structure of scientific data retrieval process? Based on the theory and method of user relevance research, this study explores the cognitive characteristics of user scientific data query and retrieval. The semi-structured interview method used to collect relevant data, and the content analysis method used to encode and analyze the cognitive process of users' scientific data query and retrieval. The results show that (1) users scientific data relevance judgment not only depend on topicality, but also use accessibility, quality, authority and usefulness. (2) There are 7 combination patterns for the use of user's scientific data relevance criteria, and (3) different patterns correspond to different user relevance types and different user information need states. These 7 criteria usage patterns reveal the cognitive enhancement of user scientific data relevance judgment. The research results have a great inspiration for the development of interactive scientific data retrieval system based on user cognitive enhancement characteristics.