用户视角下农业科学数据描述信息的“结构-效用”研究

Structure-Utility of Descriptive Information of Agricultural Scientific Data from the Perspective of Users

[目的 /意义]研究并提出科学数据描述信息的内容结构与其描述效用的对应关系,为科学数据描述的理论研究提供新的视角,为数字环境下农业科学数据的最优描述提供参考。[方法 /过程]对47名农业领域硕博研究生被试的科学数据搜索与相关性判断行为进行准实验观察。首先,通过半结构化访谈获取被试相关性判断过程中使用的农业科学数据描述项集合及其使用特征;其次,分析高信心水平下用户的描述项使用路径;最后采用多元回归方法分析描述项对判断信心的预测能力。[结果 /结论]研究得到了11类42项农业科学数据描述项,确定了来源、数据内容、使用与评价、数据产生信息是具备高效用的描述项,得到了高效用描述项组合,初步分析了用户数据素养和数据利用目的对描述项效用的影响。研究成果为科学数据元数据等具体的描述实践提供了理论依据。

[Purpose/Significance] This paper aims to study the structure-utility relationship of descriptive information of scientific data to provide a new perspective for the theoretical study of scientific data description and a reference for the best description of agricultural scientific data in the digital environment. [Method/Process] Based on information processing theory, the lens model, the probabilistic mental model theory and the adaptive decision-making behavior framework, the relationship model between descriptive information structure and informing utility was constructed. A situational experiment was designed according to the model. In this study, 47postgraduates from 14 institutes were invited for quasi-experimental observation by using qualitative and quantitative methods such as eye-tracking, semi-structured interview and questionnaire. First, this study used a semi-structured interview to obtain a user’s cognitive interpretation of fixation points and collected the descriptive items of agricultural scientific data and their use frequency by encoding the interview text. Second, this study combined descriptive item usage path coding and user judgment confidence to obtain the combination of descriptive items with high utility. Finally, the study used multiple regression analysis to identify the descriptive items with high utility and their predictive ability, and analyzed the impact of data literacy and data utilization type on the utility of descriptive items.[Results/Conclusions] The study identified 42 descriptive items of 11 categories of agricultural scientific data and their usage characteristics. Among them, the top 5 frequently used descriptive items were subject, data, overall description, source and data production information, which played an important role in user relevance judgment. Then this study identified the combination of descriptive items with high utility and found that users’ use patterns of descriptive items were diverse. Compared with making a judgment with "relevant" result, users often needed less information to achieve a high level of confidence when making an "irrelevant" judgment. This study also found that the descriptive items with high utility include source, data, use and evaluation, and data production information. It is determined that user data literacy and data utilization purpose were the influencing factors of descriptive information utility, and the effects of the two factors were preliminarily analyzed. Based on this research, the paper put forward some suggestions for improving agricultural scientific data metadata and scientific data sharing. In the future, this study will be repeated in groups with different academic backgrounds and data literacy levels, so as to enhance the generalization ability of research conclusions and construct a more effective structure of scientific data descriptive information.