摘要
[目的/意义]数据质量是Altmetrics当前面临的严峻问题之一,为进一步推进Altmetrics的理论发展与实际应用,需要对数据质量问题进行深入分析。[研究设计/方法]对Altmetrics数据的生命周期进行剖析,刻画数据从新生到投入应用的整个流程。从数据产生、数据收集和数据聚合三个环节,以动态视角分析数据质量问题及影响因素。[结论/发现]在数据产生阶段,用户的主观意愿可能造成数据质量问题;在数据收集阶段,Altmetrics来源平台的元数据准确性缺乏保障,而不同平台的文献识别方法也会影响数据质量;在数据聚合阶段,聚合器的目标定位和技术能力存在差异,数据的整合清洗方式不透明,所提供的数据缺乏质量保障。[创新/价值]从生命周期的视角梳理Altmetrics的数据质量问题,以期将来能够在科研工作中更加合理准确地使用Altmetrics数据。
[Purpose/Significance]Data quality has been one of the serious problems of Altmetrics. In order to promote the theoretical development and practical application of Altmetrics, a thorough analysis on this problem needs to be conducted.[Design/Methodology]This study decomposed the life cycle of Altmetrics data, including data generation, data collection and data aggregation. Issues and impact factors of data quality have been analyzed from a dynamic perspective.[Findings/Conclusion]In the stage of data generation, users' subjective wishes may cause data quality problems; In the stage of data collection, the accuracy of metadata from source platforms is not guaranteed, and different platforms may adopt different methods of document recognition, which could also affect the data quality; In the data aggregation stage, due to different targets and technical capabilities of various aggregators, the way of data integration and data cleaning is not clear, which also results in a lack of quality assurance.[Originality/Value]This study illustrates the issue of Altmetrics data quality from the perspective of life cycle, which could provide an application of Altmetrics data in a more reasonable and accurate way in the future.
引文
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