图书馆视角下科学数据管理人才培养模式研究

Research on Models of Scientific Data Management Talents Cultivation from the Perspective of Library

在对国外科学数据管理人才培养实践进行调查分析的基础上,参考科学数据生命周期模型,可将科学数据管理人才分为科研嵌入与咨询人才、数据净化人才、数据挖掘人才、数据开放人才和数据科学家5大类。科学数据管理人才的职业素质要求应从基本素养、知识结构、智能结构3个方面进行提升。我国图书馆科学数据管理人才的培养模式应从以下方面考虑:确定科学数据管理人才培养的指导思想,形成多类型、多层次的科学数据管理人才培养体系;明确科学数据管理人才的培养目标,完善数据管理专业教育课程体系;实行多种形式的培养体制。

Based on scientific data lifecycle model, with investigation and analysis on the cultivation of scientific data management specialists in foreign countries, scientific data management talents can be classified into five categories： research embedding and consulting talents, data purification talents, data mining talents, data openness talents and data scientists. Professional skills require of scientific data management talents should be improved from three aspects： basic quality, knowledge structure and intellectual structure. Cultivation models for scientific data management talents in China should be contemplated and constructed from the following perspectives： establishing a guiding principal for scientific data management talents cultivation, constructing a system for cultivation of scientific data management talents that is multi-type and multi-layer, articulating cultivation goal for scientific data management talents and further improving curriculum for data management education system, and last but not least implementing diversified cultivation models.