图书情报知识 ›› 2018, Vol. 0 ›› Issue (4): 102-108.doi: 10.13366/j.dik.2018.04.102

• 知识、学习与管理 • 上一篇    下一篇

科研数据实践的实证研究对数据管理和共享的重要意义:个案回顾、反思与前瞻

沈怡   

  • 出版日期:2018-07-10 发布日期:2018-07-10

The Empirical Research of Scientific Data Practices and Its Importance to the Development of Data Management and Sharing Systems: Study Reviews, Reflections, and Prospects

  • Online:2018-07-10 Published:2018-07-10

摘要:

科研数据实践与信息行为是建立有效的数据管理、分享与发掘机制和系统的实证基础和人文根据。新兴的多种学科和跨学科创新领域尤其需要开放流畅的数据分享、信息交流和知识融合才能有效地解决全球重大挑战性问题。其中,科研学者的学术交流模式和数据实践行为起着决定性的作用。本文所列举和回顾的实证研究案例,结合定量和定性的研究方法对多个学科领域和从事跨学科领域的科研学者分别进行广泛问卷调查、个体深入采访和群体科研讨论组的调研。这些实证研究以优化数据管理系统和机制为目的,为提高新一代数据图书馆和数据管理中心的功能优势和使用绩效,并为推进学术开放存取、开放数据和知识共享提供实践依据和执行策略。通过回顾和反思研究实例,旨在展望科研数据实践研究的发展前景和强调数据管理系统的人文优势。

关键词: 科研数据, 数据实践, 数据管理, 用户信息行为, 数据知识库, 开放数据, 数据再利用

Abstract:

The study of scientific data practices provides an empirical foundation and humanistic considerations for developing effective data management, sharing, and discovery systems. Today, transformative and disruptive multidisciplinary and transdisciplinary research especially requires open and fluent data sharing, information exchange, and knowledge discovery mechanisms to address grand research challenges. To this end, it is important to investigate scientists’ scholarly communication dynamics and data information behaviors to drive humancentered design and development of data infrastructure and curation services. This paper describes three examples of empirical research on scholarly data practices and discusses their pragmatic implications for library services and infrastructure development. These examples employed a mixedmethods approach to explore domain and crossdomain scientists’ data management, sharing, discovery, use, reuse, and preservation practices. The research methods range from data landscape survey, interpersonal interviews, to focus group discussion. The results inform data repository optimization and promote open data movement through empirical evidence and practical strategies. By way of reviewing and reflecting on the study cases, this paper aims to project the future landscape of data practice research and emphasizes the significance of humanistic considerations in the design of data management systems.

Key words: Scientific data, Data practice, Data management, User information behaviors, Data repository systems; , Open data, Data reuse