Data Curation with Autonomous Data Collection: A Study on Research Guides at Korea University Library

Data Curation with Autonomous Data Collection: A Study on Research Guides at Korea University Library

As the format and medium of research information diversifies with the development ofscholarly communication channels, research information is generated and distributed more frequently via manifold media. While traditional library services focused primarily on offline information, there is an increasing demand from the research community to create more organized digital channels for accessing information. Libraries must comprehensively collect information from various sources, including online media, and selectively curate relevant research information from amidst a mass of data. Some libraries have provided online subject guides to deal with online media and to provide subject-specific research information. These guides are gateways and tools for resource discovery, with well-organized categorization and classification of various sources of information (Bawden & Robinson, 2002). However, many of them are mere collections of hyperlinks to other web pages, and lack in-depth and detailed information or content. Others provide more detailed and organized information, but they seldom update their information because the constant collection and classification of information requires a huge amount of time and resources. One of the major challenges to effectively providing relevant research information lies in In this paper, we propose and describe a research guide system that automatically collects information from various sources and distributes it via subject-specific online research guides, thereby enabling efficient and continuous provision of up-to-date information. collecting and selecting information in a sustainable manner. Another challenge is how to present collected information in a way that maximizes its accessibility.