This paper presents the results of a qualitative study that involved students of an interdisciplinary PhD program. The study objective was to gather requirements to create a knowledge graph information system. The purpose of this study was to determine information-seeking practices and information needs of this community, to inform the functionalities of a proposed system, intended to help students with relevant resource discovery and decision-making.,The study design included semi-structured interviews with eight members of the community, followed by a website usability study with the same student participants.,Two main information-seeking styles are recognized and reported through user personas of international and domestic (USA) students. The findings show that the useful information resides within the community and not so much on the program website. Students rely on peer communication, although they report lack of opportunities to connect. Students’ information needs and information seeking are dependent on their progress through the program, as well as their motivation and the projected timeline.,Considering the current information needs and practices, a knowledge graph hosting both information on social networks and the knowledge produced by the activities of the community members would be useful. By recording data on their activities (for example, collaboration with professors and coursework), students would reveal further useful system functionalities and facilitate transfer of tacit knowledge.,Aside from the practical value of this research that is directly influencing the design of a system, it contributes to the body of knowledge on interdisciplinary PhD programs.

中文翻译：

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用户驱动的知识图信息系统的创建工作

本文介绍了一项涉及跨学科博士课程学生的定性研究结果。研究目的是收集创建知识图信息系统的要求。这项研究的目的是确定该社区的信息寻求实践和信息需求，告知所提议系统的功能，以帮助学生进行相关的资源发现和决策。研究设计包括半结构化访谈社区中有八名成员，然后是与同一位学生参与者进行的网站可用性研究。通过国际和国内（美国）学生的用户角色，识别和报告了两种主要的信息搜索方式。调查结果表明，有用的信息位于社区内部，而在计划网站上则没有那么多。学生们依靠同伴交流，尽管他们报告说缺乏交流的机会。学生的信息需求和信息寻求取决于课程的进度，动机和计划的时间表。考虑到当前的信息需求和实践，一个知识图将托管社交网络上的信息以及由网络生成的知识。社区成员的活动将是有益的。通过记录有关其活动的数据（例如，与教授的合作和课程工作），学生将发现更多有用的系统功能并促进隐性知识的转移。