Supplementary materials: "Mapping publications by Sustainable Development Goal at the faculty level to highlight inter-faculty collaborations"

Achieving the United Nations’ Sustainable Development Goals requires partnerships across nations, sectors, and stakeholders. In academia, interdisciplinary research can help to address complex challenges related to the Goals. This paper offers a structured approach to identifying current and potential research collaborations across faculties at a Canadian university.Publications from the Dimensions database that had been assigned to an SDG category were matched against publications indexed by the university’s Research Information Management System. The resulting matches were then sorted and tabulated by ANZSRC research category and by the faculty affiliation of the authors. Potential interdisciplinary research collaborations are then identified by matching authors from different faculties who both have publications within the same research category. Leveraging this methodology and an institution’s RIMS system provides university leaders with insight to track progress and plan research activities across the institution. A simple methodology is presented that combines the power of data processing with the user's contextual insights to uncover novel pairings of faculty members whose research is aligned. Institutions can apply this methodology to track SDG-related publications, to analyze current interdisciplinary publications, and to identify potential interdisciplinary collaborations.<br>

实现联合国可持续发展目标（Sustainable Development Goals，SDGs）需要各国、各行业及各类利益相关方开展协同合作。在学术科研领域，跨学科研究可为应对与可持续发展目标相关的复杂挑战提供助力。本研究提出一套结构化方法，用于识别一所加拿大高校各学院间当前已存在及潜在的研究合作关系。本研究将已归类至可持续发展目标类别的Dimensions数据库文献，与该高校研究信息管理系统（Research Information Management System，RIMS）收录的文献进行匹配比对。随后将匹配得到的文献，按照澳大利亚新西兰标准研究分类（ANZSRC）及作者所属学院进行分类排序与统计制表。通过匹配来自不同学院且在同一研究分类下均有发表成果的作者，即可识别出潜在的跨学科研究合作关系。借助该方法与高校的研究信息管理系统，高校管理者可获得全局性洞察，用以追踪全校科研进展并统筹规划校内各项科研活动。本研究还提出了一套简易方法，将数据处理能力与使用者的场景化洞察相结合，以发掘研究方向契合的学院成员间的全新合作配对。各高校均可应用该方法，实现与可持续发展目标相关文献的追踪、现有跨学科发表成果的分析，以及潜在跨学科合作关系的识别。