Elsevier 2023 Sustainable Development Goals (SDGs) Mapping

The United Nations Sustainable Development Goals (SDGs) challenge the global community to build a world where no one is left behind. Since 2018, Elsevier has generated SDG search queries to help researchers and institutions track and demonstrate progress toward the SDG targets. In the past 5 years, these queries, along with the university’s own data and evidence supporting progress and contributions to the particular SDG outside of research-based metrics, are used for the THE Impact Rankings. For 2023, the SDGs use the exact same search query and ML algorithm as the Elsevier 2022 SDG mappings, with only minor modifications to five SDGs, namely SDG 1, 4, 5, 7 and 14. In these cases, the queries were shortened by removing exclusion lists based on journal identifiers. These exclusion lists often contained thousands of items to filter out content in journals that were not core to the SDGs. To replicate the effect of these journal exclusions, sets of keywords were used to closely mimic the effects the journal exclusions had on the SDG content, while greatly reducing the overall query size and complexity. By following this approach, we were able to limit the changes to the publications in each SDG by less than 2 percent for most SDGs, while reducing the query size by 50 percent or more. These shortened queries also have the added benefit of running faster in Scopus, allowing further analysis of the SDG data to be done more easily. For each SDG, the full search query, along with further details about the top keyphrases, subfields, journals and keyphrases are available for download.

联合国可持续发展目标（Sustainable Development Goals, SDGs）呼吁全球社会携手构建一个不让任何人掉队的世界。自2018年起，爱思唯尔（Elsevier）便开发了可持续发展目标搜索查询工具，以助力研究人员与科研机构追踪并展示在可持续发展目标相关指标上的进展。在过去五年间，此类查询工具结合各高校自有数据，以及非基于科研计量的、针对特定可持续发展目标的进展与贡献相关佐证材料，被应用于泰晤士高等教育影响力排名（THE Impact Rankings）。2023年度的版本中，可持续发展目标沿用了爱思唯尔2022年可持续发展目标映射工作所采用的完全一致的搜索查询方案与机器学习算法，仅对5个可持续发展目标（即SDG 1、4、5、7和14）做出小幅调整。具体调整方式为：移除基于期刊标识符的排除列表后缩短查询语句。此类排除列表通常包含数千条条目，用于过滤与对应可持续发展目标核心内容无关的期刊文献。为复刻此类期刊排除操作的筛选效果，研究团队使用关键词集来精准模拟期刊排除对可持续发展目标相关内容的筛选作用，同时大幅缩减了整体查询的规模与复杂度。通过该方法，多数可持续发展目标的收录文献变化幅度均控制在2%以内，同时将查询规模缩减了50%以上。此外，此类缩短后的查询在Scopus（Scopus）数据库中的运行速度更快，使得可持续发展目标相关数据的进一步分析工作更为便捷。针对每一项可持续发展目标，完整搜索查询以及关于核心关键短语、子领域、期刊与关键短语的更多详细信息均可下载获取。