Mapping Sustainable Development Goals to Citizen Science projects - Datasets

This work presents opportunities, achievements, and future challenges in using computational analytics to better understand the connection between CS and the SDGs. The work in its status does not fully cover SDGs in CS, but it evaluates and shows the potential of the text-classification techniques for identifying SDGs in CS project descriptions and for assessing trends in connection of CS and SDGs based on available data. A total of 56 websites have been used to extract randomly 208 project descriptions from the CS Track database collected during 2019-2022. <strong>Content and grouping: </strong> Compiled list of keywords for SDG mapping. Spreadsheet containing training data from SciStarter (set of projects associated with SDGs) Spreadsheet containing the list of projects associated with SDGs in relation to the different automatic classifiers (nCoder, ESA and OSDG) and manual coding. Presentation in CS Track ECSA event (8th October 2022, Berlin): CS-Track database: a central database of CS projects in Europe that can be key to understand the connection of CS and SDGs “Understanding the nature of Citizen Science in a rapidly changing world” The associated full report resulting from this study is in progress. Please contact the corresponding authors for further information.本研究探讨了利用计算分析手段深入理解公民科学（Citizen Science，CS）与可持续发展目标（Sustainable Development Goals，SDGs）之间关联的机遇、既有成果与未来挑战。当前研究尚未完全覆盖公民科学领域的可持续发展目标相关议题，但本研究评估并验证了文本分类技术在识别公民科学项目描述中的可持续发展目标，以及基于现有数据评估公民科学与可持续发展目标关联趋势方面的应用潜力。 本研究共从2019-2022年收集的CS Track数据库中，通过56个来源网站随机提取了208条项目描述。 **内容与分组：** 1. 用于可持续发展目标映射的关键词汇编列表； 2. 包含来自SciStarter的训练数据的电子表格（该数据集为与可持续发展目标相关的项目集合）； 3. 包含与不同自动分类器（nCoder、ESA及OSDG）和人工编码相关的可持续发展目标关联项目列表的电子表格； 4. 2022年10月8日于柏林举办的CS Track ECSA活动中展示的相关内容：CS Track数据库——欧洲公民科学项目的中央数据库，是理解公民科学与可持续发展目标关联的核心资源； 5. 题为《在快速变化的世界中理解公民科学的本质》的相关主题，本研究衍生的完整报告尚在编制中，如需获取进一步信息，请联系通讯作者。