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. Content and grouping: 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.

Other related information about CS project descriptions and data source websites can be found in the following: https://doi.org/10.5281/zenodo.7310096 and https://doi.org/10.5281/zenodo.7310295 .