To share an illustrative example of how such data could be used, Ms. Min invited one of the participating partners of the Crowd4SDG Consortium, Ms. Barbara Pernici, Professor at the Politecnico di Milano (PoliMi). As Crowd4SDG – a research project of the European H2020, came to be in the Spring of 2020, the world got caught itself in the middle of the pandemic, so one of the areas that PoliMi studied is public health, explained Ms. Pernici. The Crowd4SDG tools pursued a combined goal of exploring how tools through automation techniques, i.e. machine learning, and involvement of citizens in this process, could be used for gathering and analyzing data that is fit for use. In the examples that she provided, she explained how social media data, as a way of the passive engagement of citizen scientists in the process, was used for this purpose. The described various tools of the project were developed in the form of applications. For COVID-19 – monitoring the use of face masks and following social distancing by different countries, the VisualCit tool was used that deploys Twitter data–image recognition. Undoubtedly, Ms. Pernici admits that the use of such data did not come without challenges. In the beginning, only 5 images were found useful from the 1000 samples. This is due to different types of data within Twitter that include images, memes, charts, etc. So algorithms were finetuned in terms of image recognition, annotation, and use of keywords with the help of citizen scientists. For validation purposes, the yielded results were compared with the data of other services circling at that period. The project on disaster response - monitoring the floods in Nepal and Thailand, followed also the same structure but faced other challenges related to linguistic aspects of using and recognizing keywords and geolocation. All the work has been documented and made publicly available, concluded Ms. Pernici.

Touching upon the global initiatives, Ms Hayoi Chen, Coordinator of the Inter-Secretariat Working Group on Household Surveys at UNSD, shared that a new initiative – Collaborative on Citizen Data - was launched during one of the sessions of 2023 WDF on citizen-generated data earlier that week. This collaboration aims to bridge the gaps in the official statistics and make the whole data process more inclusive. Following the discussions of the expert group meeting on CSD in November 2022, the aim is to define the framework, the scope of the work, and bring together all the involved stakeholders from the NSOs and broader NSSs and identify joint needs, and collaborate more closely on the said matter.  Ms. Chen, pointing out having a full house in the session, invited 40 participants to attend the session in person to share their case studies and ideas on how this new initiative should operate.