Baku, June 10, AZERTAC

The UN international conference on statistics of scientific data related to climate has started in Spain, according to the official website of the Food and Agriculture Organization (FAO).

FAO is joining the 8th International Conference on Big Data and Data Science for Official Statistics organized by the Basque Centre for Climate Change, INE Spain and the United Nations Statistics Division in Bilbao, from 10 to 14 June.

As the world grapples with numerous global challenges, including environmental issues, climate change, health crises, food insecurity, economic recovery, and human displacement, the need for knowledge integration has never been more critical. Amid a data landscape with fast-increasing volumes of data, information remains compartmentalised to pre-defined scales and fields, rarely building its way up to collective knowledge. The statistical community, the data science community, the geospatial community and the modelling community are tasked with delivering this integrated knowledge, to shed light on the ongoing “wicked problems”—intertwined, multistakeholder and with potential solutions dependent on subjective, competing interests.

The purpose of the conference is to address and share knowledge on these emerging issues that require the timely and flexible production of integrated scientific, statistical and geospatial information. This involves collaboration with strategic partners from the public and private sectors, as well as from academic and research institutes, and needs a paradigm shift that will favour open synthesis to contribute and reuse knowledge and apply it toward decision making. The conference will consist of a ministerial opening, high-level panels, technical sessions as well as a several workshops. The overall theme of the conference is “Informing Climate Change and Sustainable Development policies with integrated data”.

In today's digital age, ensuring that knowledge is accessible for common use and societal benefit is paramount. This involves making information freely available and shared among individuals, organizations, or society as a whole, with a focus on fostering cross-domain collaboration, innovation, and effective problem-solving. This session underscores the significance of data accessibility and interoperability in realizing the potential of knowledge commons for addressing global sustainability challenges. Presentations will highlight how interoperability standards, coupled with investments in modern data infrastructure, establish the foundation for collaborative data spaces, involving both public and private entities. Furthermore, the session will explore how governance mechanisms and ethical considerations play a crucial role in ensuring responsible data use and co-ownership within knowledge commons. Discussions will extend to examining how the global statistical community can leverage knowledge commons through initiatives like the UN Global Platform for Official Statistics, the UN Data Commons project, and the ARIES for SEEA initiative. The session will culminate in a panel discussion featuring experts sharing their insights on the future trajectory of disseminating integrated information within the context of knowledge commons. More detailed information.

The session will aim to present various initiatives on developing ecosystem extent maps and models for ecosystem services and discuss how these initiatives and tools can be used to support the compilation of SEEA ecosystem accounts and facilitate the reporting under the Kunming-Montreal Global Biodiversity Framework (GBF) of the Convention on Biological Diversity (CBD), through focusing on indicators A.2 “Extent of natural ecosystems” and B.1 “Services provided by ecosystems.” This session will also discuss the importance of interoperability for these initiatives in order to leverage on them, maximize their benefits and develop accounts-ready data to support compilation of SEEA accounts and reporting under the GBF indicators. The session will be organized in three parts: the first one focusing on ecosystem maps, the second one on ecosystem services modelling, and the third one on the interoperability of data, maps and models.