Date: 13:15~15:15 (UTC+8), 7th Spet., 2023 Venue: Beijing International Conventional Center, Beijing, China

Science, technology and innovation are important tools to support the realization of  Sustainable Development Goals (SDGs). The cutting-edge digital technology, e.g., big data,  can facilitate multi-dimensional, -disciplinary and -scale monitoring and evaluation of  sustainable development indicators, and help us to fully understand the current challenges  and find appropriate solutions for sustainable development. 

In the context of global warming, the warming rate of the Arctic is three times more than that  of the global average, which profoundly affects global climate change and the process of  sustainable development goals. The sustainable development of the Arctic has always been  one of the core issues of Arctic governance and is closely related to the 2030 Sustainable  Development Goals of the United Nations. In order to strengthen data-, science- and nature-  based approaches in the Arctic region, promote international cooperation by the cross-  integration of multi-disciplinary knowledge for the Arctic sustainable development. For this  reason, the International Research Center of Big Data for Sustainable Development Goals  (CBAS), the University of Chinese Academy of Sciences (UCAS) and Group on Earth  Observations Cold Regions Initiative (GEO CRI) jointly call for this session-"Big Data in Support  of Arctic Sustainable Development Goals and Pan-Arctic International Cooperation". 

This session invites experts in the fields of Arctic data, environment, energy, sustainable  development, humanities and social sciences and international cooperation. The session will  discuss how big data can play a positive and multi-disciplinary role in the sustainable  development. The session will be presented through invited keynote presentations, opinion  presentations and panel discussions, to discuss the demand for big data and its international  cooperations for the Arctic environment, energy, humanities and social sciences. 

The session will explore new ways and opportunities for big data to support the Arctic  sustainable development and further promote international science cooperation, build multi-  disciplinary research road map based on big data, and supporting for the global  implementation of sustainable development goals.

XU Qingchao

University of Chinese Academy of Sciences (UCAS), China

QIU Yubao

International Research Center of Big Data for Sustainable Development Goals (CBAS), China

13:15 - 13:25
Opening speech


GUO Huadong: International Research Center of Big Data for Sustainable Development Goals, China
GAO Feng Ministry of Foreign Affairs, China

13:25 - 14:05
Keynote Presentation


13:25-13:35
Scientific cooperation and sustainable development
Paul BERKMAN, Harvard University, U.S.

13:35-13:45
GEO Cold Regions Initiative
Massimo MENENTI, Delft University of Technology, the Netherlands

13:45-13:55
Digital Arctic-Environment and Ecosystem
LI Yifan, UArctic-HIT-TC, China

13:55-14:05
Digital geomorphology and sustainable development of the Arctic
YANG Jian, Shanghai Institute of International Studies, China

14:05 - 14:30
Opinion Presentation


14:05-14:10
Data and Knowledge for SDG13 climate actions
Paola De SALVO, Group on Earth Observations (GEO)

14:10-14:15
Energy transition and sustainability in Arctic Nations
DUAN Fengjun, The Canon Institute for Global Studies, China

14:15-14:20
Green Economy modelling tools, reliable metrics and measurements for achieving Arctic Sustainable Development Goals
Alina STEBLYANSKAYA, Harbin Engineering University, China

14:20-14:25
Policy Practices of Arctic Indigenous Traditional Knowledge
QU Feng, Liaocheng University, China

14:25-14:30
Gap analysis of the existing Arctic Science Co-Operations (AASCO)
Hanna K Lappalainen, Helsinki University, Finland



14:30 - 15:10
Panel Discussion: Big Data in Support of Arctic Sustainable Development Goals and Pan-Arctic International Cooperation


Chair: CHU Wenbo, Group on Earth Observations (GEO)
Panel List: all member

15:10 - 15:15
Conclusion (Closing)

For more information and participations, please contact:
Ms. Meng Dang
Email: dangmeng@cbas.ac.cn