RTA, UN Experts unite for Big Data, AI

The Dubai Roads and Transport Authority (RTA) has recently teamed up with the United Nations Committee of Experts on Big Data and Data Science on a venture aimed at enhancing big data, artificial intelligence, and data science capabilities.

This joint effort is a continuation of the existing partnership between RTA and the UN committee and signifies a pivotal evolution in their collaboration. The primary objective is to exchange insights and experiences to elevate the efficacy of RTA’s transport and other public services.

The initiative seeks to bolster RTA’s reliance on data to improve decision-making processes and ensure access to dependable data both locally and globally. RTA has established nine dedicated teams to address various aspects such as methodology, quality, technology, data access, legal issues, and privacy, and to perform comprehensive cost-benefit analyses utilizing big data.

Mohammed Al Mudharreb, CEO of RTA’s Corporate Technology Support Services Sector, emphasized the vital cooperation with the UN Committee, noting RTA’s dedication to enhancing its data capabilities. He recognized the significance of modern technologies like AI and the Internet of Things, which are integral to the Fourth Industrial Revolution, in achieving Dubai’s ambition of becoming the smartest and happiest city in the world.

RTA, as an active participant in the UN Committee, has joined two key working groups focusing on leveraging mobile phone data for transportation statistics and on training, skill development, and capacity building in big data, AI, and data science. RTA, serving both as co-chair and member, plays a key role in crafting a comprehensive guide with the Committee, offering insights and strategies for effectively using mobile phone data in transport planning and decision-making.

Al Mudharreb noted that this collaboration is in line with RTA’s vision of becoming a data-centric organization and supports the UAE’s goals of enhancing digital governmental services and practices. By harnessing mobile phone data and promoting international cooperation, RTA aims to lead in transportation innovation, not just in the UAE but across the Middle East and North Africa.

RTA’s involvement in the team dedicated to training, skills, and capacity building underscores its commitment to knowledge exchange and skill enhancement in big data and data science. This participation aims to enrich the expertise of transportation professionals, embrace cutting-edge technologies, and cultivate a culture of innovation and collaboration.

Stefan Schweinfest, Director of the Statistics Division at the United Nations in New York, mentioned his office’s longstanding successful collaboration with the UAE’s Federal Competitiveness and Statistics Centre on big data projects. He looks forward to fruitful cooperation with RTA in crafting data-driven public policies and services for sustainable transportation. He also expressed hope for RTA’s contribution to the collaboration with the Regional Hub for Big Data in the UAE, aiming to develop big data, AI, and data science capabilities for the Middle East and North Africa’s statistical community.

Schweinfest elaborated that the UAE’s Federal Competitiveness and Statistics Centre now hosts the United Nations Platform headquarters, with RTA actively involved in big data and data science initiatives. This headquarters focuses on promoting the use of big data and data science for official statistics and sustainable development goals, sharing new methodologies, algorithms, and tools, and providing training on big data, AI, and data science for the region.

The United Nations Committee of Experts on Big Data and Data Science includes members from around 31 countries and 16 international organizations like the World Bank, with over 100 global experts collaborating to develop and share state-of-the-art methods, technologies, and practices in data science and big data. The committee also offers cloud services through its international platform to foster global cooperation in advancing data science by utilizing new data sources and innovative approaches.