Data & the Data Revolution
How the world learned to count, measure, and act. A guide for students and global development professionals.
Data
Data Organizations
From clay tablets to real-time data dashboards
Humans have collected data for thousands of years. Ancient civilisations counted harvests, people, and taxes. Early censuses helped rulers govern their territories. Data was powerful — but slow, fragmented, and hard to share.
The invention of the computer changed everything. From the 1950s onward, machines could process millions of records. Governments began digitising their statistics. Researchers could spot patterns across entire populations. For the first time, data became a tool for planning the future — not just recording the past.
By the 1990s, the internet connected data across borders. By the 2010s, smartphones turned every citizen into a data source. Today, satellites, sensors, and AI generate more data each second than the world once produced in a year.
1950s–80s
Computers digitise government statistics
1990s
Internet connects data across borders
2000–2015
MDGs launch global reporting standards
2015–now
SDGs + AI transform development data
The UN and the global goals framework
In 2000, world leaders adopted the Millennium Development Goals (MDGs). The MDGs set eight targets for reducing poverty, hunger, and disease by 2015. For the first time, countries agreed to measure progress using shared indicators. This created a global language for development data.
The MDGs showed what data could do — and revealed its gaps. Many countries lacked reliable statistics. Gender data was scarce. Cultural and social indicators were largely missing.
In 2015, the Sustainable Development Goals (SDGs) replaced the MDGs. The 17 SDGs are more ambitious. They cover climate, inequality, peace, and justice. They apply to all countries — not just developing ones. The SDG framework demands better, faster, and more disaggregated data than ever before.
The Data Revolution. A 2014 UN report called for a global data revolution to support the SDGs. It urged governments, companies, and civil society to open their data and share it across borders. The report set the stage for a new era of data collaboration.
Today, 193 UN Member States report progress on over 230 SDG indicators. The UN Statistics Division coordinates this effort. The Global Partnership for Sustainable Development Data connects governments, NGOs, and companies to strengthen national data systems worldwide.
The next framework: Culture as a global goal
The SDG agenda runs until 2030. Countries are already preparing the next framework for 2030–2045. A major debate is underway: should Culture become a standalone SDG?
At MONDIACULT 2022, 135 ministers of culture gathered in Mexico City. They recognised culture as a global public good. They called for its inclusion in the post-2030 development agenda. This was a historic step.
Adding a Culture SDG would require new data. Countries would need to measure arts and cultural participation, the economic value of creative industries, the role of culture in peace and social cohesion, and cultural heritage and intangible traditions.
Collecting this data is a challenge. Cultural activity is diverse and hard to quantify. Many countries lack baseline statistics. Building these systems requires investment, cooperation, and new methodologies.
Why it matters. Culture influences how people live, cooperate, and resolve conflict. Without data, culture remains invisible in policy decisions. A Culture SDG would make it visible — and actionable.
Artificial intelligence: power and responsibility
AI is transforming data collection and analysis. Machine learning can process satellite imagery to track deforestation. Natural language processing can analyse millions of social media posts. AI tools help researchers identify trends that human analysts would miss.
For global development, this is a breakthrough. AI can fill data gaps in countries with weak statistical systems. It can speed up reporting and reduce costs. It opens doors for evidence-based policymaking in real time.
But AI also raises serious concerns. Algorithms can reflect and amplify existing biases. If training data excludes women or marginalised groups, AI outputs will too. In development contexts, biased AI can reinforce inequality rather than reduce it.
Opportunity
AI speeds up data processing, fills gaps in national statistics, and enables faster, cheaper global reporting for the SDGs.
Risk
AI can encode bias, enable mass surveillance, and threaten the privacy of vulnerable populations — especially in fragile states.
Privacy is a fundamental right. Large-scale data collection — by governments, corporations, or development organisations — must respect people’s right to control their own information. The EU’s General Data Protection Regulation (GDPR) sets a global standard. But many countries lack comparable protections. Strengthening data governance is as important as expanding data collection.
Abstract light installation with figures silhouetted against projecting lights in Istanbul — Photo: Bica 52
Women, Culture and Peace: data for change
Data on women’s participation in cultural and civic life is sparse. Existing datasets often overlook cultural agency, creative labour, and the role of women in peace processes. This gap limits policymaking and research.
Women, Culture and Peace (WCP)
The WCP framework connects the UN’s Women, Peace and Security agenda with cultural peacebuilding. It supports research into how culture, women’s leadership, and creative expression contribute to peaceful societies. Collecting and analysing WCP-relevant data is a core part of this work.
RYB Global Development uses data visualisations and digital maps to present development trends across 193 countries. We connect organisations, researchers, and policymakers to make development data accessible and actionable.
Explore our data pages
Go deeper into specific topics. Each page offers curated resources, organisations, and tools.
Looking Forward
The data revolution is not finished. More countries need robust statistical systems. More data on culture, gender, and peace is urgently needed. As AI becomes more powerful, data governance must keep pace. The post-2030 development framework offers a chance to build more inclusive, more transparent, and more culturally-aware data systems — for all 193 countries.
Sources
- United Nations, A World That Counts: Mobilising the Data Revolution for Sustainable Development (2014). undatarevolution.org/report/
- United Nations, Transforming our World: the 2030 Agenda for Sustainable Development (2015). sdgs.un.org/2030agenda
- UN Statistics Division, SDG Indicators Framework. unstats.un.org/sdgs
- UNESCO, MONDIACULT 2022 Declaration, Mexico City. unesco.org/en/mondiacult2022
- Global Partnership for Sustainable Development Data. data4sdgs.org
- UN Women, Women, Peace and Security — UN Security Council Resolution 1325 (2000). unwomen.org/en/news/in-focus/women-peace-security
- European Commission, General Data Protection Regulation (GDPR). gdpr.eu
- RYB Global Development, Women, Culture and Peace (WCP) framework. redyellowblue.org/women-culture-and-peace