Data Science for Good, Part 2 Data Science for Good, Part 2
Introduction This is the second of a three-article series about Data Science for Good. This article introduces people, organizations, and projects... Data Science for Good, Part 2


This is the second of a three-article series about Data Science for Good. This article introduces people, organizations, and projects that use data science for good. The first article explained what the idea of data science is about and how you can get involved in it. The third and last article will discuss resources and technological tools that serve that purpose.

In my experience, I’ve encountered many people interested in helping but who lack opportunities to do so. This post intends to fill some of these gaps with the necessary information.



DataKind works with charities, social enterprises, and NGOs. They provide support in a wide variety of projects. Their motto is “harnessing the power of data science in the service of humanity.” They have several chapters around the world where they run local meetups, DataDives, or long term projects. You can apply to work with them here.

If you are a data enthusiast you can contact them to volunteer in a long term project with a charity. You could help them to organise DataDives. In the DataDives they partner with other organisations to work on their problems. The organization provides datasets, challenges, data scientists work on the challenges during a weekend.



DrivenData is a data science competition website for good causes who partner with institutions working on social issues. In their words, they “find real world questions where data science can have positive social impact.” You can take a look here at their active competitions.

UN Global Pulse

UN Global Pulse is a United Nations innovation initiative on Big Data. The idea is to use big data for sustainable development and humanitarian action. UN Global Pulse has three labs around the globe in Jakarta, Kampala, and New York. Their work is usually, but not limited to, around the 17 Sustainable Development Goals for 2030, defined by the UN. Check out their projects and their resource library (the reports are very good).

The GapMinder Project

The Gapminder foundation has been educating people for many years to see the trust in facts from data.


Other institutions to consider:

Projects & Problems

If you are running out of ideas or problems to solve here, I’d like to present to you the Sustainable Development Goals for 2030 defined by the UN in 2015. Sustainable Development means, in words of Prof Charles Hopkins, “The balance of Economic and Social development without compromising the Environment for us and future generations, also considering social justice, equity, human rights, transparency, intergenerational responsibility.”

The SDGs are 17 Global Goals with 169 targets and 232 indicators. This applies to all countries and anyone can work on them.

Inequality is one of the biggest problems nowadays along with health and wealth distribution. Also climate change is something that these goals focus on. Such goals urge for solutions and efforts from all citizens and parties involved. There are datasets and studies available but there are still many issues throughout the world that need to be addressed. This is where the magic of data science comes into play and you can join in solving world projects. Select a project and go forth.  Good luck!

The Social Progress Index created, by Michael Green, as a measure of the progress of countries. The SPI is not a replacement to the GDP but a complement. Its dimensions consider basic human needs, foundations of wellbeing, and opportunity, things that account what makes a good society.

The Dollar Street Project, takes photographs of living conditions of families in different countries around the world, on their website you can see how families really live. This is a project by the GapMinder Foundation.

The Global Partnership for Sustainable Development Data, congregates +280 organizations in order to find and monitor the necessary data for measure the 17 Global Sustainable Goals of the UN for 2030.

Our World in Data project, presents interesting analyses and visualizations of our world through data. Check out their website and learn a bit about our world. This project is supported by the Bill and Melinda Gates foundation.

Check the OKFN current projects, they are very cool. Here are a couple of them:

  • Open Data For Development or OD4D in short, is a global partnership funded by IRDC, the government of Canada, The World Bank, and the UK Department for International Development. “OD4D is scaling Open Data approaches that work, improving transparency and accountability, service delivery and the well-being of the poorest and most marginalized.”
  • OD4D is a source of research around Open Data providing data sources and ideas to apply Data Science for a better world.
  • The Open Data Index project, tracks how governments implements open data policies and shares their data to the civil society.

Bloomberg’s Data for Good Exchange (D4GX), an annual conference held at Bloomberg’s offices. It brings together data science practitioners, NGOs, government agencies, and private sector with focus on the application of data science for social good.



Data Science for Good tries to improve people’s lives from multiple perspectives. It can be opening data, sharing knowledge, collaborating on open sourcing projects, telling stories of success of what was achieved so experiences can lead to better outcomes and more. 

With Data for Good we are trying to make the world a better place by harnessing the power of data in a wide variety of ways.  There are multiple ways to join the community of Data Science for Good, just start putting your work where your heart is.

These projects and institutions can help us build better public policies, and make decision makers accountable with the power of data. 


In the next and last article on Data Science for Good,  we will cover people and resources around data for good. Stay tuned!


APPENDIX: Artificial Intelligence for Social Good is a related term. It is focused on the techniques usually used in artificial intelligence field to be used for common good. Whilst Data for good is the bigger umbrella, AI for Good and Data Science for Good are narrowed definitions of the same principle.

Diego Arenas

Diego Arenas, ODSC

I've worked in BI, DWH, and Data Mining. MSc in Data Science. Experience in multiple BI and Data Science tools always thinking how to solve information needs and add value to organisations from the data available. Experience with Business Objects, Pentaho, Informatica Power Center, SSAS, SSIS, SSRS, MS SQL Server from 2000 to 2017, and other DBMS, Tableau, Hadoop, Python, R, SQL. Predicting modelling. My interest are in Information Systems, Data Modeling, Predictive and Descriptive Analysis, Machine Learning, Data Visualization, Open Data. Specialties: Data modeling, data warehousing, data mining, performance management, business intelligence.