Best ways to support UN’s SDGs with capable Big Data Science – Part 3

Continuing from Part 2 which discussed ways Big Data supports the Sustainable Development Goals (SDGs) 7 to 12 of UN’s 2030 Agenda for Sustainable Development, Part 3 does the same for the SDGs 13 to 17.

SDG 13: Climate Action

No data-driven sustainable development article (or listicle) would be complete without a discussion about climate action. Doing something for the environment is such a common idea of sustainability that I came across too many examples of Big Data-driven climate action initiatives to fit into one little section of a listicle.

Here are some examples:

  • Google Earth Engine combines publicly available satellite imagery and geospatial datasets to detect changes on Earth’s surface. The Timelapse feature is really cool (as in the tool is cool, not the deforestation or melting ice caps) because you get to see how some parts of Earth have been changing over the past 35 years. Like the drying of the Aral Sea in Central Asia, bushfires in Australia and deforestation in Bolivia.
  • Surging Seas is an interactive map developed by Climate Central to provide data on the rising sea levels, coastal flood risk, tides, storms, and tsunamis throughout the USA.
  • Several studies have worked to explain the seriousness of ocean warming. Ocean warming and acidification pose a major threat to many species and ecosystems, including marine invertebrates. For one ocean warming study, researchers at Harvard University and the UK’s National Oceanography Centre used Big Data and advanced statistics to investigate the changes in ocean temperature for the past century, and correct the errors of historical temperature measurements in the National Oceanic and Atmospheric Administration’s database. This is to determine if human contribution to ocean warming is greater than we thought and to understand what needs to be avoided for the future.
This video shows the connection between ocean temperature and the atmosphere.
Video Source: ESA/Planetary Visions

SDG 14: Life Below Water

Some people seem to have an issue with overfishing but they don’t seem to have an issue with fishing. Heck, I think fishing should be banned! It’s an injustice to marine animals.

Hopefully, SDG 14’s aim to “sustainably manage and protect marine and coastal ecosystems from pollution as well as address the impacts of ocean acidification” will include saving marine animals from danger.

One Big Data-driven effort to protect life under water that I find interesting is the acoustic pollution minimisation project by French maritime data analytics company, SINAY Maritime Data Solution, which aggregates ocean data from over 6,000 sources including IoT sensor data according to an article by Forbes.

Cetaceans (marine mammals) are especially affected by acoustic pollution due to their sensitivity to high sound pressure, usually caused by construction and port expansion projects and ships.

This project aims to detect acoustic pollution as well as how near cetaceans are in real-time to influence decisions using machine learning on acoustically noisy human activity.

SDG 15: Life on Land

Honestly, as a vegan, I was expecting studies or research into how Big Data can meet this SDG 15 by employing Big Data to liberate animals from exploitation (just like how I was expecting SDG 14 efforts to liberate marine animals from fishing nets and whatever else is used to catch them).

But noooooooo… *sigh* Hopefully, the day will come when treating any animal species as a commodity will become illegal and frowned upon by mainstream society.

On the bright side, efforts to curb deforestation have an indirect effect on animals as many species rely on forests as their habitats. One important use of Big Data for SDG 15 is the use of remote sensing data to assess temporal and spatial changes in topography and surface water. Very similar to SDG 13 of Climate Action…

Similarly, Big Data can also help monitor desertification, the creation of new deserts through the degradation of drylands, using satellite technologies and a set of land degradation indicators like soil moisture and land cover.

SDG 16: Peace, Justice and Strong Institutions

SDG 16 aims to promote the rule of law and human rights, reduce the flow of illicit weapons and work with governments and communities to end conflict and violence. This means NO WAR!

How has Big Data been used for promoting peace and justice? These use cases will tell:

  • Big Data applications are used for a migration feasibility study to deal with the migration crisis. Among the applications are using VHR and microsatellite constellation data to improve monitoring capabilities, analysing the integration of open source and social data, and providing abnormalities detected from mobile data as input to geospatial monitoring and searching services.
  • AI developed to prepare astronauts for space missions is also used to fight crime. The world needs an AI that can make good use of police data to detect suspicious patterns, reconstruct scenes and highlight promising avenues of investigation, and it turns out that this AI has what it takes to do the job.

SDG 17: Partnerships for the Goals

If there’s one thing all these SDGs share in common, it’s teamwork. All these SDGs would be difficult to come to fruition if not for UN’s partnerships. Hence, SDG 17 requires different parties to bring their expertise to the table and work together to fulfill the SDGs.

The migration crisis mentioned in SDG 16 required the partnership of so many stakeholders from different sectors including EU Agencies, National Coordination Centre, humanitarian aid and civil protection actors, NGOs managing the migration crisis on a daily basis and national authorities.

Big Data for A Positive Impact

Doing this article series about UN’s SDGs has taught me a very important lesson. Big Data has the potential to improve the world and that potential needs to be used to the fullest. It has also made me less scared of AI (a fear which was instilled by the negative rep of AI in science fiction).

Maybe there are some people who *cough cough* thought of using Big Data for their own selfish interests like profit maximisation (nothing wrong with that as long as it’s gained ethically) and using insights to blackmail someone (now this is unethical). And that discussions about data will always warrant privacy concerns.

But many of the use cases in this article series have proven to me that there are other people who want to use Big Data to make the world a better place. Make a difference in other people’s lives. Heal the environment. Fight for justice for those who are still suffering from injustice. All those cliche yet meaningful stuff…

Even if it seems as if no one is working on fulfilling certain SDGs (or that one SDG doesn’t matter to some people), at least one party will be working on a Big Data-driven initiative for every SDG, intentionally or unintentionally. Maybe because someone will always be affected by an issue that each SDG aims to solve (why else would the SDG be there?).

I also learnt that some of the SDGs are connected to each other and each of them wouldn’t be solved on its own. Like, if you work on protecting the forests and oceans (Climate Action), you might indirectly protect the animals who live in forests and oceans (Life On Land and Life Below Water).

Or, if you work on providing jobs with decent pay to poor communities (Decent Work and Economic Growth), you might end up saving them from poverty (No Poverty) and helping them put food on the table (Zero Hunger, and yeah, dining tables would help).

So whichever SDG you’re aiming to meet with your work, your work will also be meeting other SDGs. Like hitting two or more mangoes (not birds) with one stone. Who knows? If you’re using Big Data to do this, you might end up with a buffet of mangoes.