Five projects harnessing big data to good
The data science industry has grown in the last decade due to advances in computing, mathematics, and data storage. Australia’s Industry 4.0 task force has been busy exploring how to improve Australia’s economy using tools like artificial intelligence, machine learning, and big data analytics.
Data science has the potential to solve complex issues and drive innovation. However, it is often criticized for unethical data use and unintended adverse consequences. This is especially true in commercial situations where people are treated as data points within annual company reports.
Data science shouldn’t just be about profit margins and business insights. Big data, when used ethically, can solve many of society’s toughest social and environmental issues.
Underpinning Industry 4.0 must be values that support social benefit, also known as Society 4.0. This means using data ethically and involving citizens.
Here are five data science projects that put these principles into action.
Read more: The future of data science looks spectacular
It is not easy to solve social and environmental issues. Consider the distress and hardship that rural areas have experienced due to the drought. The sheer size of Australia and the number of people involved make it difficult to provide support and resources for those who are in need.
The team teamed up with the Australian Red Cross in order to determine the hotspots of humanitarian activity in Victoria. Social media data was used to map the daily humanitarian activity and pinpoint specific locations. We found that the most active areas of charity and volunteering were located around the Melbourne CBD and eastern suburbs. These insights can help local organizations to channel volunteer activity during times of crisis.
Distribution of humanitarian action across inner Melbourne and local government areas. The blue dots and the red dots are scraped Instagram posts based on hashtags such as #volunteer or #charity.
Fire safety at home: How to improve itta science is constantly challenged by the need to access the correct data in the appropriate form. Fire and smoke alarms can save lives. This risk can be reduced by targeting houses that do not have fire alarms. There is no reliable source of data to draw from.
Enigma Labs developed open data tools in the United States to map and model risk at the neighborhood level. Their model, which combines local fire data and national census data to calculate a risk score, combines a geocoder (TIGER) with analytics.
Calculated fire fatality scores at the level of Census block groups. Enigma Labs
Citizens can generate social data. Many open, crowdsourced mapping projects exist, but the real value of data science is often in the connecting of the dots.
The Project Mapping Police Violence in the US monitors and visualizes police violence. The project uses three crowdsourced databases but also fills the gaps with a mixture of social media, obituaries, and criminal records databases. The project quantifies and visualizes the problem by combining all of this information.
Visualization of the frequency and severity of police violence across the United States. Mapping Police Violence
The Internet of Things consists of many connected devices that gather data. These objects can become intelligent when they are embedded into everyday objects and are combined with cloud computing and analysis.
You may have seen BigBelly trash bins in the CBD if you live there. Solar-powered trash compactors are built into these smart bins, which regularly compress garbage throughout the day. The waste is collected 80% less, reducing carbon emissions and waste overflow.
A cloud-based data portal called CLEAN provides real-time data reporting and analysis. The tool helps identify trends in waste overflow and can be used to plan collection services.
