We talk a lot about how the Internet is driving the accumulation of data, but our offline experience can be just as valuable when it comes to big data analytics. There are 6.79 billion people on this earth, all of which have access to data about the weather, local food supply, the price of gas and many other local issues.
We talk a lot about how the Internet is driving the accumulation of data, but our offline experience can be just as valuable when it comes to big data analytics. There are 6.79 billion people on this earth, all of which have access to data about the weather, local food supply, the price of gas and many other local issues. This hyperlocal data may not be of much use on its own, but when it’s combined with billions of data points from around the world, it can give us a good indication of how weather patterns are affecting the food supply around the world, or connect news from around the world to the rising and falling stock market.
Why is hyperlocal data garnering interest now? Sensors and GPS devices used to be much more expensive, but now everyone with a smartphone carries a GPS in their pocket, making it easy and affordable to gather data based on a specific location. Location-based data is already used by marketers and services like FourSquare to target consumers when they are at an appropriate location, but the potential of hyperlocal data extends far beyond sending out coupon offers. Here’s some companies that are already taking advantage of hyperlocal data:
Premise uses a smartphone app and 700 people in 25 developing countries to collect photos of the food and goods for sale at the public markets. The photographers are mostly college students or house moms who are paid 8 to 10 cents a picture. The company collects the photos along with time and location data and a couple other facts, such as how crowded the market was at the time. That data is combined with price data from 30,000 websites. The company then analyzes this data to create a real-time inflation index that investors can use to measure food security, and producers can use to judge market conditions.
2. ClearStory Data
ClearStory Data is a startup that provides a data service to those who want instant access to data on various topics in order to analyse it and find useful insights. For example, you could look for correlations between ticket sales for the local football game and the weather, or perhaps how often the game was mentioned on social media. The concept is simple, but quickly locating data sources and presenting them in a useful way is a difficult endeavor that requires advanced technology and analytics behind the scenes as well.
FoodSpotting is an app that lets you take pictures and share photos of your food when you go out to eat. The app then connects that photo to a specific location, so that when someone is looking for a place to eat, they sort through photos of options close to them. The app also allows you to select a search area and then search for a particular food that you might be craving.
This app, created by Dutch scientists, takes hyperlocal temperature readings from the sensors used on smartphone batteries to keep them from overheating to calculate the weather in specific areas. Right now the app will read within a degree and a half of the actual temperature in major cities, and will provide many other readings such as light intensity and magnetic fluctuations. The app is still a work in progress, but the researchers believe that increasing the number of readings would eventually be useful for making weather forecasts that are much more accurate than current weather reports.
Ushahidi was first created in 2008 during the post-election fallout in Kenya. The site allowed people to anonymously report acts of violence and then plotted them on a map. After the Haitian earthquake, the site collected reports of emergencies, such as texts reporting people trapped under buildings. These reports were turned into a crisis map that emergency teams used to send aid. The site was a big first step in changing the way we report history and respond to disasters, as we can now rely on the reports from the masses rather than relying on journalists and historians.
When we’re talking about big data, let’s not forget that it’s made up of small pieces of data. This data may be a tweet or a click on a website, or it may be a photo from the local supermarket. No matter the source, we should take advantage of all data in order to truly reach the potential that big data technology, such as hadoop hive, has to offer.
Image Source: Jason Howie on Flickr