Wolfram Data Drop: Making the World Computable

What Is Wolfram Data Drop?

In March of this year, Wolfram launched an open service called Wolfram Data Drop. According to Wolfram’s website, Data Drop’s official function is to “add semantics to data and make it computable.” The service allows users to store data on the Wolfram Cloud for later visualization, querying, and analysis using the full power of the Wolfram language.

How Does It Work?

First, users create a databin on the Wolfram Cloud using the Data Drop interface. The databin is where users will store their desired datasets. Each databin has a unique ID number which users may use to tell other people or software where to dump data.

Additionally, each ID number has its own unique webpage for users to view their data. Once data is added to a databin, users can then manipulate it as they wish, such as calling the data into functions or creating dynamic graphs for reports.

What Kind of Data Can You Store?

One important question comes to mind: “Exactly what kind of data can I store?” Thanks to the might of the Wolfram Data Framework, users can add semantic value to nearly any imaginable piece of data. That is, you can make any piece of data such that it can be interpreted meaningfully by Wolfram, thereby making results of computations also meaningful.

You can store anything from basic numbers, text, and images to compound data structures like geolocations, and the beauty of Data Drop is that this data can be sourced from practically anywhere. APIs, emails, a Raspberry Pi, or even a tweet on Twitter can be used to push data into your databin. In addition, Data Drop has a channel on IFTTT (if this, then that), so data can be easily collected from other channels that exist on the service including Instagram, Dropbox, and Google Drive.

What Can You Do With It?

With Wolfram Data Drop, the possibilities are endless. Data Drop makes it easy for anyone to gather and manipulate information, which can be applied to anything from viewing patterns in daily-life activities to analyzing huge corporate network systems. A few interesting things that have been done recently include finding the most dominant color in a city (by analyzing geotagged pictures dumped from Instagram) and tracking an individual’s elevation changes throughout the week.

While the results of these applications are not very extraordinary themselves, they do show the immense potential of the service. Wolfram Data Drop is still relatively new, and only time will tell the true impact it will have in the world of information processing.