While Data Science for Social Good sorts through nearly 900 applications for their 2016 summer fellowship, their 2015 projects continue to attract interest. Last week, the Charlotte Observer profiled DSSG's collaboration with the Charlotte-Mecklenburg Police Department, using data on officers, arrests, dispatches, and other sources to help predict negative interactions between police officers and the public.
In two recent studies, CI Senior Fellows James Evans and Andrey Rzhetsky built a network of millions of papers to ask an important question: is scientific research living up to its potential? Their analysis, conducted with UCLA's Jacob Foster and CI Director Ian Foster, found that science increasingly explores more incremental and conservative questions, avoiding the
This month's announcement of a $3.1 million National Science Foundation for Array of Things inspired a wave of enthusiastic coverage about the urban sensing project. The plan to install 500 sensor nodes, collecting data on Chicago's environment, infrastructure, and activity, was touted as an important step towards creating a "smart city," boosting data-driven public policy and community engagement.
Today, a scientist's most desired citation may be from a publication not often thought of as prestigious: Wikipedia. While the open, user-curated encyclopedia may have occasional credibility issues, it remains the first source many people -- even scientists themselves -- consult when faced with an unfamiliar topic. As such, a Wikipedia reference may expose more people to a particular research finding than any citation from a scientific journal.
Scientific American looked at the Data Science for Social Good fellowship project that seeks to evaluate and improve police department early warning systems for predicting officer behavior and adverse incidents. Another DSSG project, using predictive analytics to fight lead poisoning, was also recently featured in the Chicago Tribune.
For better or worse, Wikipedia is now one of the world's foremost resources for information on everything from string theory to obscure Star Wars characters. The general public and -- even if they won't admit it -- many scholars use Wikipedia as a first-order reference on unfamiliar scientific subjects, before diving more deeply into the primary sources. But doing so places faith in the hands of the Wikipedia community, trusting that a page's editors have drawn upon the best scientific evidence in summarizing the topic for a more general audience.
Last winter, a crew from the BBC's technology program Click visited Chicago to learn more about the Array of Things, the Urban Center for Computation and Data city-wide sensor network project. Reporter Marc Cieslak went to Argonne National Laboratory, the School of the Art Institute of Chicago, and the Chicago Architecture Foundation's "City of Big Data" exhibit to profile the technology, design, and potential of the project, which hopes to install hundreds of sensor nodes around the city over the next three years.
With today's faster internet speeds and file-sharing services, many of us take data transfer for granted. But when files and datasets are measured in terabytes and petabytes instead of megabytes, many of the struggles of the past return: long waiting times, mid-transfer failures, and clunky interfaces.
When people talk about the current tech boom, it usually conjures up images of phone apps, social media networks, and startups with one-word names. But inside the public sector, a quieter tech revolution stirs, as governments increasingly recognize the power of data to help them serve their constituents more effectively. This trend creates a new kind of skills gap, as governments look for people with both the technical skills and civic motivation to analyze data and build tools for internal and external use.
In movies, huge battle scenes no longer rely upon the expensive recruitment and coordination of thousands of extras. Instead, the epic clashes of armies in films such as The Lord of the Rings trilogy use a computational technique called agent-based modeling, or ABM. In ABM, thousands or even millions of individual "agents" are programmed to follow a set of simple rules, which creates complex, realistic behavior at large scales.