NYU Data Science newsletter – November 27, 2015

GROUP CURATION: N/A

Former Magic Grantee Dafna Shahaf, a post-doc in the Computer Science Department at Stanford University, together with researchers from Stanford, the University of Washington, and Microsoft, has just published a paper in the Communications of the ACM on “Information Cartography.” Dafna and her coauthors construct a news summarization tool inspired by “metro maps.”

Extremely large datasets have become routine in biology. However, performing a computational analysis of a large dataset can be overwhelming, especially for novices. Here, we present a step-by-step guide to computing workflows with the biologist end-user in mind. Starting from a foundation of sound data management practices, we make specific recommendations on how to approach and perform computational analyses of large datasets, with a view to enabling sound, reproducible biological research.

… unattractive trade-offs face nearly everyone wanting to quickly explore a new data source. The following paper by Alagiannis et al. investigates a third approach, extending a DBMS so it can use the file data in situ, without having to load it first. They term their approach “NoDB” to indicate it does not require a separate copy of the data stored internally to the DBMS.

As people spend increasing proportions of their daily lives using social media, such as Twitter and Facebook, they are being invited to support myriad political causes by sharing, liking, endorsing, or downloading. Chain reactions caused by these tiny acts of participation form a growing part of collective action today, from neighborhood campaigns to global political movements. Political Turbulence reveals that, in fact, most attempts at collective action online do not succeed, but some give rise to huge mobilizations—even revolutions.

I wrote a thing for Foreign Policy‘s Democracy Lab on evidence that widely-used data on human rights practices understate the improvements that have occurred around the world in the past few decades: It’s Getting Better All The Time.

Can machine-learning techniques identify disease-carrying species and predict epidemics?

… PSFK: What are some of the larger themes you have been paying attention to in the online security space over the past year?

Drew Conway: From a consumer perspective, there’s a much higher expectation of security, driven by a lot of the larger, more public breaches that have happened. At the same time, there hasn’t yet been a counterbalance for companies around the expectation of stewardship around data.

… This is a “personal view”, biased by my experiences and idiosyncrasies. I’ve followed the climate situation for some time, including working on Al Gore’s book Our Choice, but I can’t hope to convey the full picture — just a sliver that’s visible from where I’m standing. I urge you to talk to many scientists and engineers involved in climate analysis and energy, and see for yourself what the needs are and how you can contribute.

This is aimed at people in the tech industry, and is more about what you can do with your career than at a hackathon. I’m not going to discuss policy and regulation, although they’re no less important than technological innovation. A good way to think about it, via Saul Griffith, is that it’s the role of technologists to create options for policy-makers.

In Chicago, cops try a ‘guardian’ approach armed with new crime-prediction methods and non-punitive social intervention.

This tutorial teaches you to create a plugin for D3 using D3’s new 4.0 module pattern. Although the word plugin suggests extending core functionality, this pattern is used internally by D3 to organize the code into modules. Thus, you can use this pattern to replace default behavior or to pick a subset of features for a custom build. Another way of thinking about it is that everything in D3 is a plugin, including core features like colors, scales, and selections.

A little over a year and a half ago, we had a dramatic rethink of the technologies and development workflows for building with WordPress.

Our existing codebase and workflows had served us well, but ten years of legacy was beginning to seriously hinder us from building the modern, fast, and mobile-friendly experiences that our users expect. It seemed like collaboration between developers and designers was not firing on all cylinders. So we asked ourselves the question: What would WordPress.com look like if we were to start building it today?

Juan Bello is an Associate Professor of Music Technology in New York University’s Steinhardt Program, and an Affiliated Faculty member at the Center for Data Science. He is the co-founder of the Music and Audio Research Lab (MARL) and his research focuses on digital signal processing, machine listening and music information retrieval.

… What drew you to Music information retrieval?

The combination of engineering, computer science and music was hard to resist. And at the time, it was a totally wide open field. People had worked on speech processing, and there have been decades of work in computer music, but using computers for music analysis was rare. There was ample space for young doctoral students to cut their teeth on and explore.