NYU Data Science newsletter – April 22, 2016

GROUP CURATION: N/A

The talking speaker started as part of a secret augmented-reality project and ended up as a surprise hit.

A new initiative is working to create a data dashboard that almost any city could use to get a handle on the health of its citizens. City-level health data can be critical when it comes to measures like reducing smoking or deciding where to build new parks and health clinics. Yet most health data is collected at the county, not the city level. That means city leaders looking to improve residents’ health lack a baseline of information to work from.

The Municipal Health Data for American Cities Initiative proposes to solve this. The initiative is a collaboration between New York University and the National Resource Network, a White House and HUD-funded agency that assists cities facing economic hardship.

Hi Reddit! I’m George Church and my lab is developing technologies for genome sequencing, gene editing, and DNA nanotechnology (bio).

One area that has attracted a lot of attention recently is the CRISPR technology for editing the genetic information in living cells, a sort of ‘nano-surgery’ that can be used to treat genetic disease at the root cause.

The French-American Doctoral Exchange Seminar (FADEx), a program organized by the Office for Science & Technology at the Embassy of France in the United States, is aimed at encouraging collaboration among American and French doctoral students with similar research interests and forging what could turn into long-lasting scientific partnerships.

The theme of FADEx 2016 is cyber-physical systems, which integrate computation, networking, and physical processes and are used in the fields of transportation, manufacturing, healthcare, and more.

Also, in University data science:

Advancing ingenuity (April 27, Harvard John A. Paulson School of Engineering and Applied Sciences)

Is Data Science a Liberal Art? (April 25, SmartData Collective, George Mount)

Data Science Across Disciplines and the program’s Final Poster Session (April 26, University of Illinois, University Library)

On this week’s episode of our podcast What’s The Point, New York Times jazz and pop critic Ben Ratliff discusses his new book Every Song Ever and how the everything-at-our-fingertips era is changing the way we listen to music. [audio, 36:04]

Also, this August in NYC:

17th International Society for Music Information Retrieval Conference (August 7-11, organized by NYU and Columbia University)

Local and state officials claimed for months that tests showed that Flint’s water had safe levels of lead. But the officials used flawed testing methods, making the levels of lead in the water supply appear far less dangerous than they were.

Three of those officials were charged with crimes on Wednesday, accused of covering up glaring deficiencies in two rounds of lead testing conducted in 2014 and 2015.

As Amazon has expanded rapidly to become “the everything store,” it’s offered the promise of an egalitarian shopping experience. On Amazon and other online retailers, a black customer isn’t viewed with suspicion, much less followed around by store security. Most of Amazon’s services are available to almost every address in the U.S. “We don’t know what you look like when you come into our store, which is vastly different than physical retail,” says Craig Berman, Amazon’s vice president for global communications. “We are ridiculously prideful about that. We offer every customer the same price. It doesn’t matter where you live.”

In the age of information, where massive and widespread collections of data are being digitized and shared, one would expect that there would be extensive information on the threats to global biodiversity. Having such information would lead to better understating on how to reduce biodiversity loss and achieve environmental goals. However, a Policy Forum piece recently published in Science found that threat data is not readily available, making it difficult to fully understand the threats to biodiversity and difficult to identify the steps necessary to alleviate those threats.

This year in particular CSCW would like to invite papers that make a contribution to building CSCW systems including (but not limited to) technical enablers for CSCW applications; methods and techniques for new CSCW services and applications; and evaluation of fully-built CSCW systems and lab and field settings. Authors will be able to direct such submissions to a dedicated subcommittee.

Deadline for submissions is Friday, May 27.

In an effort to increase community building, SciPy emphasizes the birds of a feather (BoFs) sessions to discuss primary or tangentially related topics in an interactive setting. These sessions usually include short presentations by a moderator and panel followed by an open discussion with everyone in attendance.

Austin, TX Deadline for BoF submissions is Monday, June 27. SciPy 2016 is Wednesday-Friday, July 13-15.

Welcome. This repository contains the data and scripts comprising the Numenta Anomaly Benchmark (NAB). NAB is a novel benchmark for evaluating algorithms for anomaly detection in streaming, real-time applications. It is comprised of over 50 labeled real-world and artificial timeseries data files plus a novel scoring mechanism designed for real-time applications.

Included are the tools to allow you to easily run NAB on your own anomaly detection algorithms; see the NAB entry points info. Competitive results tied to open source code will be posted in the wiki on the Scoreboard. Let us know about your work by emailing us at nab@numenta.org or submitting a pull request.

Apache Kudu (incubating) is the newest addition to the set of storage engines that integrate with the Apache Hadoop ecosystem. The promise of Kudu is to deliver high-scan performance, targeting analytical workloads, while allowing users to concurrently insert, update, and delete records. With these properties, Kudu becomes a viable alternative to existing combinations of HDFS and/or Apache HBase to achieve similar results with less complicated ETL pipelines, comparable performance, and a lighter maintenance burden.

In this blog post, we want to describe how Apache Impala (incubating) integrates with Kudu for analytic SQL queries on Hadoop and how it takes full advantage of the distinct properties of Kudu.

Apparently MTA (the company running the NYC subway) has a real-time API….I started tracking all subway trains one day and completely forgot about it. Several weeks later I had a 3GB large data dump full of all the arrivals for 1, 2, 3, 4, 5, 6, L, SI and GC (the latter two being Staten Island railway and Grand Central Shuttle).