Making Data Dance

In the last half-decade, innovations in technology and data storage have led to the generation of an estimated 90 percent of all the data ever produced. The sheer volume and increased complexity of these data have created unprecedented opportunities, but taking advantage of them requires investment in data science talent that can deliver the innovative tools to meet a client’s highly specific needs.

Hear More from Quilong MinThat’s why a growing number of scientists, policy makers, researchers, and private enterprises are coming to the University at Albany’s Albany Visualization and Informatics Lab (AVAIL), a data science engineering team that is pioneering web-based solutions that put visualized, organized data at a client’s fingertips.

“Show us your data, we’ll make it dance,” proclaims the lab’s website.

In 2014 alone, the AVAIL team, led by Catherine Lawson, associate professor in Geography and Planning and an affiliated faculty member in the informatics Ph.D. program, developed a web-based “Bus Stop Level Transit Demand Modelling” tool suite for NJTransit and the New Jersey Department of Transportation; a Federal Highway Administration pooled fund study to develop a web-based traffic data analytics module for six state transportation departments (Connecticut, Ohio, Pennsylvania, Texas, North Carolina and Michigan); and a web-based collaborative decision-making tool to facilitate the location of weather instrumentation towers for NYS Mesonet, New York’s new early warning extreme weather detection system.

AVAIL also secured a number of projects for 2015, including a statewide traffic bottleneck map for the New York State Department of Transportation (NYSDOT); a second phase of the NJTransit web-tool suite, and a real-time bus and subway schedule for the Manhattan Transit Authority.

In December 2014, the prestigious Ewing Marion Kauffman Foundation awarded AVAIL a $200,000 contract to create an Entrepreneurial Landscape Analysis Tool that shows business climate change over time. The tool combines data sets with leading indicator potential, overlaying information visually and geospatially, and so highlights business type distributions, property value, and income.

“This will aid businesses in identifying market gaps, human capital and geographic opportunities,” said Lawson, “and it will also help local planners identify policies that encourage entrepreneurism and illuminate important economic trends.”

In the Kauffman Foundation project, AVAIL is using a broad analysis of nationally available datasets for understanding economic activity and job creation to develop interdependent visualizations that reveal change in economic activity for Census Urban Areas and also allow comparison of American cities with each other and themselves across a 20-year span (1992 to 2012).

“We will use this data to look in detail at urbanized areas at the zip code and census tract levels to understand the spatial aspects of economic activity, such as industry clustering and employment density,” said Lawson.

AVAIL’s assets, which include the programming wizardry of Alex Muro (UAlbany class of ’06) and the growing computer science talents of several graduate students, are increasingly being sought after by private industry. One of the team’s students, Eric Conklin, after receiving his master’s in computer science in December 2014, was hired full-time by AVAIL to head up the development of a National Performance Measurement Research Dataset bottleneck map for NYSDOT. Upon completion of this open source software tool, AVAIL expects to expand its use to other state DOTs and metropolitan planning organizations.

AVAIL is also a key partner in an innovative international project to test and calibrate new traffic-counting video camera technologies developed in Poland, with funding from the private Polish Road and Bridge Research Institute. The cameras, developed by a company called Neurosoft, are being deployed at a location in Virginia. AVAIL plans to test the viability of the technology and calibrate the collected data to American transportation data standards. The hope is that the cameras will provide a cheaper and more effective means of collecting transportation data.