The popularity of data science has grown steadily over the last decade with the advent of big data and the much-buzzed-about analyses of Nate Silver.
Leaders in the technology industry, from commerce to computing, are intently focused on getting as much knowledge from data as possible.
Now, the wrangling of data to uncover solutions, make predictions, formulate deeper questions and identify opportunities has found a home at the university library.
Michael Simeone, director of Data Science and Analytics at ASU Library, sees Arizona State University as an ideal ecosystem for the applications of data science and the library as a critical resource to support it.
The key, he says, is collaboration.
“Data science isn’t done in isolation. It’s inherently collective and interdisciplinary, which is why ASU is the perfect place for it,” said Simeone, an assistant research professor affiliated with the Biosocial Complexity Initiative, the Department of English, the Institute for Social Science Research, and the School of Sustainability. “My focus at the library is connecting researchers with information and with each other.”
Along with fellow data scientist David Little, Simeone aims to spread that message Sept. 17–21 as part of Data Science Week, a series of open-house events for students and faculty to gauge interest and raise awareness about the new library lab and the research and partnership opportunities it can foster.
Video by Deanna Dent/ASU Now
Such partnerships include a project with ASU Facilities Management, in which a student-faculty team analyzed thousands of university facility requests over the past five years in order to establish a predictive model for estimating component failures in building climate-control systems.
Another collaboration with the School of Art, within the Herberger Institute for Design and the Arts, led to the creation of an interactive model to visualize the geographical range of artists whose works were highly sought out in the trans-Atlantic art trade.
“We have ongoing and available projects for the community to get involved in, and we want students and researchers participating from a diversity of fields: art history, engineering, language and literature, biology, urban planning, economics and business,” Simeone said. “If you’re faculty, staff or student, we can look at opportunities to collaborate, gain project experience, or learn about what other researchers are doing at ASU and beyond.”
Whether you’re a beginner or an expert, all are welcome in the data lab, a decidedly low-tech space that Simeone runs in the lower level of Hayden Library.
When entering the lab, you won’t find a sea of computers or a team of screen-focused programmers. (This isn’t the place where you drop off your messy data for a “geek” to clean.)
Instead, you’ll find whiteboards, a few purpose-built computers, and an open table with people exploring a problem and the various ways of engaging with it.
“This isn’t a service desk,” Little said. “This is an open lab. We’re looking to help you find a collaborator or collaborate with you directly, and we’re interested in solving complex problems and working with meaningful data in our efforts to do that.”
Over the last year, Simeone has worked to ensure that the new lab space met key needs of the ASU community. Meeting regularly with students, faculty and staff interested in gaining experience with data visualization, machine learning and analytics programs, Simeone has worked with both undergraduate and graduate students on their own research, including a team from the W. P. Carey School of Business for a capstone project that involved text-mining emails for organizational analysis.
Simeone also teaches graduate-level courses in the computational and digital humanities certificate, which is run by the School for International Letters and Cultures.
Working with Simeone, ASU student Shashank Kapoor is specializing in big data systems as part of his graduate work in computer science, within the Ira A. Fulton Schools of Engineering.
Referred to as “data engineering,” Kapoor’s work first requires significant data analysis in order to engineer software to perform a specific task.
“For example, if you are a bank, say you want to know all your customers who could be victims of identity theft,” Kapoor said. “We can run that data science job with the banking software. It is an overlap with data science. With data science skills, no matter what type of data you have — structured, unstructured or semi-structured — I can analyze it and give some meaningful output, and with data engineering skills, I can provide that useful output in the best fashion.”
The ASU Library lab will also launch a student data science working group this semester, in which students will meet weekly to explore problems, get exposed to using tools such as Python, a program used to gain insight from storing and manipulating data, and help one another think with data.
“The student working group is really key to having students learn best practices and get experience solving problems in a multidisciplinary, team-based environment,” Simeone said.
According to Simeone and Little, the potential for data science applications at ASU is high.
“The principles of data science align well with ASU’s core values: use-inspired research, knowledge fusion, collaboration and inclusion,” Simeone said. “Here, everyone wants to be part of building something. We’re helping them do that.”
Top photo: Data scientist Michael Simeone speaks about data visualization during an introduction to the Hayden Library data lab on Sept. 7. Photo by Deanna Dent/ASU Now
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