Using Data Science

What question or problem are you trying to address using data science?

Network intrusion

The problem is that of developing a simple, inexpensive methodology for detecting network intrusion attempts. Specifically, we are working on a system that is unobtrusive and requires little or no human attention. The conceptual approach is to predict network traffic in real-time and test for rapid departures between observed and predicted traffic. Brian Steele, Mathematical Sciences

Meteorological data

There is a major challenge in the accuracy of spatially explicit meteorological data for the US which is needed for all sorts of assessments from weather modeling to crop and ecological assessment to hydrology, climate change, and human health studies. This is particularly true with real-time and high resolution (<1x1 km) data. Generation of these spatial datasets from point observations, satellite data, and models involves enormous datasets and computing power. Anna Klene, Geography

Data collection and processing

Some time ago (in the age of Small Data) data was a blessing.  Now it sometimes becomes a curse.  Data has become very available and even abundant.  It is collected much faster than we are able to process it.  It becomes more and more common to dump data soon after it is collected just because it is not possible to store it or process it in real time. Therefore, we need to develop general approaches and tools that help us handle data efficiently in a wide variety of problems. Peter Golubstov, Mathematical Sciences

Cross disciplinary solutions

Computer science provides the core skills necessary to tackle problems in data science: data acquisition, data filtering, data cleaning, data analysis (data mining, machine learning), and data visualization. Computer science provides the necessary tools to develop solutions to some of the world's most pressing research problems across a surprisingly diverse set of fields by helping scientists find, understand, and learn from large data sets. Data science research conducted in our department is helping to solve problems in Biology, Chemistry, Conservation, Forestry, Law, and Physics, to name a few.  Robert Smith, Computer Science

 

What societal need drives your work in Data Science?

Public administration

In essence, data science and public administration brings together experts with the mission to conduct research to create data-driven solutions for large scale social problems in the public sector - health care, sustainability, criminal justice, non-profit, etc. For instance, data science and public administration can: provide training for students and professionals who are in government and non-profit organizations, conduct collaborative research with government and non-profit organizations, and develop software tools to be used by public service professionals.    Sara Rinfret, Political Science and Public Administration

Local economic growth

The work we do in big data /data analytics  has a direct impact on the economic development of Missoula and Montana.  Many tech companies are locating here with the expectation that we can provide a workforce with very specialized skills, coupled with a broad knowledge base.  Companies like Washington Corporation, ATG, GCS, LMG, Terra Echos, DataSmart Solutions, and TeraDact Solutions have already hired some of our students and are clamoring for more. Jason Triche, Management Information Systems

Resource management

The data and computer models being developed have broad applications for a range of resource management problems, including hydrology, and vegetation ecology. A primary focus is the development of more sophisticated models for anticipating and managing wildland fires. Anna Klene, Geography

Decision-making

For society to survive, meaningful decisions must be made quickly and based on available data (which is specifically collected for this purpose). Societal processes are now so complex that without appropriately designed data collection and analysis algorithms the finding of optimal solutions is no longer possible. Leonid Kalachev, Mathematical Sciences

Analysis of textual data

This technology can detect new semantic meaning in existing repositories, assess the growth of information in semantic areas, and yet find the needle of unique semantic meaning in the huge repositories of textual data available in our digital world. Joel Henry, Computer Science

Preventing hacking

The societal need is the increasing dependence of society on technology, and the more rapidly increasing efforts of bad players to disrupt computer systems. Brian Steele, Mathematical Sciences