Data Analytics

Using computational methods to transform both structured and unstructured data into actionable knowledge

Researchers Working in this Area

Related Research Projects

Analysis of academic activity patterns in academic literature

Time frame
2017-Present
Investigators
Jana Diesner, Vetle Torvik
Total funding to date
$25,000.00
Funding agency
Korea Institute of Science and Technology Information

The project team will work on extracting key concepts from scholarly publications and explore techniques for building a taxonomy of extracted concepts by leveraging open knowledge bases (e.g., Wikipedia). The outcome of this process will be evaluated for various science and technology knowledge platform-based analysis services. The techniques, which reduce semantic ambiguity, will analyze…

Big Data-Theoretic Approach to Quantify Organizational Failure Mechanisms in Probabilistic Risk Assessment

Time frame
2015-Present
Investigators
Zahra Mohaghegh, Catherine Blake
Total funding to date
$899,663.00
Funding agency
National Science Foundation

Catastrophic events such as Fukushima and Katrina have made it clear that integrating physical and social causes of failure into a cohesive modeling framework is critical in order to prevent complex technological accidents and to maintain public safety and health. In this research, experts in Probabilistic Risk Assessment (PRA), Organizational Behavior and Information Science and Data…

Computational Impact Assessment of Issue Focused Media and Information Products

Time frame
2015-Present
Investigator
Jana Diesner
Total funding to date
$150,000.00
Funding agency
Ford Foundation

Films are produced, screened and perceived as part of a larger and continuously changing ecosystem that involves multiple stakeholders and themes. This project will measure the impact of social justice documentaries by capturing, modeling and analyzing the map of these stakeholders and themes in a systematic, scalable and analytically rigorous fashion. This solution will result in a validated…

Impact of Data Quality and Provenance

Time frame
2014-Present
Investigator
Jana Diesner
Total funding to date
$130,475.00
Funding agency
Korea Institute of Science and Technology Information

How do limitations and intransparencies in data quality and data provenance bias research outcomes, and how can we detect and mitigate these limitations? For example, we have been investigating the impact of entity resolution errors on network analysis results. We found that commonly reported network metrics and derived implications can strongly deviate from the truth—as established based on…

INDICATOR: An Information System for Monitoring the Health of a Community

Time frame
2007-Present
Investigator
Ian Brooks
Total funding to date
$300,723.00
Funding agency
Centers for Disease Control and Prevention, U.S. Department of Agriculture, Carle Foundation

INDICATOR is a novel information system for collecting, integrating, and analyzing data from multiple sources to provide public health decision makers real-time data on the health of their community. Data comes from sources as varied as emergency department visits, school attendance, veterinary clinics, and social media postings and together have been used to change public policy in outbreak…

INDICATOR

Natural Language Processing for Building and Enhancing Graph Data and Theory

Investigator
Jana Diesner

How can we use user-generated content to construct, infer or refine network data? We have been tackling this problem by leveraging communication content produced and disseminated in social networks to enhance graph data. For example, we have used domain-adjusted sentiment analysis to label graphs with valence values in order to enable triadic balance assessment. The resulting method enables…

NCSA Faculty Fellowship: Predictive Modeling for Impact Assessment

Time frame
2015-Present
Investigator
Jana Diesner
Total funding to date
$24,323.00
Funding agency
National Center for Supercomputing Applications

Assistant Professor Jana Diesner a received an Faculty Fellowship and seed funding for her project, “Predictive Modeling for Impact Assessment,” from the National Center for Supercomputing Applications (NCSA). Diesner collaborates closely with NCSA scientists on the project, which builds on her work developing computational solutions…

Pathtracker: A smartphone-based system for mobile infectious disease detection and epidemiology

Time frame
2015-Present
Investigator
Ian Brooks
Total funding to date
$1,005,692.00
Funding agency
National Science Foundation

This project will develop a mobile sensor technology for performing detection and identification of viral and bacterial pathogens. By means of a smartphone-based detection instrument, the results are shared with a cloud-based data management service that will enable physicians to rapidly visualize the geographical and temporal spread of infectious disease. When deployed by a community of…

Single Interface for Music Score Searching and Analysis

Time frame
2015-Present
Investigator
J. Stephen Downie
Total funding to date
$15,000.00
Funding agency
Social Sciences and Humanities Research Council of Canada

Music prints and manuscripts created over the past thousand years sit on the shelves of libraries and museums around the globe. As these organizations digitize their collections, images of these scores are increasingly accessible online. However, the musical content remains difficult to search.

Google Books and HathiTrust have already made it possible to search the content of text…

Socio-technical Data Analytics (SODA) Education

Time frame
2012-2016
Investigator
Catherine Blake
Total funding to date
$498,777.00
Funding agency
Institute of Museum and Library Services

This project will create both a master’s and doctoral-level specialization in Socio-technical Data Analytics (SODA). Partnerships with local researchers and businesses who already work with large data-sets will enable master's graduates to receive first-hand experience with both the social and technical implications of large digital data collections, and thus be well-prepared for leadership…

Related News Articles