Data Science Commons^™

Data Science In Statistics Curricula: Preparing Students To “Think With Data”, J. Hardin, R. Hoerl, Nicholas J. Horton, D. Nolan, B. Baumer, O. Hall-Holt, P. Murrell, R. Peng, P. Roback, D. Temple Lang, M. D. Ward

Statistical and Data Sciences: Faculty Publications

A growing number of students are completing undergraduate degrees in statistics and entering the workforce as data analysts. In these positions, they are expected to understand how to use databases and other data warehouses, scrape data from Internet sources, program solutions to complex problems in multiple languages, and think algorithmically as well as statistically. These data science topics have not traditionally been a major component of undergraduate programs in statistics. Consequently, a curricular shift is needed to address additional learning outcomes. The goal of this article is to motivate the importance of data science proficiency and to provide examples and …

Big Data, Bigger Dilemmas: A Critical Review, Hamid Ekbia, Michael Mattioli, Inna Koupe, G. Arave, Ali Ghazinejad, Timothy Bowman, Venkatq R. Suri, Tsou Andrew, Scott Weingart, Cassidy R. Sugimoto

Articles by Maurer Faculty

The recent interest in Big Data has generated a broad range of new academic, corporate, and policy practices along with an evolving debate among its proponents, detractors, and skeptics. While the practices draw on a common set of tools, techniques, and technologies, most contributions to the debate come either from a particular disciplinary perspective or with a focus on a domain-specific issue. A close examination of these contributions reveals a set of common problematics that arise in various guises and in different places. It also demonstrates the need for a critical synthesis of the conceptual and practical dilemmas surrounding Big …

Degradation Science: Mesoscopic Evolution And Temporal Analytics Of Photovoltaic Energy Materials, Roger H. French, Rudolf Podgornik, Timothy J. Peshek, Laura S. Bruckman, Yifan Xu, Nicholas R. Wheeler, Abdulkerim Gok, Yang Hu, Mohammad A. Hossain, Devin A. Gordon, Pei Zhao, Jiayang Sun, Guo-Qiang Zhang

Faculty Scholarship

Based on recent advances in nanoscience, data science and the availability of massive real-world datastreams, the mesoscopic evolution of mesoscopic energy materials can now be more fully studied. The temporal evolution is vastly complex in time and length scales and is fundamentally challenging to scientific understanding of degradation mechanisms and pathways responsible for energy materials evolution over lifetime. We propose a paradigm shift towards mesoscopic evolution modeling, based on physical and statistical models, that would integrate laboratory studies and real-world massive datastreams into a stress/mechanism/response framework with predictive capabilities. These epidemiological studies encompass the variability in properties that affect performance …

Time Series Analysis For Psychological Research: Examining And Forecasting Change, Andrew T. Jebb, Louis Tay, Wei Wang, Qiming Huang

Publications and Research

Psychological research has increasingly recognized the importance of integrating temporal dynamics into its theories, and innovations in longitudinal designs and analyses have allowed such theories to be formalized and tested. However, psychological researchers may be relatively unequipped to analyze such data, given its many characteristics and the general complexities involved in longitudinal modeling. The current paper introduces time series analysis to psychological research, an analytic domain that has been essential for understanding and predicting the behavior of variables across many diverse fields. First, the characteristics of time series data are discussed. Second, different time series modeling techniques are surveyed that …

Investigating The Efficacy Of Algorithmic Student Modelling In Predicting Students At Risk Of Failing In The Early Stages Of Tertiary Education: Case Study Of Experience Based On First Year Students At An Institute Of Technology In Ireland., Geraldine Gray

Doctoral

The application of data analytics to educational settings is an emerging and growing research area. Much of the published works to-date are based on ever-increasing volumes of log data that are systematically gathered in virtual learning environments as part of module delivery. This thesis took a unique approach to modelling academic performance; it is a first study to model indicators of students at risk of failing in first year of tertiary education, based on data gathered prior to commencement of first year, facilitating early engagement with at-risk students.

The study was conducted over three years, in 2010 through 2012, and …

Effects Of Data Replication On Data Exfiltration In Mobile Ad Hoc Networks Utilizing Reactive Protocols, Corey T. Willinger

Theses and Dissertations

A swarm of autonomous UAVs can provide a significant amount of ISR data where current UAV assets may not be feasible or practical. As such, the availability of the data the resides in the swarm is a topic that will benefit from further investigation. This thesis examines the impact of le replication and swarm characteristics such as node mobility, swarm size, and churn rate on data availability utilizing reactive protocols. This document examines the most prominent factors affecting the networking of nodes in a MANET. Factors include network routing protocols and peer-to-peer le protocols. It compares and contrasts several open …

The Role Of Citizens In Detecting And Responding To A Rapid Marine Invasion, Steven B. Scyphers, Sean P. Powers, J. Lad Akins, J. Marcus Drymon, Charles W. Martin, Zeb H. Schobernd, Pamela J. Schofield, Robert L. Shipp, Theodore S. Switzer

University Faculty and Staff Publications

Documenting and responding to species invasions requires innovative strategies that account for ecological and societal complexities. We used the recent expansion of Indo-Pacific lionfish (Pterois volitans/miles) throughout northern Gulf of Mexico coastal waters to evaluate the role of stakeholders in documenting and responding to a rapid marine invasion. We coupled an online survey of spearfishers and citizen science monitoring programs with traditional fishery-independent data sources and found that citizen observations documented lionfish 1–2 years earlier and more frequently than traditional reef fish monitoring programs. Citizen observations first documented lionfish in 2010 followed by rapid expansion and proliferation in …

Engineering Analytics: Research Into The Governance Structure Needed To Integrate The Dominant Design Methodologies, Teddy Steven Cotter

Engineering Management & Systems Engineering Faculty Publications

In the ASEM-IAC 2014, Cotter (2014) explored the current state of engineering design, identified the dominate approaches to engineering design, discussed potential contributions from the new field of data analytics to engineering design, and proposed an Engineering Analytics framework that integrates the dominate engineering design approaches and data analytics within a human-intelligence/machine-intelligence (HI-MI) design architecture. This paper reports research applying ontological engineering to integrate the dominate engineering design methodologies into a systemic engineering design decision governance architecture.

Reasoning Over Taxonomic Change: Exploring Alignments For The Perelleschus Use Case, Nico M. Franz, Mingmin Chen, Shizhuo Yu, Parisa Kianmajd, Shaun Bowers, Bertram Ludäscher

Computer Science Faculty Scholarship

Classifications and phylogenetic inferences of organismal groups change in light of new insights. Over time these changes can result in an imperfect tracking of taxonomic perspectives through the re-/use of Code-compliant or informal names. To mitigate these limitations, we introduce a novel approach for aligning taxonomies through the interaction of human experts and logic reasoners. We explore the performance of this approach with the Perelleschus use case of Franz & Cardona-Duque (2013). The use case includes six taxonomies published from 1936 to 2013, 54 taxonomic concepts (i.e., circumscriptions of names individuated according to their respective source publications), and 75 expert-asserted …

Statistical Engineering: A Causal-Stochastic Modeling Research Update, Teddy Steven Cotter

Engineering Management & Systems Engineering Faculty Publications

In the ASEM-IAC 2012, Cotter (2012) summarized prior works that led to the proposal for statistical engineering, identified the gaps in knowledge that statistical engineering needs to address, explored additional gaps in knowledge not addressed in the prior works, set forth a working definition of and body of knowledge for statistical engineering, and set forth proposals of potential systems contributions the Engineering Management profession could make toward the development of statistical engineering. In 2014, the ASQ Statistics Division, DOT&E, NASA, and IDA co-sponsored a Statistical Engineering Agreement to jointly research development of the discipline of statistical engineering. The statistics community …

Adaptive Graph Construction For Isomap Manifold Learning, Loc Tran, Zezhong Zheng, Guoquing Zhou, Jiang Li, Karen O. Egiazarian (Ed.), Sos S. Agaian (Ed.), Atanas P. Gotchev (Ed.)

Electrical & Computer Engineering Faculty Publications

Isomap is a classical manifold learning approach that preserves geodesic distance of nonlinear data sets. One of the main drawbacks of this method is that it is susceptible to leaking, where a shortcut appears between normally separated portions of a manifold. We propose an adaptive graph construction approach that is based upon the sparsity property of the ℓ₁ norm. The ℓ₁ enhanced graph construction method replaces k-nearest neighbors in the classical approach. The proposed algorithm is first tested on the data sets from the UCI data base repository which showed that the proposed approach performs better than …