Graph data, especially large graph data, come up in many domains, such as social networks, the map of science, biological data, and even knitting! This presents a problem when we consider visualizing these structures. Layouts must be chosen carefully so that the structure of the graph is visible. Some graphs are large enough and connected enough…

Graph Signal Processing (GSP) plays a crucial role in addressing the growing need for information processing across networks, especially in tasks like supervised classification. However, the success of GSP in such tasks hinges on accurately identifying the underlying relational structures, which are often not readily available and must be inferred…

All chemistry students must develop competency in analyzing and making sense of data. However, there are many difficulties that chemistry students may experience while analyzing data. Many students may not use relevant prior knowledge to aid in making sense of data, or they may not form conclusions using all the data provided. Additionally, prior…

Community colleges are continually being faced with pressures to use data to inform decisions. These pressures arise from a triage of factors, including accountability, accreditation, and student success initiatives. Yet, as these demands continue, research has shown that community colleges struggle to institutionalize data-informed decision…

Charter schools exist under the umbrella of public education, but are not subject to the same level of public oversight or accountability measures as traditional public schools in North Carolina and many other states (BiFulco and Ladd, 2006, Bettinger, 2004). There is a lack of easily accessible efficiency data on charter schools. The primary aim…

With the development of PC, internet as well as mobile devices, we are facing a data exploding era. On one hand, more and more features can be collected to describe the data, making the size of the data descriptor larger and larger. On the other hand, the number of data itself explodes and can be collected from multiple resources. When the data…

Large real-world graph (a.k.a network, relational) data are omnipresent, in online media, businesses, science, and the government. Analysis of these massive graphs is crucial, in order to extract descriptive and predictive knowledge with many commercial, medical, and environmental applications. In addition to its general structure, knowing what…

Tabular data is pervasive in the form of spreadsheets and relational databases. Although tables often describe multivariate data without explicit network semantics, it may be advantageous to explore the data modeled as a graph or network for analysis. Even when a given table design conveys some static network semantics, analysts may want to look…

In light of the prosperity of online social media, Web users are shifting from data consumers to data producers. To catch the pulse of this rapidly changing world, it is critical to transform online social media data to information and to knowledge. This dissertation centers on the issue of modeling the dynamics of user communities, trending…

Visual analysis is the primary method of analyzing data in single-subject methodology, which is the predominant research method used in the fields of applied behavior analysis and special education. Previous research on the reliability of visual analysis suggests that judges often disagree about what constitutes an intervention effect. Considering…

Minimal research has investigated training packages used to teach professional staff how to implement functional analysis procedures and to interpret data gathered during functional analysis. The current investigation used video-based training with role-play and feedback to teach six professionals in a clinical setting to implement procedures of a…

Biomedical research has produced vast amounts of new information in the last decade but has been slow to find its use in clinical applications. Data from disparate sources such as genetic studies and summary data from published literature have been amassed, but there is a significant gap, primarily due to a lack of normative methods, in combining…

We studied the problem of constraint-based pattern mining for three different data formats, item-set, sequence and graph, and focused on mining patterns of large sizes. Colossal patterns in each data formats are studied to discover pruning properties that are useful for direct mining of these patterns. For item-set data, we observed robustness of…

The variety and complexity of potentially-related data resources available for querying--webpages, databases, data warehouses--has been growing ever more rapidly. There is a growing need to pose integrative queries "across" multiple such sources, exploiting foreign keys and other means of interlinking data to merge information from diverse…

This dissertation concerns kindergarteners' and second graders' invented representations of motion, their interactions with conventional representations of motion built from the child's movement in front of a motion detector and using real-time graphing tools, and any changes in the invented representations that this interaction brings about. We…