UMD Theses and Dissertations
Permanent URI for this collectionhttp://hdl.handle.net/1903/3
New submissions to the thesis/dissertation collections are added automatically as they are received from the Graduate School. Currently, the Graduate School deposits all theses and dissertations from a given semester after the official graduation date. This means that there may be up to a 4 month delay in the appearance of a given thesis/dissertation in DRUM.
More information is available at Theses and Dissertations at University of Maryland Libraries.
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Item Understanding Scientific Literature Networks: Case Study Evaluations of Integrating Visualizations and Statistics(2011) Gove, Robert Paul; Shneiderman, Ben; Computer Science; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Investigators frequently need to quickly learn new research domains in order to advance their research. This thesis presents five contributions to understanding how software helps researchers explore scientific literature networks. (1) A taxonomy which summarizes capabilities in existing bibliography tools, revealing patterns of capabilities by system type. (2) Six participants in two user studies evaluate Action Science Explorer (ASE), which is designed to create surveys of scientific literature and integrates visualizations and statistics. Users found document-level statistics and attribute rankings to be convenient when beginning literature exploration. (3) User studies also identify users' questions when exploring academic literature, which include examining the evolution of a field, identifying author relationships, and searching for review papers. (4) The evaluations suggest shortcomings of ASE, and this thesis outlines improvements to ASE and lists user requirements for bibliographic exploration. (5) I recommend strategies for evaluating bibliographic exploration tools based on experiences evaluating ASE.Item Studying the Relationships of Information Technology Concepts(2011) Tsui, Chia-jung; Wang, Ping; Library & Information Services; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Different information technology concepts are related in complex ways. How can the relationships among multiple IT concepts be described and analyzed in a scalable way? It is a challenging research question, not only because of the complex relationships among IT concepts, but also due to lack of reliable methods. Seeking to meet the challenge, this dissertation offers a computational approach for analyzing, visualizing, and understanding the relationships among IT concepts. The dissertation contains five empirical studies. The first study employs Kullback-Leibler (KL) divergence to compare the semantic similarity of forty-seven IT concepts discussed in a trade magazine over a ten-year period. Results show that the similarity of IT concepts can be mapped in a hierarchy and similar technologies demonstrated similar discourses. The second study employs co-occurrence analysis to explore the relationships among fifty IT concepts in six magazines over ten years. Results show general patterns similar to those found in the first study, but with interesting nuances. Together, findings from the first two studies imply reasonable validity of this computational approach. The third study validates and evaluates the approach, making use of an existing thesaurus as ground truth. Results show that the co-occurrence-based IT classification outperforms the KL divergence-based IT classification in agreeing with the ground truth. The fourth study is a survey of information professionals who help evaluate this computational approach. Results are generally consistent with the findings in the previous study. The fifth study explores the co-occurrence analysis further and has generated IT classifications very much similar to the ground truth. The computational approach developed in this dissertation is expected to help IT practitioners and researchers make sense of the numerous concepts in the IT field. Overall, the dissertation establishes a good foundation for studying the relationships of IT concepts in a representative, dynamic, and scalable way.Item INFORMATION THEORETIC SECRET KEY GENERATION: STRUCTURED CODES AND TREE PACKING(2010) NITINAWARAT, SIRIN; Narayan, Prakash; Electrical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)This dissertation deals with a multiterminal source model for secret key generation by multiple network terminals with prior and privileged access to a set of correlated signals complemented by public discussion among themselves. Emphasis is placed on a characterization of secret key capacity, i.e., the largest rate of an achievable secret key, and on algorithms for key construction. Various information theoretic security requirements of increasing stringency: weak, strong and perfect secrecy, as well as different types of sources: finite-valued and continuous, are studied. Specifically, three different models are investigated. First, we consider strong secrecy generation for a discrete multiterminal source model. We discover a connection between secret key capacity and a new source coding concept of ``minimum information rate for signal dissemination,'' that is of independent interest in multiterminal data compression. Our main contribution is to show for this discrete model that structured linear codes suffice to generate a strong secret key of the best rate. Second, strong secrecy generation is considered for models with continuous observations, in particular jointly Gaussian signals. In the absence of suitable analogs of source coding notions for the previous discrete model, new techniques are required for a characterization of secret key capacity as well as for the design of algorithms for secret key generation. Our proof of the secret key capacity result, in particular the converse proof, as well as our capacity-achieving algorithms for secret key construction based on structured codes and quantization for a model with two terminals, constitute the two main contributions for this second model. Last, we turn our attention to perfect secrecy generation for fixed signal observation lengths as well as for their asymptotic limits. In contrast with the analysis of the previous two models that relies on probabilistic techniques, perfect secret key generation bears the essence of ``zero-error information theory,'' and accordingly, we rely on mathematical techniques of a combinatorial nature. The model under consideration is the ``Pairwise Independent Network'' (PIN) model in which every pair of terminals share a random binary string, with the strings shared by distinct pairs of terminals being mutually independent. This model, which is motivated by practical aspects of a wireless communication network in which terminals communicate on the same frequency, results in three main contributions. First, the concept of perfect omniscience in data compression leads to a single-letter formula for the perfect secret key capacity of the PIN model; moreover, this capacity is shown to be achieved by linear noninteractive public communication, and coincides with strong secret key capacity. Second, taking advantage of a multigraph representation of the PIN model, we put forth an efficient algorithm for perfect secret key generation based on a combinatorial concept of maximal packing of Steiner trees of the multigraph. When all the terminals seek to share perfect secrecy, the algorithm is shown to achieve capacity. When only a subset of terminals wish to share perfect secrecy, the algorithm is shown to achieve at least half of it. Additionally, we obtain nonasymptotic and asymptotic bounds on the size and rate of the best perfect secret key generated by the algorithm. These bounds are of independent interest from a purely graph theoretic viewpoint as they constitute new estimates for the maximum size and rate of Steiner tree packing of a given multigraph. Third, a particular configuration of the PIN model arises when a lone ``helper'' terminal aids all the other ``user'' terminals generate perfect secrecy. This model has special features that enable us to obtain necessary and sufficient conditions for Steiner tree packing to achieve perfect secret key capacity.Item Long-term Information Preservation and Access(2010) Song, Sang Chul; JaJa, Joseph F; Electrical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)An unprecedented amount of information encompassing almost every facet of human activities across the world is generated daily in the form of zeros and ones, and that is often the only form in which such information is recorded. A good fraction of this information needs to be preserved for periods of time ranging from a few years to centuries. Consequently, the problem of preserving digital information over a long-term has attracted the attention of many organizations, including libraries, government agencies, scientific communities, and individual researchers. In this dissertation, we address three issues that are critical to ensure long-term information preservation and access. The first concerns the core requirement of how to guarantee the integrity of preserved contents. Digital information is in general very fragile because of the many ways errors can be introduced, such as errors introduced because of hardware and media degradation, hardware and software malfunction, operational errors, security breaches, and malicious alterations. To address this problem, we develop a new approach based on efficient and rigorous cryptographic techniques, which will guarantee the integrity of preserved contents with extremely high probability even in the presence of malicious attacks. Our prototype implementation of this approach has been deployed and actively used in the past years in several organizations, including the San Diego Super Computer Center, the Chronopolis Consortium, North Carolina State University, and more recently the Government Printing Office. Second, we consider another crucial component in any preservation system - searching and locating information. The ever-growing size of a long-term archive and the temporality of each preserved item introduce a new set of challenges to providing a fast retrieval of content based on a temporal query. The widely-used cataloguing scheme has serious scalability problems. The standard full-text search approach has serious limitations since it does not deal appropriately with the temporal dimension, and, in particular, is incapable of performing relevancy scoring according to the temporal context. To address these problems, we introduce two types of indexing schemes - a location indexing scheme, and a full-text search indexing scheme. Our location indexing scheme provides optimal operations for inserting and locating a specific version of a preserved item given an item ID and a time point, and our full-text search indexing scheme efficiently handles the scalability problem, supporting relevancy scoring within the temporal context at the same time. Finally, we address the problem of organizing inter-related data, so that future accesses and data exploration can be quickly performed. We, in particular, consider web contents, where we combine a link-analysis scheme with a graph partitioning scheme to put together more closely related contents in the same standard web archive container. We conduct experiments that simulate random browsing of preserved contents, and show that our data organization scheme greatly minimizes the number of containers needed to be accessed for a random browsing session. Our schemes have been tested against real-world data of significant scale, and validated through extensive empirical evaluations.Item A DATA ANALYTICAL FRAMEWORK FOR IMPROVING REAL-TIME, DECISION SUPPORT SYSTEMS IN HEALTHCARE(2010) Yahav, Inbal; Shmeuli, Galit; Business and Management: Decision & Information Technologies; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)In this dissertation we develop a framework that combines data mining, statistics and operations research methods for improving real-time decision support systems in healthcare. Our approach consists of three main concepts: data gathering and preprocessing, modeling, and deployment. We introduce the notion of offline and semi-offline modeling to differentiate between models that are based on known baseline behavior and those based on a baseline with missing information. We apply and illustrate the framework in the context of two important healthcare contexts: biosurveillance and kidney allocation. In the biosurveillance context, we address the problem of early detection of disease outbreaks. We discuss integer programming-based univariate monitoring and statistical and operations research-based multivariate monitoring approaches. We assess method performance on authentic biosurveillance data. In the kidney allocation context, we present a two-phase model that combines an integer programming-based learning phase and a data-analytical based real-time phase. We examine and evaluate our method on the current Organ Procurement and Transplantation Network (OPTN) waiting list. In both contexts, we show that our framework produces significant improvements over existing methods.Item SENSEMAKING: CONCEPTUAL CHANGES, COGNITIVE MECHANISMS, AND STRUCTURAL REPRESENTATIONS. A QUALITATIVE USER STUDY(2010) Zhang, Pengyi; Soergel, Dagobert; Library & Information Services; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)The purpose of this thesis is to improve our understanding of sensemaking process as a basis for building better systems to assist sensemaking. Sensemaking is the task of creating an understanding of a problem or task so that further actions may be taken in an informed manner. Sensemaking is a pre-requisite for many other tasks such as decision making and problem solving. An important part of sensemaking involves making clear the interrelated concepts and their relationships in a problem or task space. This research investigated the question of how users create and use structured representations for sensemaking. It proposed and refined an iterative sensemaking model building upon previous sensemaking research, learning theories, cognitive psychology and task-based information seeking and use. In particular, the study focused on the processes, conceptual changes, and cognitive mechanisms used during users' sensemaking tasks. The qualitative, multi-case user study investigated how a sample of fifteen users working with news writing and business analysis tasks structure their conceptual space with the assistance of note-taking and concept mapping tools. Data on the sensemaking process were collected from multiple sources including think-aloud protocols, screen movement recordings, interviews, and intermediate and final work products. Using the iterative sensemaking model as an analytical and descriptive framework, the study captured the often idiosyncratic paths sensemakers took, ranging from planned, systematic to rather random, ad hoc patterns of "search--sensemaking" iterations. Findings also revealed various ways in which the iterations started and exited, which suggested that the heterogeneous patterns of sensemaking lie in the shifts from one iteration to the next, rather than in the iterations themselves. The knowledge structure was updated by accretion, tuning, and restructuring to produce the final knowledge representation and sensemaking product. Several cognitive mechanisms were used in processing new information, examining concepts and relationships, and examining anomalies and inconsistencies. They were used in bottom-up, top-down, and combined fashions to move the processes along and to trigger conceptual changes to the knowledge structure of users. Based on these findings, the study argues that information system that aimed to assist sensemaking should provide an architecture that links structure, data, and sources that can be represented and manipulated in multiple formats. It should also provide integrated assistances at the task and cognitive mechanism levels. The research contributes to sensemaking research by extending existing descriptive sensemaking models with an analytical framework that incorporates conceptual changes to the knowledge structure and cognitive mechanisms that trigger the processes and conceptual changes. Furthermore, the research identified core issues in designing information systems to assist sensemaking tasks and suggested design implications for sensemaking tools that may be useful in many settings such as learning, knowledge creation, organization, and sharing.Item Understanding and Supporting Visual Communication within Costume Design Practice(2009) Bradley, Rachael Leigh; Preece, Jennifer J; Library & Information Services; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Theatres provide artistic value to many people and generate revenue for communities, yet little research has been conducted to understand or support theatrical designers. Over 1,800 non-profit theatres and 3,522 theatre companies and dinner theatres operate in the United States. In 2008, 11 million people attended 1,587 Broadway shows for a total gross of 894 million dollars. These numbers do not take into account College and community theatres, operas, and ballets, all of which also require costumes. This dissertation studied image search, selection, and use within costume design practice to: 1) understand how image use as a collaborative visual communication tool affects the search and selection process and 2) assist an often overlooked community. Previous research in image search and selection has focused on specific resources or institutions. In contrast, this research used case study methodology to understand image search, selection, and use within the broad context of an image-intensive process. The researcher observed costume designers and other theatre members as they located, selected, shared, discussed, and modified images through an iterative design process resulting in a final set of images, the costumes themselves. The researcher also interviewed participants throughout the design process, photographed artifacts, and conducted a final interview with participants at the end of each case study. The resulting data was coded using grounded theory and guided by previous research. Based on the analysis, the researcher suggests a three-stage model that describes image use in costume design and provides a starting point for understanding image use in other collaborative design practices. Participants used a wide range of analog and digital resources, including personal and institutional collections, but often used the same three search and selection strategies regardless of the resource type. Set building and refinement, image comparison, and tagging were all important features of the image search and selection process but are not well supported in most image search systems. In addition, participants continuously added resources to personal collections for future use on individual productions. This research set out to understand search and selection within the context of collaborative use on a single production, but what became apparent was the central nature of collaboration across productions to the search and selection process itself. Personal networks between costume designers and within the theatre community played a central role in solving challenges costume designers encounter as part of their work. This research bridges a gap in current image research by placing image search and selection within the context of a collaborative design practice. At the same time, it suggests guidelines for developing technology to support a community which has long been overlooked. With additional research, the findings from this research can be extended to apply to the theatrical community as a whole and also to other design professionals.Item Relevance, Rhetoric, and Argumentation: A Cross-Disciplinary Inquiry into Patterns of Thinking and Information Structuring(2009) Huang, Xiaoli; Soergel, Dagobert; Library & Information Services; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)This dissertation research is a multidisciplinary inquiry into topicality, involving an in-depth examination of literatures and empirical data and an inductive development of a faceted typology (containing 227 fine-grained topical relevance relationships and 33 types of presentation relationship). This inquiry investigates a large variety of topical connections beyond topic matching, renders a closer look into the structure of a topic, achieves an enriched understanding of topicality and relevance, and induces a cohesive topic-oriented information architecture that is meaningful across topics and domains. The findings from the analysis contribute to the foundation work of information organization, intellectual access / information retrieval, and knowledge discovery. Using qualitative content analysis, the inquiry focuses on meaning and deep structure: Phase 1 : develop a unified theory-grounded typology of topical relevance relationships through close reading of literature and synthesis of thinking from communication, rhetoric, cognitive psychology, education, information science, argumentation, logic, law, medicine, and art history; Phase 2 : in-depth qualitative analysis of empirical relevance datasets in oral history, clinical question answering, and art image tagging, to examine manifestations of the theory-grounded typology in various contexts and to further refine the typology; the three relevance datasets were used for analysis to achieve variation in form, domain, and context. The typology of topical relevance relationships is structured with three major facets: Functional role of a piece of information plays in the overall structure of a topic or an argument; Mode of reasoning: How information contributes to the user's reasoning about a topic; Semantic relationship: How information connects to a topic semantically. This inquiry demonstrated that topical relevance with its close linkage to thinking and reasoning is central to many disciplines. The multidisciplinary approach allows synthesis and examination from new angles, leading to an integrated scheme of relevance relationships or a system of thinking that informs each individual discipline. The scheme resolving from the synthesis can be used to improve text and image understanding, knowledge organization and retrieval, reasoning, argumentation, and thinking in general, by people and machines.Item Digital Libraries in Schools: The Best Practices of National Board Certified Library Media Specialists(2009) Massey, Sheri Anita; Druin, Allison; Weeks, Ann C.; Library & Information Services; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)This study investigated the digital library integration behaviors of school library media specialists (SLMSs) who have achieved certification from the National Board for Professional Teaching Standards (NBPTS). A qualitative interview study design was chosen to convert tacit knowledge related to digital library use into explicit knowledge that can be shared with others. The goal of this research was to identify behaviors and techniques that exemplary SLMSs share when using digital libraries to support the curriculum in K-12 schools. The researcher interviewed and collected artifacts from 10 local National Board certified SLMSs and analyzed the resulting transcripts and materials using thematic analysis. A preliminary coding scheme was derived from the NBPTS Library Media technology innovation standard, which requires candidates to demonstrate expertise in providing technology access, teaching effective technology use, engaging learners with technology, and using technology to enhance the curriculum. Themes related to these four areas emerged from the data, as did sub-themes in the form of barriers the SLMSs encountered and strategies they developed to meet the standard. The barriers are discussed using Ertmer's (1999) first- and second-order classifications. The strategies are the SLMSs' best practices. To provide digital library access the SLMSs made themselves and their assistants available to learners; demonstrated mental and resource flexibility when they encountered obstacles; and, implemented creative funding strategies. To teach digital library use they used the research process to help students bridge knowledge learned in various contexts; provided training; remained abreast of digital library innovations; and, offered suggestions to product developers. To maintain engagement with digital libraries they used proven teaching techniques that build on strong instructional design principles. Finally, they relied on collaborative relationships when integrating digital libraries. They increased collaboration by building trust among colleagues; extending their reach beyond the SLMC in person and virtually, diversifying their role within the school, and gathering curriculum information to incorporate information literacy skills into lessons. Key implications: encourage SLMS-teacher collaboration, build a knowledge management system that captures expertise and supports SLMS communication, reconsider blocking social networking tools in schools to bridge the disconnect between students' home and school information-related behaviors.Item User Acceptance of Community Emergency Alert Technology: Motivations and Barriers(2009) Wu, Fei; Preece, Jennifer J; Qu, Yan; Library & Information Services; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)The purpose of the study is to investigate the factors that motivate the acceptance of emergency alert technologies that are designated for the community's emergency preparedness and response. By investigating the acceptance case of UMD Alerts at the University of Maryland, I explore three related questions through a three-phase, mixed-methods research design: First, what are the key factors that influence the acceptance and use of emergency alert technology? Second, how are different motivational factors related to the intention to use emergency alert technology? Third, what mechanisms may be integrated into system design and implementation to motivate user acceptance? I identify key motivational factors by reviewing the literature and conducting in-depth interviews. Then, I conduct a survey to examine the relationships between the motivational factors and the intention or behavior of acceptance. Finally, I test the motivational effects of the "subjective norm" - one of the predominant factors derived from the interview study and the survey - in a field experiment. Integrating the findings from these three phases, this research shows that user acceptance of emergency alert technology is affected by a variety of factors that the general technology acceptance model (TAM) fails to take into account. In brief, users may be more motivated to accept such technologies if 1) the meaningful use of the technology can be observed in everyday life; 2) the technology system behavior can be easily controlled; and 3) the diffusion of the technology is promoted through the users' social networks and is compatible with the culture of the user community. This dissertation work demonstrates a "deepening" effort in applying TAM to response technology acceptance and establishes a foundation for challenging new lines of research that more closely examine the motivations and barriers to technology acceptance in sociotechnical contexts.