Research and Informatics Division, University Libraries

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https://hdl.handle.net/10919/71806

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Browsing Research and Informatics Division, University Libraries by Department "Computer Science"

Now showing 1 - 6 of 6
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    Integration of VT ETD-db with Banner
    Volpe, James; McMillan, Gail; Fox, Edward A. (Department of Computer Science, Virginia Polytechnic Institute & State University, 2008)
    The Electronic Thesis and Dissertation database (ETD-db) was developed at Virginia Tech by Digital Library and Archives for the VT Graduate School and the Networked Digital Library of Theses and Dissertations (NDLTD). The software is freely available and over 100 universities worldwide have implemented the ETD-db system. One drawback of the system is the dependence on user keyed data. At Virginia Tech, like most other universities, there is an administrative database that could provide much of this information. The Banner Administrative System is the central administration system at Virginia Tech. Banner’s underlying database software is from Oracle. This paper will demonstrate how the ETD-db can be seamlessly integrated with an Oracle database or more specifically the Banner Administrative System, to improve the integrity of the data for ETDs.
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    On Utilization of Contributory Storage in Desktop Grids
    Miller, Chreston; Butler, Patrick; Shah, Ankur; Butt, Ali R. (Department of Computer Science, Virginia Polytechnic Institute & State University, 2007)
    The availability of desktop grids and shared computing platforms has popularized the use of contributory resources, such as desktops, as computing substrates for a variety of applications. However, addressing the exponentially growing storage demands of applications, especially in a contributory environment, remains a challenging research problem. In this report, we propose a transparent distributed storage system that harnesses the storage contributed by grid participants arranged in a peer-to-peer network to yield a scalable, robust, and self-organizing system. The novelty of our work lies in (i) design simplicity to facilitate actual use; (ii) support for easy integration with grid platforms; (iii) ingenious use of striping and error coding techniques to support very large data files; and (iv) the use of multicast techniques for data replication. Experimental results through simulations and an actual implementation show that our system can provide reliable and efficient storage with large file support for desktop grid applications.
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    Protocols
    Singh, Ajeet; Chen, Yinlin; Santhanam, Srinivasa; Zhu, Weihua (2009-10-09)
    This module addresses the concepts, development and implementation of digital library protocols and covers the roles of protocols in information retrieval systems (IR) and Service Oriented Architectures (SOA).
  • Scalable Storage for Digital Libraries
    Mather, Paul (Department of Computer Science, Virginia Polytechnic Institute & State University, 2002-10-01)
    I propose a storage system optimised for digital libraries. Its key features are its heterogeneous scalability; its integration and exploitation of rich semantic metadata associated with digital objects; its use of a name space; and its aggressive performance optimisation in the digital library domain.
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    Science of Digital Libraries(SciDL)
    Fox, Edward A.; Carroll, John M.; Fan, Patrick; Cassel, Lillian N.; Zubair, Mohammad; Maly, Kurt; McMillan, Gail; Ramakrishnan, Naren; Halbert, Martin (Department of Computer Science, Virginia Polytechnic Institute & State University, 2003)
    Our purpose is to ensure that people and institutions better manage information through digital libraries (DLs). Thus we address a fundamental human and social need, which is particularly urgent in the modern Information (and Knowledge) Age. Our goal is to significantly advance both the theory and state-of-theart of DLs (and other advanced information systems) - thoroughly validating our approach using highly visible testbeds. Our research objective is to leverage our formal, theory-based approach to the problems of defining, understanding, modeling, building, personalizing, and evaluating DLs. We will construct models and tools based on that theory so organizations and individuals can easily create and maintain fully functional DLs, whose components can interoperate with corresponding components of related DLs. This research should be highly meritorious intellectually. We bring together a team of senior researchers with expertise in information retrieval, human-computer interaction, scenario-based design, personalization, and componentized system development and expect to make important contributions in each of those areas. Of crucial import, however, is that we will integrate our prior research and experience to achieve breakthrough advances in the field of DLs, regarding theory, methodology, systems, and evaluation. We will extend the 5S theory, which has identified five key dimensions or onstructs underlying effective DLs: Streams, Structures, Spaces, Scenarios, and Societies. We will use that theory to describe and develop metamodels, models, and systems, which can be tailored to disciplines and/or groups, as well as personalized. We will disseminate our findings as well as provide toolkits as open source software, encouraging wide use. We will validate our work using testbeds, ensuring broad impact. We will put powerful tools into the hands of digital librarians so they may easily plan and configure tailored systems, to support an extensible set of services, including publishing, discovery, searching, browsing, recommending, and access control, handling diverse types of collections, and varied genres and classes of digital objects. With these tools, end-users will for be able to design personal DLs. Testbeds are crucial to validate scientific theories and will be thoroughly integrated into SciDL research and evaluation. We will focus on two application domains, which together should allow comprehensive validation and increase the significance of SciDL's impact on scholarly communities. One is education (through CITIDEL); the other is libraries (through DLA and OCKHAM). CITIDEL deals with content from publishers (e.g, ACM Digital Library), corporate research efforts e.g., CiteSeer), volunteer initiatives (e.g., DBLP, based on the database and logic rogramming literature), CS departments (e.g., NCSTRL, mostly technical reports), educational initiatives (e.g., Computer Science Teaching Center), and universities (e.g., theses and dissertations). DLA is a unit of the Virginia Tech library that virtually publishes scholarly communication such as faculty-edited journals and rare and unique resources including image collections and finding aids from Special Collections. The OCKHAM initiative, calling for simplicity in the library world, emphasizes a three-part solution: lightweightprotocols, component-based development, and open reference models. It provides a framework to research the deployment of the SciDL approach in libraries. Thus our choice of testbeds also will nsure that our research will have additional benefit to and impact on the fields of computing and library and information science, supporting transformations in how we learn and deal with information.
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    Structural Model Discovery in Temporal Event Data Streams
    Miller, Chreston (Virginia Tech, 2013-04-23)
    This dissertation presents a unique approach to human behavior analysis based on expert guidance and intervention through interactive construction and modification of behavior models. Our focus is to introduce the research area of behavior analysis, the challenges faced by this field, current approaches available, and present a new analysis approach: Interactive Relevance Search and Modeling (IRSM). More intelligent ways of conducting data analysis have been explored in recent years. Ma- chine learning and data mining systems that utilize pattern classification and discovery in non-textual data promise to bring new generations of powerful "crawlers" for knowledge discovery, e.g., face detection and crowd surveillance. Many aspects of data can be captured by such systems, e.g., temporal information, extractable visual information - color, contrast, shape, etc. However, these captured aspects may not uncover all salient information in the data or provide adequate models/patterns of phenomena of interest. This is a challenging problem for social scientists who are trying to identify high-level, conceptual patterns of human behavior from observational data (e.g., media streams). The presented research addresses how social scientists may derive patterns of human behavior captured in media streams. Currently, media streams are being segmented into sequences of events describing the actions captured in the streams, such as the interactions among humans. This segmentation creates a challenging data space to search characterized by non- numerical, temporal, descriptive data, e.g., Person A walks up to Person B at time T. This dissertation will present an approach that allows one to interactively search, identify, and discover temporal behavior patterns within such a data space. Therefore, this research addresses supporting exploration and discovery in behavior analysis through a formalized method of assisted exploration. The model evolution presented sup- ports the refining of the observer\'s behavior models into representations of their understanding. The benefit of the new approach is shown through experimentation on its identification accuracy and working with fellow researchers to verify the approach\'s legitimacy in analysis of their data.