Collection-Level Subject Access in Aggregations of Digital Collections: Metadata Application and Use

Problems in subject access to information organization systems have been under investigation for a long time. Focusing on item-level information discovery and access, researchers have identified a range of subject access problems, including quality and application of metadata, as well as the complexity of user knowledge required for successful subject exploration. While aggregations of digital collections built in the United States and abroad generate collection-level metadata of various levels of granularity and richness, no research has yet focused on the role of collection-level metadata in user interaction with these aggregations. This dissertation research sought to bridge this gap by answering the question “How does collection-level metadata mediate scholarly subject access to aggregated digital collections?” This goal was achieved using three research methods: • in-depth comparative content analysis of collection-level metadata in three large-scale aggregations of cultural heritage digital collections: Opening History, American Memory, and The European Library • transaction log analysis of user interactions, with Opening History, and • interview and observation data on academic historians interacting with two aggregations: Opening History and American Memory. It was found that subject-based resource discovery is significantly influenced by collection-level metadata richness. The richness includes such components as: 1) describing collection’s subject matter with mutually-complementary values in different metadata fields, and 2) a variety of collection properties/characteristics encoded in the free-text Description field, including types and genres of objects in a digital collection, as well as topical, geographic and temporal coverage are the most consistently represented collection characteristics in free-text Description fields. Analysis of user interactions with aggregations of digital collections yields a number of interesting findings. Item-level user interactions were found to occur more often than collection-level interactions. Collection browse is initiated more often than search, while subject browse (topical and geographic) is used most often. Majority of collection search queries fall within FRBR Group 3 categories: object, concept, and place. Significantly more object, concept, and corporate body searches and less individual person, event and class of persons searches were observed in collection searches than in item searches. While collection search is most often satisfied by Description and/or Subjects collection metadata fields, it would not retrieve a significant proportion of collection records without controlled-vocabulary subject metadata (Temporal Coverage, Geographic Coverage, Subjects, and Objects), and free-text metadata (the Description field). Observation data shows that collection metadata records in Opening History and American Memory aggregations are often viewed. Transaction log data show a high level of engagement with collection metadata records in Opening History, with the total page views for collections more than 4 times greater than item page views. Scholars observed viewing collection records valued descriptive information on provenance, collection size, types of objects, subjects, geographic coverage, and temporal coverage information. They also considered the structured display of collection metadata in Opening History more useful than the alternative approach taken by other aggregations, such as American Memory, which displays only the free-text Description field to the end-user. The results extend the understanding of the value of collection-level subject metadata, particularly free-text metadata, for the scholarly users of aggregations of digital collections. The analysis of the collection metadata created by three large-scale aggregations provides a better understanding of collection-level metadata application patterns and suggests best practices. This dissertation is also the first empirical research contribution to test the FRBR model as a conceptual and analytic framework for studying collection-level subject access.

A new age of fuel performance code criteria studied through advanced atomistic simulation techniques

A fundamental step in understanding the effects of irradiation on metallic uranium and uranium dioxide ceramic fuels, or any material, must start with the nature of radiation damage on the atomic level. The atomic damage displacement results in a multitude of defects that influence the fuel performance. Nuclear reactions are coupled, in that changing one variable will alter others through feedback. In the field of fuel performance modeling, these difficulties are addressed through the use of empirical models rather than models based on first principles. Empirical models can be used as a predictive code through the careful manipulation of input variables for the limited circumstances that are closely tied to the data used to create the model. While empirical models are efficient and give acceptable results, these results are only applicable within the range of the existing data. This narrow window prevents modeling changes in operating conditions that would invalidate the model as the new operating conditions would not be within the calibration data set. This work is part of a larger effort to correct for this modeling deficiency. Uranium dioxide and metallic uranium fuels are analyzed through a kinetic Monte Carlo code (kMC) as part of an overall effort to generate a stochastic and predictive fuel code. The kMC investigations include sensitivity analysis of point defect concentrations, thermal gradients implemented through a temperature variation mesh-grid, and migration energy values. In this work, fission damage is primarily represented through defects on the oxygen anion sublattice. Results were also compared between the various models. Past studies of kMC point defect migration have not adequately addressed non-standard migration events such as clustering and dissociation of vacancies. As such, the General Utility Lattice Program (GULP) code was utilized to generate new migration energies so that additional non-migration events could be included into kMC code in the future for more comprehensive studies. Defect energies were calculated to generate barrier heights for single vacancy migration, clustering and dissociation of two vacancies, and vacancy migration while under the influence of both an additional oxygen and uranium vacancy.

Microlepidoptera of Illinois hill prairies

Among insects, which are the most diverse eukaryotic group on earth, Lepidoptera is one of four enormously diverse orders, with approximately 10,000 described species in North America. Within the order, Nearctic “microlepidoptera,” which represent an overwhelmingly large percentage of diversity within the order, remain poorly known despite their ecological importance in many plant communities. In this thesis, I undertook several studies of microlepidoptera diversity in a natural community type (hill prairie) and a managed community type (biofuel feedstock). In two Illinois hill prairies differing in size, latitude, and plant composition, alpha diversity of Pyraloidea and Tortricidae was similar, but the prairies were found to support different sets of species of these moth groups. It is concluded that the similarity in alpha diversity occurs because the larger prairie supports primarily a complement of moth species that feed as larvae on prairie plants (especially species of Asteraceae and Fabaceae), whereas the moths collected in the small prairie represent relatively few prairie-associated species, plus a large component of species that feed as larvae on deciduous trees that surround the prairie. This agrees with the finding of high beta diversity of moths between the sites, which reflects a high level of larval hostplant specificity in most species of Pyraloidea and Tortricidae. Based on published information plus observations made on microlepidoptera collected during the course of this study, 31 families of basal microlepidoptera were reviewed with an aim toward evaluating the likelihood of their including species that are dependent on tallgrass prairie. Of these families, 12 were evaluated as possible, and two as likely or certain, to include prairie-dependent species. In a comparison of moth diversity in light-trap samples from corn, miscanthus, switchgrass, and native prairie, alpha diversity was highest in prairie and was higher in switchgrass than in the other two biofuel crops. Moth species complements generally were similar among the biofuel crops, and prairie shared higher species complementarity with switchgrass than with corn or miscanthus. These findings suggest that large-scale conversion of land to biofuel crops may, to a substantial degree, detrimentally affect arthropod biodiversity, with a resulting loss of valuable arthropod-derived ecosystem services both within the cropping systems and in the surrounding landscape. During the course of this study, rearing efforts yielded two species of moths of the family Gelechiidae, both of which are monophagous leaf feeders on leadplant, Amorpha canescens (Fabaceae). Because these moths are restricted to tallgrass prairie, they are likely to be of interest to conservation biologists. In the interest of naming the moths to facilitate communication regarding them, and to augment our taxonomic knowledge of their respective genera, the moths are described, and diagnoses are provided to differentiate them from similar, related species.