You limited your search to:
Partner:
UNT College of Information
Decade:
2010-2019
Year:
2010
Collection:
UNT Scholarly Works
- Beyond Size and Search: Building Contextual Mass in Digital Aggregations for Scholarly Use
- This paper discusses building contextual mass in digital aggregations for scholarly use. Abstract: At present there are no established collection development methods for building large-scale digital aggregations. However, to realize the potential of the collective base of digital content and advance scholarship, aggregations must do more than provide search of sizable bodies of content. Informed by empirical understanding of scholarly information practices, the IMLS Digital Collections and Content project developed an aggregation strategy for building Opening History, one of the largest digital cultural heritage aggregations in the country. The strategy applied policy-driven collecting based on the principle of contextual mass, and conspectus-style evaluation of collection-level metadata to identify strong subject areas within the aggregation. Analysis of density, interconnectedness, diversity, and small/large collection complementary determined subject concentrations and thematic strengths to be prioritized for future collection development and used as organizational structures for browsing and visualization. The approach models how scholars build their own personal research collections, as they follow leads from collection to collection across institutions near and far, and adds value that cannot be achieved through conventional retrieval and browsing at the item-level. digital.library.unt.edu/ark:/67531/metadc71795/
- Collection-Level Subject Access in Aggregations of Digital Collections: Metadata Application and Use
- This doctoral dissertation is about collection-level subject access in aggregations of digital collections. Abstract: 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 personas 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. digital.library.unt.edu/ark:/67531/metadc67618/
- An Event Model for Herbarium Specimen Data in XML
- This poster discusses the Apiary Project. The Apiary Project, a collaboration of the Texas Center for Digital Knowledge at the University of North Texas and the Botanical Research Institute of Texas, is building a framework and web-based workflow for the extraction and parsing of herbarium specimen data. The workflow will support the transformation of written or printed specimen data into a high-quality machine-processable XML format. This poster describes an event model that informed the development of the Apiary XML Application Schema digital.library.unt.edu/ark:/67531/metadc81369/
- An Event Model for Herbarium Specimen Data in XML Poster Abstract
- This abstract describes a poster about the Apiary Project. The Apiary Project, a collaboration of the Texas Center for Digital Knowledge at the University of North Texas and the Botanical Research Institute of Texas, is building a framework and web-based workflow for the extraction and parsing of herbarium specimen data. The workflow will support the transformation of written or printed specimen data into a high-quality machine-processable XML format. This poster describes an event model that informed the development of the Apiary XML Application Schema digital.library.unt.edu/ark:/67531/metadc81384/
- Extracting and Parsing of Herbarium Specimen Data: Exploring the Use of the Dublin Core Application Profile Framework
- This paper discusses extraction and parsing of herbarium specimen data. Abstract: Herbaria around the world house millions of plant specimens; botanists and other researchers value these resources as ingredients in biodiversity research. Even when the specimen sheets are digitized and made available online, the critical information about the specimen stored on the sheet are not in a usable (i.e., machine-processible) form. This paper describes a current research and development project that is designing and testing high-throughput workflows that combine machine- and human-processes to extract and parse the specimen label data. The primary focus of the paper is the metadata needs for the workflow and the creation of the structured metadata records describing the plant specimen. In the project, the authors are exploring the use of the new Dublin Core Metadata Initiative framework for application profiles. First articulated as the Singapore Framework for Dublin Core Application Profiles in 2007, the use of this framework is in its infancy. The promises of this framework for maximum interoperability and for documenting the use of metadata for maximum reusability, and for supporting metadata applications that are in conformance with Web architectural principles provide the incentive to explore and add implementation experience regarding this new framework. digital.library.unt.edu/ark:/67531/metadc81386/
- From AACR2 to RDA: an Update
- This presentation gives an update on the Anglo-American Cataloging Rules 2 (AACR2) and Resource Description and Access (RDA). In this presentation, the author discusses what is changing with RDA and what isn't, the functionality of the catalog, user's experience with functionality, what RDA allows us to do, and cataloger tasks. digital.library.unt.edu/ark:/67531/metadc84314/
- Introducing Resource Description and Access: taming the new cataloging rules
- This presentation gives an introduction to Resource Description and Access (RDA). The author presents information on how RDA works, its affects on cataloging and its functionality. digital.library.unt.edu/ark:/67531/metadc84309/
- RDA: What Cataloging Managers Need to Know
- This presentation discusses what cataloging managers need to know about Resource Description and Access (RDA). It describes issues related to how RDA is affecting cataloging, what is changing and what is not, where we are and how we got here, the intention of RDA, objectives and principles, its relation to AACR2, and other RDA information. digital.library.unt.edu/ark:/67531/metadc84310/
- UNT at ImageCLEF 2010: CLIR for Wikipedia Images
- This paper presents the results of the team of the University of North Texas in the Wikipedia image retrieval track of Image-CLEF-2010. The authors' approach is based on performing translation of the French and German image captions to English and using of Language Models for generating their runs. The authors also explore the use of complex queries by asking two users to manually build queries based on the original topics distributed. The authors' results indicate that the approach of translating the image captions is feasible and yields results that are quite competitive with other teams that participated in the same track. digital.library.unt.edu/ark:/67531/metadc96836/
- What Does Transaction Log Data Tell about Collection-Level Subject Access?
- This poster presents information about what transaction log data can tell about about collection-level subject access. This poster includes the research questions, methods findings and future research involved in investigating transaction log data and collection-level subject access. digital.library.unt.edu/ark:/67531/metadc67597/
- What Does Transaction Log Data Tell About Collection-Level Subject Access?
- This paper accompanies a poster presentation on what transaction log data tells us about collection-level subject access. This paper reports results of the quantitative and qualitative study of a systematic sample of transaction log data that recorded user interactions with a large-scale aggregation of cultural heritage digital collections over a period of one year. digital.library.unt.edu/ark:/67531/metadc130200/