Mark Edward Phillips

Development of a portal to Texas history

Purpose – To help information professionals learn about issues and considerations in portal building.Design/methodology/approach – The University of North Texas Libraries’ Portal to Texas History provides long‐term storage and access to digital copies of important original materials illuminating Texass past. This paper describes the development of the Portal technology and content – presenting objectives, processes, and future plans – and defines the larger goal of facilitating collaboration among resource‐holding institutions.Findings – Practical aspects of creating and populating the portal include development of specifications and standards, construction of an application framework, selection of content, production of metadata, and refinement of user interfaces. Planned future enhancements to the Portal will augment sustainability and provide added value for users. The portal project may also serve as a catalyst for wider collaborative efforts in digitization.Originality/value – The Portal to Texas Hi...

Building a Framework of Metadata Change to Support Knowledge Management

Evolving user needs and relevance require continuous change and reform. A good digital collection has mechanisms to accommodate the differing uses being made of the digital library system. In a metadata management context, change could mean to transform, substitute, or make the content of a metadata record different from what it is or from what it would be if left alone. In light of the evolving compliance requirements, this paper analyses the three most common types of change within metadata records as well as their subcategories and discusses the possible implications of such changes within and beyond the metadata records.

Indexing quality and effectiveness: an exploratory analysis of electronic theses and dissertations representation

Theses and dissertations (ETDs) represent a wealth of scholarly and artistic content created by graduate students in masters and doctoral programs in the degree‐seeking process. Considering the multi‐disciplinarity and interdiciplinarity characteristics of ETDs, often several subjects and indexing terms need to be supplied to adequately represent ETDs for efficient access.

The University of North Texas Libraries' Portal to Texas History: archival challenges and solutions

The UNT Texas History Portal Project strives to balance the goals of accessibility of information and long-term preservation of digital objects. This poster details the system that automates the collection of metadata records to coordinate access to Web-viewable files and preservation of archived master files.

Introducing name authority into an ETD collection

Purpose – The purpose of this paper is to develop and evaluate a workflow for establishing name authority in uncontrolled collections. Design/methodology/approach – The authors developed a workflow incorporating command-line tools and tested it in the electronic theses and dissertations (ETDs) collection. The authors narrowed the scope of the study to born-digital ETDs in the collection and to contributor names, including chairs and committee members. Findings – This workflow can save staff time and allows for flexible implementation depending on staff numbers and skills as well as institutional needs. Originality/value – This workflow could be used by other institutions with little or no modification, as it does not rely on specialized software or extensive expertise.

Integrating Image-Based Research Datasets into an Existing Digital Repository Infrastructure

In 2011, the University of North Texas (UNT) Libraries partnered with researchers in the universitys academic departments to describe and provide access to items not traditionally included in the UNT Libraries’ systems. Including more than 1,400 items apiece, the two projects are considered active datasets by their respective users. Each collection provided new challenges in harmonizing partner, metadata, and end-user requirements. This article discusses the projects, workflow for defining requirements, and final implementation in the UNT Digital Library. These collections serve as a model for integrating other research projects easily and inexpensively into a repository infrastructure.

Metadata versus Full-Text: Tracking Users’ Electronic Theses and Dissertations (ETDs) Seeking Behavior

This presentation provides data from a recent research project at the University of North Texas (UNT) Libraries to better understand how users are discovering the electronic theses and dissertations (ETDs) in the UNT Libraries. To extract the specific requests for ETDs in the UNT Digital Library, the data was obtained from a server log-that contained more than 178 million lines of requests. From these requests, the search query was executed in an ambiguous way (not specific fielded searches) queries were extracted to create a dataset of item-query pairs. These item-query pairs were presented to the Solr full-text indexer that powers the search and retrieval side of the UNT Digital Library to report back on statistics, and help to explain whether a specific query was satisfied by either the ETDs full-text, metadata, or by both fields. The resulting data helps us understand how our users are arriving at a given ETD in the collection. Among other speculations, the role of metadata for the discovery process, and the possible overlap that is present between metadata and the full-text of the ETD itself will be analyzed and discussed.

Can Research Librarians make Contributions to Decision-making as Intelligence Analysts?: The Prospects and Challenges

This panel discusses the prospects and challenges of providing intelligence analysis services in U.S. research libraries to support decision-making at various levels.

Uncovering Hidden Insights for Information Management: Examination and Modeling of Change in Digital Collection Metadata.

This paper reports the study which measured and categorized metadata change in the digital collection of patents. The descriptive metadata in this collection is based on the local version of Dublin Core. The moist frequently occurring categories and subcategories of change are identified, as well as metadata fields that are edited the most often. Comparative analysis between multiple editing events is conducted. Results and future/concurrent research are discussed.

Machine learning for name type classification in library metadata: Machine Learning for Name Type Classification in Library Metadata

This poster reports on the effectiveness of machine learning approaches to classify common names in library metadata records using the Library of Congress Name Authority File. Features extracted from this dataset were used to train and evaluate classification algorithms including decision tree, naïve Bayes, random forest and support vector machine implemented in Weka, an open‐source machine learning platform. The best performing classifiers were also tested on a collection of 30,000 names extracted from the UNT Digital Library This poster presents the feature sets, their testing results and the information gains of extracted features. The study demonstrated that machine learning could effectively classify names as persons or corporations.