Search Results

Application of Big Data Analytics in Precision Medicine: Lesson for Ethiopia
Precision medicine is an emerging approach for disease treatment and prevention that considers individual variability in genes, environment, and lifestyle for each person. Big data analytics (BDA) using cutting-edge technologies helps to design models that can diagnose, treat and predict diseases. In Ethiopia, healthcare service delivery faces many challenges specifically in relation to prescribing the right medicine to the right patient at the right time. Thus, patients face challenges ranging from staying on treatment plans longer, and then leaving treatment, and finally dying of complications. Therefore, the aim of this paper is to explore the trends, challenges, and opportunities of applying BDA in precision medicine globally and take lessons for Ethiopia through a systematic literature review of 19 peer reviewed articles from five databases. The findings indicated that cancer in general, epilepsy, and systemic diseases altogether are areas currently getting big attention. The challenges are attributed to the nature of health data, failure in collaboration for data sharing, ethical and legal issues, interoperability of systems, poor knowledge skills and culture, and poor infrastructure. Development of modern technologies, experimental technologies and methods, cloud computing, Internet of Things, social networks and Ethiopia’s government initiative to promote private technological firms could be an opportunity to use BDA for precision medicine in Ethiopia.
Campus Chaplains: Cult Training and Perceptions
This article examines the perception of 43 college chaplains across the United States with regard to cult training and perceptions of college and university cult activity.
Changing Landscape of Scholarly Communications: Open Access
The 17th International Conference on Knowledge Management was held in the historic city of Potsdam, Germany. Since the conference was among the first post-pandemic face to face conferences, the overall theme of the 17th edition of the ICKM conference rightly focused on “Knowledge, Uncertainty and Risks: From individual to global scale” at different levels of analysis and agency. This document highlighted one of the panels and the panelists argue that open access to scholarly knowledge production should be the modus operandi in the time and age we live in. Open access to knowledge is critical not just to accelerate advances in finding solutions to societal issues, but also to meet the growing expectations around higher education institutions’ social responsibilities in times of uncertainties.
Competencies Required for Digital Curation: An Analysis of Job Advertisements
Article discussing competencies required for digital curation. The results of the analysis show that digital curation jobs are characterized by a complex interplay of various skills and knowledge. The findings of this study present emerging requirements for a qualified workforce in the field of digital curation.
CTR-NT: A Survey of Local Cataloging Tool and Resource Utilization
This presentation discusses a grant project on Cataloging Tools and Resource: North Texas (CTR-NT). The study aimed to discover the extent and utilization of cataloging tools and resources within technical service departments in the public libraries of the North Texas Regional Library System (NTRLS) and the North East Texas Library System (NETLS).
Designing Learning for Sustainable Development: Digital Practices as Boundary Crossers and Predictors of Sustainable Lifestyles
This article contains results from a survey among students of urban and spatial planning in Slovenia to inform teacher's approaches to teaching as an important driver of institutional change.
Determining Event Durations: Models and Error Analysis
This paper presents models to predict event durations.
Digital humanities in the iSchool
This article presents findings from a series of related studies exploring aspects of Digital Humanities teaching, education, and research in iSchools, often in collaboration with other units and disciplines. Results provide a snapshot of the current state of digital humanities in iSchools which may usefully inform the design and evolution of new DH programs, degrees, and related initiatives.
An Evaluation of the Federal Government's Implementation of the Government Information Locator Service (GILS): Final Report
This document reports the results of the evaluation study commissioned in response to the Government Information Locator Service (GILS) Board's request for an assessment of GILS. The study began in September 1996, data collection ended in March 1997, and the final report was completed in June 1997. The goal of the study was to understand how: GILS serves various user groups, GILS improves public access to government information, agencies are progressing with their implementations, and GILS works as a tool for information resources management.
Exploration of Metadata Practices in Digital Collections of Archives with Arabian Language Materials
Article for a study aimed to develop understanding of the current state of metadata practices in digital collections of archival institutions in the Arabian Gulf region. It also explored perspectives (including attitudes and possible barriers) for development of large-scale regional portals that would facilitate discovery of Arab digital archives (including language collections) by aggregating metadata. It was presented at the 2nd International Workshop on Digital Language Archives held on June 30, 2023 as part of the ACM/IEEE Joint Conference on Digital Libraries 2023.
An Extensible Approach to Interoperability Testing: The Use of Special Diagnostic Records in the Context of Z39.50 and Online Library Catalogs
Presentation discussing the use of special diagnostic records in the context of Z39.50 and online library catalogs.
Framework for designing motivational augmented reality applications in vocational education and training
This article introduces and evaluates a framework for designing motivational augmented reality applications.
From design to impact: a phenomenological study of HumanMOOC participants’ learning and implementation into practice
Article investigates Massive Open Online Courses (MOOC) impact on participants' actual practices.
Gender Differences in 7th Grade Students' Interest in STEM after Participating in a Solenoid Instructional Unit
Paper presented at the 2019 ASEE Annual Conference & Exposition. The research presented studies achievement scores and affinity towards STEM scores of male and female students after participating in a unit focused on understanding a solenoid.
Hierarchical Coding Scheme: Exploring Methods and Techniques for Facilitating Access to Digital Language Archives
This is the hierarchical coding scheme used for qualitative analysis of interviews with language archive managers, depositors, and end-users as part of the 'Exploring Methods and Techniques for Facilitating Access to Digital Language Archives' project (January 2019-August 2020).
How does intrinsic and extrinsic motivation drive performance culture in organizations?
Article reviews literature on the subject of employee motivation to determine whether intrinsic or extrinsic motivation is becoming the driving force of business.
Hybrid medical simulation – a systematic literature review
This article presents a systematic literature review of papers published from 1960 to 2019 that illustrate hybrid simulation can be as effective as high fidelity simulators in certain training scenarios while at the same time providing a superior training context to enhance learners patient to care-giver interactions and to better immerse the trainee in the feelings and emotion of the scenario.
Immersion Librarianship: An assessment of transforming LIS students' professional worldview through a service learning project at an international school library
This paper was presented at the 2017 IFLA World Library and Information Congress. This paper contains a summary of the study to discern what students learned from a library and information science service learning study abroad program to Russia in 2012.
Increasing Information Certainty for Post-Traumatic Growth
Trauma, and its associated effects, can be conceptualized as a period of information uncertainty. The natural psychological response to trauma is a period of post-traumatic stress. Trauma occurs when an existing knowledge base has been challenged. Any event that challenges important components of an individual’s assumptive world is said to be traumatic. This post-traumatic period is akin to many theories and concepts in information science including uncertainty reduction, Everyday Life Information Seeking, Sensemaking Theory, Making Meaning and Anomalous States of Knowledge. One possible outcome after the post- traumatic period is post-traumatic growth. Researchers agree post-traumatic growth primarily occurs across one or more of the following domains: personal strength, new possibilities, relating to others, appreciation of life and spiritual change. That is, people affected by trauma tend to grow when they find new or additional paths of information certainty.
An Interactive Web-Based Dashboard to Examine Trending Topics: Application to Financial Journals
Understanding trends is helpful to identify future behaviors in the field, and the roles of people, places, and institutions in setting those trends. Although traditional clustering strategies can group articles into topics, these techniques do not focus on topics over limited timescales; additionally, even when articles are grouped, the generated results are extensive and difficult to navigate. To address these concerns, we create an interactive dashboard that helps an expert in the field to better understand and quantify trends in their area of research. Trend detection is performed using the time-biased document clustering introduced in Behpour et al. (2021) study. The developed and freely available web application enables users to detect well defined trending topics in financial journals by experimenting with various levels of temporal bias - from detecting short-timescale trends to allowing those trends to spread over longer times. Experts can readily drill down into the identified topics to understand their meaning through keywords, example articles, and time range. Overall, the interactive dashboard will allow experts in the field to sift through the vast literature to identify the concepts, people, places, and institutions most critical to the field.
Language Archiving Training: A Case Study of a Metadata Course in Library and Information Science Graduate Program, 2020 - 2023
Article explores the training gap between the way these materials are organized and represented and the understanding of that data – and expectations towards the more functional ways of its organization and representation – by language preservation and revitalization researchers, and by members of language communities. Information resources collected by language archives have unique attributes of importance to their target user groups, and these attributes and their representation are not currently widely addressed by the formal training provided to information professionals. It was presented at the 2nd International Workshop on Digital Language Archives held on June 30, 2023 as part of the ACM/IEEE Joint Conference on Digital Libraries 2023.<
Library Computing Services in Rural Texas during the COVID-19 Pandemic
Article analyzing the 2020 Texas Public Library Statistics and a portion of the 2019 and 2018 data. It examined various services from libraries located in the areas with a population of less than 5,000. This is the Accepted Manuscript version of a published article.
The Life Between Big Data Log Events: Learners' Strategies to Overcome Challenges in MOOCs
This article discusses a study in which 92 MOOC learners were interviewed to better understand their worlds, investigate possible mechanisms of student attrition, and extend conversations about the use of big data in education.
Longitudinal analysis of cognitive constructs fostered by STEM activities for middle school students
This article studies whether the changes found to occur pre- to post intervention in students' cognitive structures continued to persist two years later.
A Machine Learning Approach to Evaluating Translation Quality
This paper explores the possibility of applying Machine Learning for Machine Translation evaluation.
A Machine Learning Approach to Evaluating Translation Quality
Poster presented at the 2017 ACM/IEEE-CS Joint Conference on Digital Libraries. explores the possibility of applying Machine Learning for Machine Translation evaluation.
Mapping the Interoperability Landscape for Networked Information Retrieval
This paper discusses interoperability of networked information. Interoperability is a fundamental challenge for networked information discovery and retrieval. Often treated monolithically in the literature, interoperability is multifaceted and can be analyzed into different types and levels. This paper discusses an approach to map the interoperability landscape for networked information retrieval as part of an interoperability assessment research project.
Metadata Practices of Academic Libraries in Kuwait, Oman, and Qatar: Current State, Risks, and Perspectives for Knowledge Management
Developing, implementing, and managing metadata is crucial to successful knowledge management, and academic libraries have traditionally played a central role in these activities. The Arabian Gulf countries are underrepresented in the existing research into library metadata practices. This exploratory study used semi-structured interviews of metadata managers at 8 universities with the goal of developing understanding of the current state of metadata practices, including descriptive cataloging, identity management, and knowledge organization in academic libraries of three Arabian Gulf countries (Kuwait, Oman, and Qatar), as well as potential future developments to facilitate discovery of resources. Findings provide insights into this previously under-researched area and contribute to understanding of knowledge management and risks on a global scale.
Multiteam systems in an agile environment: a realist systematic review
Article describes a collaborate study between University of North Texas and Toyota Connected focusing on how to structure and manage multiteam systems (MTSs).
Prediction of Concrete Bridge Deck Condition Ratting Based on Climate Data in Addition to Bridge Data: Five States as a Case Study
Evaluating the impact of learning from climate data, in addition to bridge data, on the performance of concrete deck condition rating prediction is critical for identifying the right data needed to enhance bridge maintenance decision making. Few studies have considered such an evaluation and utilized a small size of samples that prevent revealing the knowledge hidden within the big size of data. Although, such evaluation over big data seems quite necessary, class imbalance problem makes it challenging. To alleviate such a problem, five states, including Alabama, Iowa, New York, Pennsylvania, and South Carolina, were selected as the case study. Not only are the states located in three different climatically consistent regions defined by the National Ocean and Atmospheric Administration (NOAA), but also their concrete deck conditions ratings are somewhat balanced. To conduct the evaluation, this research developed the bridge data set pertaining to 56,288 bridges across the afore-mentioned states through employing the GIS technology. The bridge data set contains bridge data derived from National Bridge Inventory (NBI), and climate data derived from Parameter-elevation Relationships on Independent Slopes Model (PRISM) climate maps and NOAA. Then, two machine learning algorithms, including random forest and GBM, were trained - with and without climate data - and their prediction performances were compared. The results indicated that: (1) random forest outperforms GBM with an accuracy of 63.3%, and (2) the change in the prediction performance after further learning from climate data was marginal since the accuracy reached to 64.9%.
Project Work Plan Draft
This document details a work plan to guide the planning and execution of a new phase of the Z39.50 Interoperability Testbed Project.
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.
Research Teams: Fostering Scholarship and Practice
This workshop is presented by members of a University of North Texas research team. First, the team will overview their experience as members of the research team and share experience in areas such as trust formation, team roles, productivity, work-life balance, faculty-students interaction, peer and faculty mentorship, dissertation preparation, and job seeking. Second, the workshop will discuss and brainstorm how this format can be implemented for organizations both with faculty-student teams and with peer-directed teams. Finally, successes and challenges are openly discussed with audience.
Role of Collection-Level Subject Metadata in Subject Access to Digital Collections in Aggregations
This presentation discusses collection-level subject metadata in subject access to digital collections in aggregations. This was presented at the 18th International Conference "Libraries and Information Resources in the Modern World of Science, Culture, Education, and Business" in Sudak, Ukraine.
Sense-Making: Panel of Discovery
The 17th International Conference on Knowledge Management was held in the historic city of Potsdam, Germany. Since the conference was among the first post-pandemic face to face conferences, the overall theme of the 17th edition of the ICKM conference rightly focused on “Knowledge, Uncertainty and Risks: From individual to global scale” at different levels of analysis and agency. This document highlighted one of the panels that provide an overview of the different methodologies and theories of sense-making from several of the seminal originators of sensemaking.
Social Media and People Perception of Global Warming During Critical Environmental Events: the Impact of Misinformation through the Lens of Social Noise
Global warming is the term used to describe critical environmental issues and concerns. Social media such as Twitter provides a platform for people to share information, exchange ideas, and express their opinions about current and timely issues. This study utilized contextual analysis to analyze data collected from Twitter for the hashtag "global warming" during the period 2010 & 2011. Using sentiment analysis and topic modeling, the study aimed first at assessing people's perception towards global warming issues, and second study the impact of misinformation from the standpoint of social noise on people's perception of global warming during critical environmental events. The outcome of this study helps create a better understanding of the environmental issues discussed on social media. The sentiment analysis from the data analyzed so far shows that most of the tweets were based on Twitter users' personal opinions and not science. The topic modeling results suggest that Twitter users typically tweeted when a major environmental event occurred due to global warming. Topic modeling also aids in the identification of terms that is associated with social noise. The presence of social noise suggests that misinformation does exist and spreads faster.
Stock2Vec: An Embedding to Improve Predictive Models for Companies
Building predictive models for companies often relies on inference using historical data of companies in the same industry sector. However, companies are similar across a variety of dimensions that should be leveraged in relevant prediction problems. This is particularly true for large, complex organizations which may not be well defined by a single industry and have no clear peers. To enable prediction using company information across a variety of dimensions, we create an embedding of company stocks, Stock2Vec, which can be easily added to any prediction model that applies to companies with associated stock prices. We describe the process of creating this rich vector representation from stock price fluctuations and characterize what the dimensions represent. We then conduct comprehensive experiments to evaluate this embedding in applied machine learning problems in various business contexts. Our experiment results demonstrate that the four features in the Stock2Vec embedding can readily augment existing cross-company models and enhance cross-company predictions.
A Theory of Public Knowledge
This article offers a theory of public knowledge for the purposes of defining more clearly its role in information systems and classification schemas.
Time-Compressed Audio on Attention, Meditation, Cognitive Load, and Learning
This article presents a study that examined how three auditory lectures delivered at different speeds – normal (1.0x), fast (1.5x) and very fast (3.0x) speeds – affected graduate students’ attention, cognitive load, and learning.
Unfolding Research Data Services: An Information Architecture Perspective
Poster presented at the 2018 ACM/IEEE Joint Conference on Digital Libraries. This poster describes the use of a content analysis with the lens of information architecture to better understand how research data services are organize in North American academic library websites, and to what extent the research data lifecycle is supported within these services.
Using Data Visualization Tools to Mitigate the Influx of Information in Organizations
Considerable research has been conducted on the topic of information overload using different approaches, from marketing and customer demand to information technologies and sciences, and even among mental health professionals. In business the critical question is how does information overload impact processes, operations, and profitability, and how can data visualization help to solve issues with data management and consumption in organizations. The ability to quickly and effectively process information and make decisions equates to organizational survival in a dynamic, knowledge-based economy where all segments of society are heavily affected by information technologies and systems and data management industries. The growing number of systems apparatuses challenges both individuals and organizations, resulting in reports of fatigue and experiences that compromise successful performance. The objective of this literature review is to discuss how data visualization tools help address information overload and optimize decision making and the business intelligence process in organizations. It concludes that data visualization, indeed, is critical in helping individuals capture, manage, organize, visualize, and present understandable data, but that decision making is affected by cognitive factors that interfere with data processing and interpretation in decision makers.
Using existing metadata standards and tools for a digital language archive: a balancing act
Article discusses how building a digital language archive requires a number of steps to ensure collecting, describing, preserving and providing access to language data in effective and efficient ways. This paper introduces the reader to the background of this project and discusses some of the areas important for representing language materials where both University of North Texas Libraries (UNTL) metadata and CoRSAL metadata practices were adapted to better fit the needs of intended audiences.
Using the mTSES to Evaluate and Optimize mLearning Professional Development
This article reports on the findings from the analysis of data collected using the Mobile Teacher's Sense of Efficacy Scale survey instrument, from an open course about mobile learning called Instructional Design for Mobile Learning that took place from May 4 through June 6, 2015.
Web Archiving Bibliography 2013
The following document is a bibliography of the field of web archiving. It includes a preface as well as a list of bibliographical resources.
Z39.50 Interoperability Testing Framework for Online Library Catalogs Using Radioactive MARC Records
This document discusses a Z39.50 Interoperability Testing framework. In a first phase of the Z39.50 Interoperability Testbed, a large dataset of MARC records was used. In this work, the authors are exploring how a set of special, diagnostic MARC records can be developed and used to identify interoperability problems between a Z39.50 client and a Z39.50 server providing access to a database of bibliographic records supporting the search and retrieval functions of an online library catalog. The authors refer to these special, diagnostic records as radioactive MARC records. It discusses the various components and identifies the tasks related to developing and implementing the components.
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