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Swygart-Hobaugh, Mandy; Anderson, Raeda; George, Denise; Glogowski, Joel – College & Research Libraries, 2022
We present findings from an exploratory quantitative content analysis case study of 156 doctoral dissertations from Georgia State University that investigates doctoral student researchers' methodology practices (used quantitative, qualitative, or mixed methods) and data practices (used primary data, secondary data, or both). We discuss the…
Descriptors: Doctoral Dissertations, Doctoral Students, Research Methodology, Data Collection
Winkler, Bea; Kiszl, Péter – New Review of Academic Librarianship, 2022
Artificial intelligence (AI) is a defining technology of the 21st century, creating new opportunities for academic libraries. The goal of this paper is to provide a much-needed analysis, interpreted in an international context, on what the leaders of academic libraries in East-Central Europe, and specifically in Hungary, think about AI and its…
Descriptors: Foreign Countries, Academic Libraries, Administrators, Artificial Intelligence
Nan Pang – International Journal of Web-Based Learning and Teaching Technologies, 2024
Multimedia information fusion technology is currently a popular technology for data processing. The advanced productivity it brings is dozens of times that of traditional data information processing. The collected and processed information is not only efficient and accurate, but also has strong scalability. With the continuous development of…
Descriptors: Foreign Countries, Academic Libraries, Library Facilities, Library Development
Pouchard, Line; Bracke, Marianne Stowell – Issues in Science and Technology Librarianship, 2016
This paper describes a survey of data practices given to the Purdue College of Agriculture. Data practices are a concern for many researchers with new governmental funding mandates that require data management plans, and for the institution providing resources to comply with these mandates. The survey attempted to answer these questions: What are…
Descriptors: Agricultural Education, Case Studies, Data Processing, Data
Wiley, Christie; Mischo, William H. – Issues in Science and Technology Librarianship, 2016
This article analyzes 21 in-depth interviews of engineering and atmospheric science faculty at the University of Illinois Urbana-Champaign (UIUC) to determine faculty data management practices and needs within the context of their research activities. A detailed literature review of previous large-scale and institutional surveys and interviews…
Descriptors: Data Processing, College Faculty, Scientists, Engineering Education
Stigberg, Sara; Guittar, Michelle; Morse, Geoffrey – portal: Libraries and the Academy, 2015
Assessment and supporting data have become of increasing interest in librarianship. In this paper, we describe the development and implementation of the Northwestern University Library Acknowledgments Database tool, which gathers and documents qualitative data, as well as its component reporting function. This collaborative project and resulting…
Descriptors: Special Libraries, Database Design, Library Development, Program Implementation
Godby, Carol Jean – OCLC Online Computer Library Center, Inc., 2013
This document describes a proposed alignment between BIBFRAME (Bibliographic Framework) and a model being explored by the Online Computer Library Center (OCLC) with extensions proposed by the Schema Bib Extend project, a Worldwide Web Consortium sponsored (W3C-sponsored) community group tasked with enhancing Schema.org to the description of…
Descriptors: Academic Libraries, Consortia, Data Processing, Databases
Schmitt, Carl M.; O'Shae, Patricia; Vaden, Kaleen – National Center for Education Statistics, 2007
This manual describes the methods, procedures, techniques, and activities that were used to produce the Academic Library Survey of 2004 (ALS:2004). This manual is designed to provide guidance and documentation for users of the ALS data. Included in the manual are the following: (1) an overview of the study and its predecessor studies; (2) an…
Descriptors: Academic Libraries, Surveys, Data Collection, Response Rates (Questionnaires)