Browsing by Author "Library and Information Science, School of Computing and Informatics"

Now showing 1 - 10 of 14
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    A measurement of faculty views on the meaning and value of student privacy
    (Springer, 2022-06-04) Jones, Kyle M. L.; VanScoy, Amy; Bright, Kawanna; Harding, Alison; Vedak, Sanika; Library and Information Science, School of Computing and Informatics
    Learning analytics tools are becoming commonplace in educational technologies, but extant student privacy issues remain largely unresolved. It is unknown whether faculty care about student privacy and see privacy as valuable for learning. The research herein addresses findings from a survey of over 500 full-time higher education instructors. In the findings, we detail faculty perspectives of their privacy, students’ privacy, and the high degree to which they value both. Data indicate that faculty believe privacy is important to intellectual behaviors and learning, but the discussion argues that faculty make choices that put students at risk. While there seems to be a “privacy paradox,” our discussion argues that faculty are making assumptions about existing privacy protections and making instructional choices that could harm students because their “risk calculus” is underinformed. We conclude the article with recommendations to improve a faculty member’s privacy decision-making strategies and improve institutional conditions for student privacy.
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    A systematic review of library makerspaces research
    (Elsevier, 2022-10) Kim, Soo Hyeon; Jung, Yong Ju; Choi, Gi Woong; Library and Information Science, School of Computing and Informatics
    Despite the abundance of research on library makerspaces, systematic reviews of library makerspace research are lacking. As research on library makerspaces advances, the field needs reliable empirical findings to examine the impact of library makerspaces and identify research areas that are valuable for future research. Guided by the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) statement, 43 out of 838 records were selected for the systematic review. The overall trend of research methodologies and theories, settings, participants, research purposes, as well as tools, technologies and programming in library makerspace research were identified. The findings reveal that qualitative studies that were descriptive in nature were the predominant approaches. While appropriate literatures were explored, theoretical frameworks were less used. This systematic review contributes new areas and directions for future research, including the need for expansion of research methodologies and theoretical frameworks and investigation of diverse users and types of making.
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    Application of Edge-to-Cloud Methods Toward Deep Learning
    (IEEE, 2022-10) Choudhary, Khushi; Nersisyan, Nona; Lin, Edward; Chandrasekaran, Shobana; Mayani, Rajiv; Pottier, Loic; Murillo, Angela P.; Virdone, Nicole K.; Kee, Kerk; Deelman, Ewa; Library and Information Science, School of Computing and Informatics
    Scientific workflows are important in modern computational science and are a convenient way to represent complex computations, which are often geographically distributed among several computers. In many scientific domains, scientists use sensors (e.g., edge devices) to gather data such as CO2 level or temperature, that are usually sent to a central processing facility (e.g., a cloud). However, these edge devices are often not powerful enough to perform basic computations or machine learning inference computations and thus applications need the power of cloud platforms to generate scientific results. This work explores the execution and deployment of a complex workflow on an edge-to-cloud architecture in a use case of the detection and classification of plankton. In the original application, images were captured by cameras attached to buoys floating in Lake Greifensee (Switzerland). We developed a workflow based on that application. The workflow aims to pre-process images locally on the edge devices (i.e., buoys) then transfer data from each edge device to a cloud platform. Here, we developed a Pegasus workflow that runs using HTCondor and leveraged the Chameleon cloud platform and its recent CHI@Edge feature to mimic such deployment and study its feasibility in terms of performance and deployment.
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    Big Data Curation Framework: Curation Actions and Challenges
    (Sage, 2022) Yoon, Ayoung; Kim, Jihyun; Donaldson, Devan Ray; Library and Information Science, School of Computing and Informatics
    Big data curation represents an emerging topic of inquiry but still in an early phase along its adoption curve. The term big data itself is a nebulous concept, and the differences between small data curation and big data curation are nuanced. The goal of this research is to provide a theoretical framework that identifies big data curation actions and associated curation challenges. This study is based on the practices of big data research and data curation by systematically examining literature. The outcome of the study includes the big data curation framework that provides overview of curation activities and concerns that are essential to perform such activities. The study also provides practical implications for libraries, archives, data repositories and other information organisations that concerns the issue of big data curation as big data presents a multidimensional array of exigencies in relation to the mission of those organisations.
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    Data Management Planning for an Eight-Institution, Multi-Year Research Project
    (OJS, 2022-09-07) Briney, Kristin A.; Goben, Abigail; Jones, Kyle M. L.; Library and Information Science, School of Computing and Informatics
    While data management planning for grant applications has become commonplace alongside articles providing guidance for such plans, examples of data plans as they have been created, implemented, and used for specific projects are only beginning to appear in the scholarly record. This article describes data management planning for an eight-institution, multi-year research project. The project leveraged four data management plans (DMP) in total, one for the funding application and one for each of the three distinct project phases. By understanding researcher roles, development and content of each DMP, team internal and external challenges, and the overall benefits of creating and using the plans, these DMPs provide a demonstration of the utility of this project management tool.
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    Does It Matter: Have BLM Protests Opened Spaces for Collective Action in LAMs?
    (Litwin Books, 2022-09-30) Ahmed, Sumayya; Clemens, Rachael; Patillo, Ericka; Murillo, Angela P.; Library and Information Science, School of Computing and Informatics
    The catalytic social justice events of the spring and summer of 2020 led to calls for a racial reckoning within society at large and also within the field of library and information science (LIS). This motivated us to capture the perceptions and voices of professionals across the field about changes they may have witnessed in their workplace, profession, and themselves. We consider the following questions: Have conversations, social spaces, teaching practices, policies, workplace dynamics, and demands, changed in response to the Black Lives Matter (BLM) protests, and if so, how? Have institutional changes perceived as responses to BLM protests been witnessed? What are the nuances behind such behavioral changes (e.g., opportunity, compulsion, peer pressure)? For this research, we used Critical Incident Technique (CIT) to explore how the 2020 BLM protests impacted the workplace environments of LIS faculty and professionals in libraries, archives, and museums (LAMs). A 27-question survey was administered via Qualtrics and participants were recruited using LAM professional listservs. A total of 645 participants completed the survey. This research provides the preliminary analysis and discussion of those results and provides insights to the impact of the 2020 social justice movements in LAMs. By capturing voices of LAM professionals, we explore participants’ perceptions of the impact that BLM protests had on their institutions and/or professional associations and document a range of responses at both the individual and structural levels.
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    Informational Readers Part 2: Web-based Story Maps in the Social Sciences
    (E. L. Kurdyla Publishing, 2021-02) Lamb, Annette; Library and Information Science, School of Computing and Informatics
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    Informational Readers, Part 1: Web-Based Story Maps in STEM
    (E. L. Kurdyla Publishing, 2021-04) Lamb, Annette; Library and Information Science, School of Computing and Informatics
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    Informational Readers, Part 3: Web-based Story Maps in the Arts and Humanities
    (E. L. Kurdyla Publishing, 2021-06) Lamb, Annette; Library and Information Science, School of Computing and Informatics
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    Questions of Trust: A Survey of Student Expectations and Perspectives on Library Learning Analytics
    (University of Chicago Press, 2022-04) Asher, Andrew D.; Briney, Kristin A.; Jones, Kyle M. L.; Regalado, Mariana; Perry, Michael R.; Goben, Abigail; Smale, Maura A.; Salo, Dorothea; Library and Information Science, School of Computing and Informatics
    Universities are developing learning analytics initiatives that include academic library participation. Libraries rarely inform their students about learning analytics projects or general library data practices. Without a clear student voice in library learning analytics projects, libraries and librarians are creating potential privacy complications. This study seeks to document students’ thoughts on academic library participation in learning analytics and privacy concerns. A survey was developed and fielded at eight US higher education institutions, and this article covers the findings from the approximately 2,200 responses. Although most students reported high levels of trust in libraries and librarians, a consistent minority indicated little or no trust at all. Findings demonstrate that students considered librarian access to and sharing of personally identifiable information to constitute a privacy violation but also lacked awareness of the data and analytic practices on which libraries rely. Notable demographic differences were also discovered.