bluuebunny/crossref_metadata_2025 huggingface dataset:
Mutual Sustainability among Communities and Their Knowledge Infrastructures
Authors: Fenlon Katrina , Reza Alia , Grimmer Jessica , Wagner Travis
Published: October 2023

Digital, community‐based knowledge infrastructures confront complex, systemic challenges to their sustainability over time. From digital community archives to computationally amenable corpora, databases, or data models created by and serving research communities, these sites of grassroots knowledge production tend to be maintained without long‐term institutional commitments. Yet, they hold unique cultural evidence of enormous value. Prior work on the sustainability of digital humanities scholarship has surfaced numerous factors in project sustainability, including technical, organizational, and financial concerns. The roles of communities themselves in sustaining community‐based knowledge infrastructures, however, are under‐studied. This qualitative, multi‐case study of digital humanities projects and digital community archives addresses community‐centered approaches to understanding and implementing sustainability for digital knowledge infrastructures. This study finds that communities of various kinds—from public communities to networks of research practice—conceive of the sustainability of their digital projects as inextricably linked to the sustainability of communities themselves. We offer an exploration of factors in the mutual relationship of sustainability between communities and their knowledge infrastructures, including how they support the wellbeing of individuals and cohesion among communities, and how they promote activism and advocacy efforts within broader publics and disciplinary cultures.
Development of a Recordkeeping Culture in Community‐Based Organisations in Bangladesh
Authors: Frings‐Hessami Viviane , Hossain Md. Khalid , Bhowmik Joy , Meem Jemima Jahan
Published: October 2023

Records play an important role in supporting business activities and in ensuring accountability in all types of organisations. However, recordkeeping research has mostly focused on the government sector and on large organisations. Little attention has been paid to small organisations which have limited resources to create and manage the records that they are required to produce and the records that could support their engagement in diversified activities. In this paper, we report the findings from 16 focus group discussions with community‐based organisations in Bangladesh which are in the process of transitioning from informal to registered organisations and, in order to do so, must formalise their recordkeeping practices. We discuss the recordkeeping needs and capabilities of these organisations and the recordkeeping problems that they are experiencing. We argue that it is important to support the development of a recordkeeping culture as part of capacity‐building in these organisations so that they can function effectively and be sustainable.
Voices of the Stacks: A Multifaceted Inquiry into Academic Librarians' Tweets
Authors: Ghosh Souvick , Thajudeen James
Published: October 2023

Twitter has emerged as an important forum for discussion among academic librarians. In this research, we take a mixed‐methods approach to study the thematic content and sentiment of tweets authored by academic librarians in the United States, Canada, and the United Kingdom. We found differences in the semantic content and themes present in the data from each country that point to differences in how librarians in each country engage on Twitter. While more work remains to be done, we cast new light on how members of professional communities use social media. Our qualitative analysis identified 11 thematic categories in academic librarians' Twitter discussions, focusing on professional topics. UK librarians exhibited a higher frequency of labor‐ and employment‐related terms compared to their US and Canadian counterparts. Sentiment ratios for US and Canadian tweets were similar, while the UK displayed nearly double the positive‐to‐negative tweet ratio. We also present a methodological intervention comparing two different sentiment analysis methods, VADER, and Zero‐Shot Learning (ZSL), to classify posts by academic librarians. ZSL significantly outperformed the off‐the‐shelf classifier, highlighting how accurate prediction is possible without annotated training data.
The Mining of China's Policies against COVID‐19 from Policy Targets and Policy Tools Perspectives
Authors: Huo Chaoguang , Li Xinru , Zhang Chenwei , Huo Fanfan
Published: October 2023

In response to the global disaster of COVID‐19, every country has implemented various policies. China, as a developing country, has issued policies to combat COVID‐19 that could serve as a reference for future pandemic prevention and control efforts, and may offer lessons for national governance. This paper employs bibliometric methods, text mining, and network analysis to mine and characterize the evolution of China's policies against COVID‐19. Specifically, we extract policy targets and identify the policy tools from each policy, cross‐compare the policy tools used for different policy targets, and characterize their evolution during the pandemic. Our findings show that policy targets have shifted over different stages to balance epidemic prevention with economic development. We also identify several shortcomings in distribution and utilization of policy tools. To improve policy implementation, it is crucial to align policy targets with appropriate policy tools and ensure a balanced and functional approach to policy implementation.
Multi‐Modal Crisis Discourse and Collective Sensemaking on TikTok
Authors: Khoury Christy , Owen‐Smith Alexander , Joh Una , Duan Yiran , Hemsley Jeff
Published: October 2023

An explosion at the Port of Beirut resulted in over 200 fatalities and displaced many more. Hundreds recorded and thousands shared the event, sparking discourse across social media. We provide a mixed‐methods analysis of 26 TikTok videos about the port explosion. Our study involved a semiotic analysis of the videos and a content analysis of the related 21,150 comments. The discourse surrounding the explosion extends a growing body of literature on the role of TikTok in disseminating crisis‐related information. We use a collective sensemaking framework to investigate how TikTok contributes to the understanding of an event. The authors find that Middle Eastern content creators contributed more to collective sensemaking about the event than non‐Middle Eastern creators. We additionally examine the current state of collective sensemaking on TikTok and provide platform implications.
Examining Social Media Policy and Records Management in Massachusetts Municipal Governments
Authors: Kriesberg Adam
Published: October 2023

This paper reports on an exploratory analysis of the social media policies of municipal governments in the Commonwealth of Massachusetts. With a strong Public Records law and language clearly indicating that social media posts are government records, Massachusetts provides a framing for research into municipal policy on social media use, retention, preservation, and access. Of the 351 municipalities in the Commonwealth, just 87 have publicly accessible Social Media policies. These policies indicate that municipal governments take their responsibilities around social media records management seriously, they do not offer many specifics around how they will engage directly with posts from privately‐owned social media platforms. Implications of these findings suggest that the digital preservation community must continue to develop tools and methods to preserve social media records the support broader efforts around government transparency and accountability, as well as advocate for platforms to include features to support responsible public sector social media use.
Sharing Qualitative Interview Data in Dialogue with Research Participants
Authors: Kvale Live Håndlykken , Pharo Nils , Darch Peter
Published: October 2023

Research data sharing is embedded in policies, guidelines and requirements commonly promoted by research funding organizations that demand data to be “as open as possible, as closed as necessary” and FAIR. This paper discusses the challenges of balancing privacy protection with data sharing in a PhD project involving long‐tail, small‐sized qualitative human subjects' data. Based on experiences and feedback from project participants, we argue that privacy protection is about respecting the participants and their self‐image. This can be achieved through dialogue and involvement of the participants building on the principles of shared stewardship. Further, we suggest that de‐identification and plain language consent materials are better at protecting privacy than anonymisation, which in a digital data environment is difficult to achieve and not necessarily a sensible approach for qualitative data, where the gold is in the details. The literature indicates that it matters to participants whether data are reused for research or other purposes, and that they trust the institutions. This supports our claim that research data services must find better solutions for restricted sharing when necessary.
In a Perfect World: Exploring the Desires and Realities for Digitized Historical Image Archives
Authors: Late Elina , Ruotsalainen Hille , Kumpulainen Sanna
Published: October 2023

The primary goal of this paper is to explore users' desires for digitized historical image collections, examining their desires based on different use purposes and information interaction activities. In addition, we investigate the image attributes that users wish to search from the collection. To accomplish this, we conducted 21 qualitative interviews with active users of a digitized historical photograph archive. Our findings suggest that users' desires relate to three contexts: tools, collection, and socio‐organizational issues. Moreover, our results indicate that users require support for various information interaction activities, not just searching. We found that users' desires vary based on their specific use purposes, and that users prioritize conceptual access points that can already mostly be generated through automated annotation methods. Ultimately, this study contributes to a better understanding of users' real‐life image needs and offers implications for improving access to digital image collections.
Person‐OrientedOntologies Analysis for Digital Humanities Collections from a Metadata Crosswalk Perspective
Authors: Liu Rui , McKay Dana , Buchanan George
Published: October 2023

Mapping between different representations of similar data is a common challenge in digital humanities (DH). In practical DH collections, the ‘person’ is an essential and centric unit and other parts could link to the ‘person’ to form the knowledge base. However, there is still no general and useful person‐oriented ontology in DH community. Many practical DH projects have developed their own ontologies by DH experts, but these ontologies are not interoperable. Therefore, it is important to explore existing biographical ontologies and develop a comprehensive person‐oriented ontology for DH.

Using the metadata crosswalk method, we examined the ontologies provided for persons in three DH collections to analyze how they map onto standard ontologies such as FOAF (friend of a friend). This paper uncovers a significant and consistent gap between standard biographical ontologies and those used in practical DH collections, arriving at a set of heterogeneous problems, including different granularities of metadata. Consequently, we propose three key person‐oriented ontological types of elements, drawing on this metadata crosswalk: basic biographical elements, relational elements, and explanatory elements (such as career, connected with role and time). This metadata crosswalk provides a foundation for future matching between person‐oriented ontologies and facilitates semantic interoperability between DH collections.
An Investigation of the Use of Theories in Misinformation Studies
Authors: Ogbadu‐Oladapo Lydia , Chung Hsin‐Husan , Li Jiyuan , Chen Jiangping
Published: October 2023

This paper examines social science and humanity theories that have been applied to studies dealing with misinformation. We identified 273 articles published from 2012 to 2023 from Web of Science, Scopus, and ScienceDirect. These articles are empirical studies that have applied one or more social science or humanity theories. Applying content analysis approach, we identified 124 theories that authors have used in their studies. These theories belong to different disciplines or fields, such as political science, psychology, communication, sociology, and economics. We discuss the top 11 theories and how they have been used to understand misinformation and its impacts. This study provides insights into understanding current misinformation studies and rich resources for information evaluation and information literacy education.
From Principles to Practice: Comparative Analysis of European and United States Ethical AI Frameworks for Assessment and Methodological Application
Authors: Pierson Cameron M. , Hildt Elisabeth
Published: October 2023

The Z‐Inspection® Process is a form of applied research for the ethical assessment of AI systems. It is quickly establishing itself as a robust method to ethically assess AI in Europe. The process is predicated on the European Union's Ethics Guidelines for Trustworthy AI, outlining ethical principles intended to guide European AI development. In contrast, the United States has only recently released its holistic version of such guidelines, the Blueprint for an AI Bill of Rights. The aim of this paper is to assess the suitability of the Blueprint for an AI Bill of Rights as an ethical framework underpinning the use of the Z‐Inspection® Process in the United States. This paper provides preliminary findings of comparative analysis of European and United States ethical frameworks for responsible AI development. Findings outline primary ethical concepts that are shared between respective frameworks. Findings suggest the US Blueprint is suitable as an ethical framework for the Z‐Inspection® Process. There are notable omissions within the US framework which would require further development for Z‐Inspection® use. Discussion will consider opportunities for adapting Z‐Inspection® to the United States context, including contributions from the information professions and research.
“Get Our Feet Wet and Hands Dirty”: Black Community‐Based Librarianship and the Fight Against Information Poverty, 1940‐1975
Authors: Poole Alex H.
Published: October 2023

Focusing on information services to marginalized urban communities in the United States between 1940 and 1975, this paper argues that African American librarians played foundational roles in early community‐based librarianship (CBL) initiatives. In doing so, Black librarians skillfully and resourcefully fought information poverty, pushed for social and political equality, and promoted their communities’ well‐being through proactive information provision. By fighting the systemic racism throttling inner‐city Black communities, their labors constituted a seminal contribution to the post‐World War II United States Freedom Struggle. Theirs was a specifically Black CBL. Underpinned by the theoretical work of Elfreda Chatman, this heretofore hidden history offers fruitful lessons for current library and information science practice. It therefore aligns with the annual meeting theme, “Translating Information Research into Practice, Policy, and Action,” particularly its emphasis on “creating effective models of information provision, creating empathetic information services” and on “understanding the power of information to develop human happiness, equality, and wellbeing.”
Study on the Characteristics of Cross‐Domain Knowledge Diffusion from Science to Policy: Evidence from Overton Data
Authors: Ren Chao , Yang Menghui
Published: October 2023

The cross‐domain knowledge diffusion from science to policy is a prevalent phenomenon that demands academic attention. To investigate the characteristics of cross‐domain knowledge diffusion from science to policy, this study suggests using the citation of policies to scientific articles as a basis for quantifying the diffusion strength, breadth, and speed. The study reveals that the strength and breadth of cross‐domain knowledge diffusion from scientific papers to policies conform to a power‐law distribution, while the speed follows a logarithmic normal distribution. Moreover, the papers with the highest diffusion strength, breadth, and fastest diffusion speed are predominantly from world‐renowned universities, scholars, and top journals. The papers with the highest diffusion strength and breadth are mostly from social sciences, especially economics, those with the fastest diffusion speed are mainly from medical and life sciences, followed by social sciences. The findings indicate that cross‐domain knowledge diffusion from science to policy follows the Matthew effect, whereby individuals or institutions with high academic achievements are more likely to achieve successful cross‐domain knowledge diffusion. Furthermore, papers in the field of economics tend to have the higher cross‐domain knowledge diffusion strength and breadth, while those in medical and life sciences have the faster cross‐domain knowledge diffusion speed.
A Study of COVID‐19 Information Behaviors among Black Americans
Authors: Stewart Brenton J. , Ju Boryung , Walker Jessie J.
Published: October 2023

Many Black Americans expressed skepticism and hesitancy about the Covid‐19 vaccine. The objective of this research is to examine whether there is a relationship between Covid‐19 vaccine status, Covid‐19 vaccine knowledge, and information seeking about the coronavirus. A national online questionnaire of 222 Black identified individuals completed the instrument in the Summer of 2021. We conducted data analysis using ANOVA and nonparametric correlation tests among the variables. Findings show that individuals who have received the COVID‐19 vaccine exhibited greater COVID‐19 vaccine‐related knowledge compared to people who declined the vaccine, or were hesitant adopters. There is no significant difference in the level of knowledge between those who are hesitant about the vaccine and those who declined it. Finally, there is a moderate positive correlation between COVID‐19 vaccine knowledge and engagement in COVID‐19‐related information seeking. We conclude with strategies to improve the Black American health information environment by way of practice, policy and action.
Characterizing and Early Predicting User Performance for Adaptive Search Path Recommendation
Authors: Wang Ben , Liu Jiqun
Published: October 2023

User search performance is multidimensional in nature and may be better characterized by metrics that depict users' interactions with both relevant and irrelevant results. Despite previous research on one‐dimensional measures, it is still unclear how to characterize different dimensions of user performance and leverage the knowledge in developing proactive recommendations. To address this gap, we propose and empirically test a framework of search performance evaluation and build early performance prediction models to simulate proactive search path recommendations. Experimental results from four datasets of diverse types (1,482 sessions and 5,140 query segments from both controlled lab and natural settings) demonstrate that: 1) Cluster patterns characterized by cost‐gain‐based multifaceted metrics can effectively differentiate high‐performing users from other searchers, which form the empirical basis for proactive recommendations; 2) whole‐session performance can be reliably predicted at early stages of sessions (e.g., first and second queries); 3) recommendations built upon the search paths of system‐identified high‐performing searchers can significantly improve the search performance of struggling users. Experimental results demonstrate the potential of our approach for leveraging collective wisdom from automatically identified high‐performance user groups in developing and evaluating proactive in‐situ search recommendations.
Finding the Aha! Moment of Search: A Preliminary Examination of Insight Learning During Search
Authors: Wang Xinyue , Liu Chang
Published: October 2023

Research in information behavior has examined search difficulties and how people learn during searches but has not fully examined how searchers solve the difficulties on their own and gain new knowledge during this process. This study introduced the concept of insight learning during search to provide a new perspective for the studies in Search as Learning (SAL) and to optimize searchers' experiences in a more efficient, innovative, and joyful way to combine search and learning. As a preliminary study, we conducted self‐reported interviews with 30 participants to collect cases of insight learning during the search process. Based on thematic analysis of the data, we summarized the benefits of insight learning during search, described the process of how aha! occurred after impasse, and identified the antecedent, key, and consequence of insight during the search process. We aimed to help generate more insights by providing three dimensions of key factors to think about. A preliminary understanding of the insights formed in this study could contribute to further discussion about learning during the search and could help design new search tools that support effective learning.
Curating for Contrarian Communities: Data Practices of Anthropogenic Climate Change Skeptics
Authors: Wofford Morgan F. , Thomer Andrea K.
Published: October 2023

The open data movement is often touted as a sweeping strategy to democratize science, promote diverse data reuse, facilitate reproducibility, accelerate innovation, and much more. However, the potential perils of open data are seldom examined and discussed in equal measure to these promises. As we continue to invest in open data, we need to study the full spectrum of what open data facilitates in practice, which can then inform future policy and design decisions. This paper aims to address this gap by presenting an investigative digital ethnography of one contrarian community, anthropogenic climate change (ACC) skeptics, to describe how they process, analyze, preserve, and share data. Skeptics often engage in data reuse similar to conventional data reusers, albeit for unconventional purposes and with varying degrees of trust and expertise. The data practices of ACC skeptics challenge the assumption that open data is universally beneficial. These findings carry implications for data repositories and how they might curate data and design databases with this type of reuse in mind.
Using Explainable AI to Understand Team Formation and Team Impact
Authors: Xu Huimin , Saar‐Tsechansky Maytal , Song Min , Ding Ying
Published: October 2023

The citation of scientific papers is considered a simple and direct indicator of papers' impact. This paper predicts papers' citations through team‐related variables, team composition, and team structure. Team composition includes team size, male/female dominance, academia/industry collaboration, unique race number, and unique country number. Team structures are made up of team power level and team power hierarchy. Team members' previous citation number, H‐index, previous collaborators, career age, and previous paper numbers are a proxy of team power. We calculated the mean value and Gini coefficient to represent team power level (the collective team capability) and team power hierarchy (the vertical difference of power distribution within a team). Taking 1,675,035 CS teams in the DBLP dataset, we trained the XGBoost model to predict high/low citation. Our model has reached 0.71 in AUC and 70.45% in accuracy rate. Utilizing Explainable AI method SHAP to evaluate features' relative importance in predicting team citation categories, we found that team structure plays a more critical role than team composition in predicting team citation. High team power level, flat team power structure, diverse race background, large team, collaboration with industry, and male‐dominated teams can bring higher team citations. Our project can provide insights into how to form the best scientific teams and maximize team impact from team composition and team structure.
Refueling Mental Health: Digital Reading Predicts Psychological Resilience for Left‐behind Children in Rural China
Authors: Zhao Liang , Zeng Zihan , Liu Jiayi , Zhang Yachen
Published: October 2023

Beyond the easy and equal access to massive online contents, will digital reading bring more social welfare values for disadvantaged groups? Take left‐behind children (LBC) in rural China as example, whose mental health issue has widely aroused public concern. Lacking of sufficient parental supervision and educational resources leads to insufficient development of psychological resilience and makes them vulnerable to mental health problems. As psychological resilience is a critical protective factor for maintaining mental health, in this paper, we wonder whether digital reading could perform as an alternative way with easy accessibility and numerous resources to supplement LBC's resilience development. We conducted a field questionnaire study on LBC (N = 217) and investigated the predictive effect of digital reading on psychological resilience. After controlling sociodemographic variables and common resilience protective factors, hierarchical regression results demonstrated that digital reading predicted an additional 4.3% of the variation in resilience above the control variables, indicating digital reading a positive promoter of LBC's psychological resilience. Moreover, by systematically exploring the fine‐grained digital reading variables, we also found intrinsic motivation to read and recreational digital reading (e.g., reading comics and communicating online) to be the two most stronger predictors of psychological resilience.
Digital Ownership: The Case of E‐Books
Authors: Zhu Xiaohua Awa
Published: October 2023

Ownership of digital information products in the digital age presents an intricate issue. While research has shown that individuals experience a sense of ownership over their digital possessions, the scope of digital ownership rights in comparison to physical entities remains unclear. Amongst various digital products, e‐books stand out due to their ubiquity. This paper presents the results of an empirical research study that used an online survey to examine e‐book consumers' perspectives on digital ownership and digital rights. The study revealed that while most participants value and desire ownership rights, certain conventional ownership rights, such as reselling, gifting, and lending, are deemed less significant and can be relinquished by consumers due to cost‐related factors. Furthermore, contrary to prevailing assumptions, the study found no discernible generational gap concerning people's perceptions of digital ownership rights. These findings hold implications for researchers, policymakers, and public‐interest groups seeking to advocate for the public's digital rights.
Exploring Information Seeking and PIM Practices of Early‐Career Researchers: Insights into Navigating Academic Transitions
Authors: Alon Lilach
Published: October 2023

This study represents the initial phase of a broader investigation into the significance of information seeking and personal information management (PIM) practices during life transitions. It focuses on early‐career researchers who experience multiple academic transitions and aims to identify the information practices they use and their role in promoting successful life transitions. To achieve this goal, in‐depth semi‐structured interviews were held with 15 early‐career researchers who recently completed their PhDs or graduated. Findings suggest that the participants relied on iterative cycles of various information seeking and validation practices to transition between positions and academic institutions, which improved their knowledge about the transition and reduced uncertainty. Once a network of transition‐related information was established, participants began utilizing PIM practices to organize their information and plan for the transition, thereby enhancing their sense of control over their information and maintaining it over the long term in an unstable environment. The study underscores the importance of information practices during life transitions and recommends interventions such as institutional support and information skills training programs to assist early‐career researchers in challenging transitions. The subsequent study will build upon these findings to further examine the role of information behavior in facilitating life transitions.
“I Am in a Privileged Situation”: Examining the Factors Promoting Inequity in Open Access Publishing
Authors: Ayeni Philips
Published: October 2023

Despite increasing advocacy for open access (OA), the uptake of OA in some disciplines has remained low. Existing studies have linked the low uptake in OA publishing in the humanities and social sciences (HSS) to disciplinary norm, limited funding to pay for article processing charges (APCs), and researchers' preferences. However, there is a growing concern about inequity in OA scholarly communication, as it has remained inaccessible and unaffordable to many researchers. This study therefore investigated inequity in OA publishing in Canada. Using semi‐structured interviews, qualitative data was collected from 20 professors from the HSS disciplines of research‐intensive universities in Canada. Data was analyzed with NVivo software following the reflexive thematic analysis approach. Findings revealed three main causes of inequity in OA publishing among the participants. These are the cost of APCs, unequal privileges, and gender disparities. Hence, there is a need for concerted efforts by funding agencies, stakeholders, higher education institutions, and researchers to promote equity in OA scholarly communication. Some recommendations for improving equity in OA publishing are provided in this paper.
Computational Thematic Analysis of Poetry via Bimodal Large Language Models
Authors: Choi Kahyun
Published: October 2023

This article proposes a multilabel poem topic classification algorithm utilizing large language models and auxiliary data to address the lack of diverse metadata in digital poetry libraries. The study examines the potential of context‐dependent language models, specifically bidirectional encoder representations from transformers (BERT), for understanding poetic words and utilizing auxiliary data, such as author's notes, in supplementing poetry text. The experimental results demonstrate that the BERT‐based model outperforms the traditional support vector machine‐based model across all input types and datasets. We also show that incorporating notes as an additional input improves the performance of the poem‐only model. Overall, the study suggests pretrained context‐dependent language models and auxiliary data have potential to enhance the accessibility of various poems within collections. This research can eventually assist in promoting the discovery of underrepresented poems in digital libraries, even if they lack associated metadata, thus enhancing the understanding and appreciation of the literary form.
Studying Lived Experience and Automated Systems: The Case of Universal Credit
Authors: Currie Morgan , Podoletz Lena
Published: October 2023

This paper applies the concept of ‘lived experiences’ to understand people's subjective and everyday encounters with automated systems. We reflect on how qualitative longitudinal research methods are useful for capturing the affective and emotional dimensions of these experiences; these flexible methods also allow for iterative changes that can react to new findings and participant feedback. Using our empirical study on Universal Credit (UC), the UK's largest social security payment, we demonstrate how studying lived experiences via qualitative longitudinal research helps us reflect on both the topic of the research and our position as researchers in relation to study participants. We argue that the lived experience framework is extremely valuable for understanding the consequences of automated decisions for users of these systems and to redress the uneven power dynamics of representing the voices of those sharing these encounters.
Involving Older Users in Design of Patient Accessible Electronic Health Records: Exploring the Potential of Open‐Ended Questions
Authors: Eriksson‐Backa Kristina , Enwald Heidi , Hirvonen Noora , Huvila Isto
Published: October 2023

Despite older adults being one of the most important groups of users of eHealth services, including patient accessible electronic health records, these are claimed to not be designed to suit older users, and to not necessarily fulfill their information needs. User‐centered design methods often utilized when developing eHealth services have also been claimed to not work well for older adults. This paper suggests an alternative way of collecting ideas and feedback on eHealth from older adults, by including open‐ended questions in the data collection of larger studies on eHealth information behavior. When data are collected by methods like focus group interviews and surveys, older adults can be requested to envision an eHealth service that suits their needs. Results from studies in Finland are presented, and show that current eHealth services do not fulfill all information needs of older adults, as answers to the question in both focus group interviews and surveys contain practical suggestions for additional and more comprehensible information, easier ways of searching for needed information, and alternative channels for communication. Open‐ended questions can be a cost‐effective and timesaving way to help in the design and development of patient accessible electronic health records and other types of eHealth services.
DataChat: Prototyping a Conversational Agent for Dataset Search and Visualization
Authors: Fan Lizhou , Lafia Sara , Li Lingyao , Yang Fangyuan , Hemphill Libby
Published: October 2023

Data users need relevant context and research expertise to effectively search for and identify relevant datasets. Leading data providers, such as the Inter‐university Consortium for Political and Social Research (ICPSR), offer standardized metadata and search tools to support data search. Metadata standards emphasize the machine‐readability of data and its documentation. There are opportunities to enhance dataset search by improving users' ability to learn about, and make sense of, information about data. Prior research has shown that context and expertise are two main barriers users face in effectively searching for, evaluating, and deciding whether to reuse data. In this paper, we propose a novel chatbot‐based search system, DataChat, that leverages a graph database and a large language model to provide novel ways for users to interact with and search for research data. DataChat complements data archives' and institutional repositories' ongoing efforts to curate, preserve, and share research data for reuse by making it easier for users to explore and learn about available research data.
An Examination of the Real‐World Appraisal Practices of Archivists
Authors: Faulkner James D. , Kim Jeonghyun
Published: October 2023

Archives serve as repositories for items of enduring value. Archivists use a process called appraisal to evaluate the value of these items. While various theories and methods have been developed to guide the appraisal and many issues have been identified, little is known about how archivists conduct appraisals or what efforts they undertake to mitigate these issues. As such, this exploratory and qualitative study aims to examine the appraisal practices of archivists in university special collections, the role of the collection policy, and how these policies deal with problematic aspects of appraisal. This study found that university special archivists view appraisal as a complex but systematic process and implement the collection policy's principles and methodologies into their appraisal practices. Moreover, this study revealed that archivists try to establish and maintain effective relationships with donors and communities throughout the entire appraisal process.
Information in Crisis Mode? A Conceptual Analysis of the Information Crisis Discourse
Authors: Hicks Alison , Noone Rebecca
Published: October 2023

The concept of ‘information crisis’ is playing an increasingly prominent role within information studies literature and practice. Yet, the term is rarely defined and its meaning often remains both inconsistent and ambiguous. This opacity calls for a greater grounding of the term if it is to become a key concept in the field, including how it operates and what it enforces. This short paper draws upon information studies literature to present a conceptual analysis of the concept of ‘information crisis.’ From this analysis, we argue that an ‘information crisis’ framing is typically used to either establish the status quo, through centring challenges to established information ecosystems, or maintain the status quo, by outlining the operations needed to renew or protect these landscapes. These findings illustrate how ‘information crisis’ can obscure the very contexts of inequality and injustice through which crisis operates and delimits the possibility of changing/disrupting the status quo.
Information Barriers Caused by Marginalization and Norms: Experiences of Transgender and Non‐Binary People
Authors: Huttunen Aira
Published: October 2023

Marginalization and stigma can shape the information practices of vulnerable groups. Using examples from previous research, this short paper examines how norms and marginalization can serve as information barriers in societal and medical settings for transgender and non‐binary people. The results indicate the presence of several information barriers that are related to marginalization and gender norms in both social and medical settings. Marginalization can result in covert information seeking, and gender norms can affect embodied information practices, such as information sharing. Medical authorities hold authority that can impose barriers on information sharing and lead to gender norms being adhered to in medical settings. The results highlight various practical implications for information and healthcare providers.
Practices of the “Library as Place” in Norway
Authors: Kawamoto Marika , Koizumi Masanori
Published: October 2023

In modern society, though public libraries must be equal and neutral “places” to address social problems such as the crisis of democracy and social isolation, it is unclear how the roles and functions of “Library as Place” appear in modern library management policies or practices. This study aimed to clarify the characteristics of public library policies in Norway and Oslo and the practices of the Oslo public library from the perspective of the “Library as Place.” Using Kawamoto and Koizumi's (2023) model, a qualitative content analysis and case analysis were conducted of the roles and functions of “Libraries as Place” in Oslo, Norway, identifying the access to materials and information that libraries have traditionally afforded alongside the implementation of distinctive functions such as Cultural activities, Cutting edge, Improving life skills, and Meeting place as concrete practices. These functions contribute to public libraries becoming places in the heart of the community whose services are accessible to all.
Development and Validation of a Data Literacy Assessment Scale
Authors: Kim Jeonghyun , Hong Lingzi , Evans Sarah , Oyler‐Rice Erin , Ali Irhamni
Published: October 2023

The recognition of data literacy as an important learning outcome in higher education has led to a call for assessment tools to measure students’ data literacy. Although there has been a growing interest in the conceptualization of data literacy, the literature lacks a measuring instrument to operationalize data literacy. This study developed and validated a three‐factor, 24‐item data literacy assessment tool using a sample of 573 students from four community colleges in the United States. The data literacy scale developed in this study has respectable reliability and construct validity, supported by a concept analysis of data literacy, a comparative analysis of data literacy competency frameworks, an expert panel review, exploratory factor analysis, and confirmatory factor analysis.
Trend of Collaboration in STEM Education in Informal Learning Institutions Based on IMLS‐funded Projects
Authors: Kim Soo Hyeon , Yoon Ayoung , Seo JooYoung
Published: October 2023

There is limited systematic research on understanding the trends of STEM education in libraries. While reviews of STEM education from various funding agencies exist, these reviews encompass STEM education across formal and informal settings, which may not provide specific implications that center around libraries. This paper examines the trend of collaboration among libraries and other collaborating organizations involved in STEM education funded by the Institute of Museum and Library Services (IMLS). Through content analysis and geocode analysis of 128 projects that are funded by IMLS in 2012–2022, this study shows the diverse engagement of different types of informal learning institutions in STEM education over time. Findings also demonstrate that while few informal learning institutions represented the leading and collaborating organizations in IMLS STEM education initially, leading and collaborating organizations diversified with a higher level of collaboration.
Teenagers and Videoconference Fatigue: A Preliminary Analysis from an Affordance‐based Approach
Authors: Lee Chei Sian , Li Benjamin Junting , Wu Qian
Published: October 2023

The Covid‐19 pandemic has led to the widespread use of videoconference (VC) technologies, particularly in education and this trend is projected to continue. Prolonged VC usage can lead to “videoconference fatigue” (VCF). While research on factors contributing to VCF has been conducted among university students, there is limited research on younger students (especially teenagers). To fill this gap, this study adopts an affordance‐based approach to identify VC affordances (resources and constraints) contributing to VCF in teenagers. Specifically, the objectives are to examine if (a) VC affordances (visibility, information, and availability), and (b) demographic profiles (age and gender) have effects on VCF among teenagers. A large‐scale survey was conducted and responses from 491 teenagers were analyzed using Hierarchical Regression Analysis. Results indicate that the three identified VC affordances contribute to VCF in teenagers. In addition, teenage girls and older teenagers are more prone to VCF.
Geofence Warrants, Geospatial Innovation, and Implications for Data Privacy
Authors: McGowan Catherine
Published: October 2023

Geospatial technologies collect, analyze, and produce information about earth, humans, and objects through a convergence of geographic information systems, remote sensors, and global positioning systems. A microanalysis of Google's U.S. Patent 9,420,426 Inferring a current location based on a user location history (Duleba et al., 2016) reveals how geospatial innovation employs artificial intelligence (AI) to train computer‐vision models, infer, and impute geospatial data. The technical disclosures in patents offer a view within black‐boxed digital technologies to examine potential privacy implications of datafied citizens in a networked society. In patented geospatial innovation, user agency is subverted through AI and anonymous knowledge production.

Presently, the Fourth Amendment does not adequately protect citizens in a networked society. Data privacy legal cases are interpreted through a lens of inescapability (Tokson, 2020), which assumes perpetual agency to consent to sharing data. In short, agency‐centered privacy models are insufficient where AI can anonymously produce knowledge about an individual. Privacy implications are exemplified in geofence warrants—an investigative technique that searches location history to identify suspects in a geofenced region in the absence of evidence. This analysis demonstrates that digital privacy rights must expand to datafication models (Mai, 2016) centered on knowledge production.
When Push Comes To Pull: Place, Mobility, and Information Access for Vehicle Residents
Authors: Montague Kaitlin E.
Published: October 2023

This high‐exposure study explores the information seeking practices of a specific unstably housed, mobile population. Vehicle residents earn a wage but have chosen to move into their vehicles as a survival strategy during a time when housing expenses account for more than half of lower‐income Americans’ monthly income. Drawing from previous work that highlights the importance of place in information behavior, this study investigates the ways that places influence information seeking for a population whose information environment is ever‐changing. This study is informed by two sets of semi‐structured interviews with seven individuals, including information horizon interviews and guided tours, from November 2020‐June 2021. Key initial findings demonstrate that both place and mobility constrain and facilitate information seeking for participants. Overall, understanding the unique features and needs of this particular group results in a more thorough comprehension of their information seeking practices to better understand information and service provision, information inequality, and inequity.
Anti‐Black Racism, Anti‐Immigrant Sentiment, and Misinformation: A Recipe for Profound Societal Harm
Authors: Ndumu Ana , Orie Chuku Nenna
Published: October 2023

Mass media and big data constitute powerful information tools that fuel extremist, populist messaging. Demagogues turn to information tools to convey polarizing views, and governments increasingly rely on data and artificial intelligence to manage immigration. The speakers will describe how three global, deep‐seated, and historic societal ills—anti‐Black racism, anti‐immigrant sentiment, and misinformation—converge to typecast, vilify, and pathologize Black diasporic immigrants. The speakers will also share examples of anti‐Black, anti‐immigrant, and misinformed policymaking, rhetoric, and cultural norms within the United Kingdom and United States. Particular attention is granted to problematic assumptions within large‐scale population datasets that narrate migration tropes.
Tuning Out the Noise: Benchmarking Entity Extraction for Digitized Native American Literature
Authors: Parulian Nikolaus Nova , Dubnicek Ryan , Evans Daniel J. , Hu Yuerong , Layne‐Worthey Glen , Downie J. Stephen , Heaton Raina , Lu Kun , Orr Raymond I. , Magni Isabella , Walsh John A.
Published: October 2023

Named Entity Recognition (NER), the automated identification and tagging of entities in text, is a popular natural language processing task, and has the power to transform restricted data into open datasets of entities for further research. This project benchmarks four NER models–Stanford NER, BookNLP, spaCy‐trf and RoBERTa–to identify the most accurate approach and generate an open‐access, gold‐standard dataset of human annotated entities. To meet a real‐world use case, we benchmark these models on a sample dataset of sentences from Native American authored literature, identifying edge cases and areas of improvement for future NER work.