bluuebunny/crossref_metadata_2025_split huggingface dataset:
A Natural Language Processing Pipeline for Detecting Informal Data References in Academic Literature
Authors: Lafia Sara , Fan Lizhou , Hemphill Libby 
Published: October 2022

AbstractDiscovering authoritative links between publications and the datasets that they use can be a labor‐intensive process. We introduce a natural language processing pipeline that retrieves and reviews publications for informal references to research datasets, which complements the work of data librarians. We first describe the components of the pipeline and then apply it to expand an authoritative bibliography linking thousands of social science studies to the data‐related publications in which they are used. The pipeline increases recall for literature to review for inclusion in data‐related collections of publications and makes it possible to detect informal data references at scale. We contribute (1) a novel Named Entity Recognition (NER) model that reliably detects informal data references and (2) a dataset connecting items from social science literature with datasets they reference. Together, these contributions enable future work on data reference, data citation networks, and data reuse.
Learning Domain‐specific Semantic Representation from Weakly Supervised Data to Improve Research Dataset Retrieval
Authors: Luo Pengcheng , Hong Lingzi , Wang Jimin , Wang Shiqi , Guo Xin , Gao Zheng , Cho Sang Wouk 
Published: October 2022

AbstractAlong with the development of the data‐driven research paradigm, there are exponentially increasing datasets, which bring challenges to researchers in the efficient retrieval of relevant datasets. Previous studies mainly focused on query expansion methods based on sparse retrieval models to improve the accuracy and recall in retrieval. We investigated the use of semantically rich information to retrieve relevant datasets and the benefits of using domain‐specific dense vector representation as opposed to general representation. First, we used pairs of metadata fields that have semantic relevance to construct the domain‐specific weakly supervised training data. Then, a pre‐trained transformer‐based deep learning model is fine‐tuned on the training data using the contrastive learning method. Finally, dense vector representations of the queries and datasets are obtained based on the fine‐tuned model. The relevance of a dataset to a query is measured by the similarity between the vectors. To evaluate the performance of the proposed model, we collected 104,683 datasets from 13 research data repositories, recruited volunteers to design research‐oriented queries, and annotated the retrieval results. The experimental results show that compared with the domain‐independent fine‐tuned model, our proposed method can improve the NDCG@10 score by about 5%.
Delving into Data Science Methods in Response to the COVID‐19 Infodemic
Authors: Chong Miyoung , Shah Chirag , Shu Kai , He Jiangen , Hagen Loni 
Published: October 2022

AbstractThe circulation of myriad of information from diverse digital platforms during the COVID‐19 pandemic caused the unprecedented infodemic. Along with the increased case numbers, the shared information accelerated exponentially, especially via social media, and a large proportion of the daily distributed information was blended with myth, rumors, pseudoscience, or modified facts. Uncovering viral mis‐ and disinformation narratives and information voids is essential to a swift and effective response on delivering public health information and policy by the governments during a public health emergency. Although many studies have examined how information was circulated and shared during the COVID‐19 pandemic era, large gaps in literature exist as to how effectively to track, describe, and answer it. In this panel, the panelists propose and discuss data science methods to analyze the COVID‐19 infodemic. We hope our panel contribute to exploring more effective and applicable data science methods to investigate infodemic in crises.
A Framework for Co‐designing and Developing Participatory Storymaps with Aboriginal Communities
Authors: Du Jia Tina , Peters Stefan , Haines Jelina , Trevorrow Aunty Ellen , Jia Romy Menghao , Ziaian Tahereh 
Published: October 2022

AbstractThe research reported in this paper is part of an ongoing project on promoting Aboriginal cultural storytelling using mobile participatory mapping applications and web‐based interactive storymaps. This paper presents a conceptual framework for developing a co‐designed participatory storymap. The storymap aims to ubiquitously collect location‐based knowledge and stories in both online and offline modes, as well as present an interactive web map that dynamically integrates information recorded as georeferenced texts, images, audios, and videos. The participatory mapping has a potential to allow Aboriginal communities to capture and preserve their cultural heritage on their own using a smartphone or tablet. Ethical co‐designing process of implementing the storymaps is also discussed.
Data Paper as a Reward? Motivation, Consideration, and Perspective behind Data Paper Submission
Authors: Huang Pao Pei , Jeng Wei 
Published: October 2022

AbstractData papers, as one of the channels to encourage researchers to open up research data under the open science movement, are expected to provide strong incentives through formal citations. However, few studies have investigated the drivers of this emerging type of publication. This study examines researchers' motivations, and considerations for data paper submission, as well as their perspectives on this scholarly publication. Through an in‐depth interview approach with ten data paper authors, our preliminary results found that, researchers are often driven by extrinsic factors to increase their publications, and data papers are sometimes viewed as territory claims before further research. Although the academic community widely recognizes the benefits of publishing data papers, some still cast a doubtful eye on its academic value and impact. We anticipate such insights on the driving forces and point of views of data papers could provide opportunities for stakeholders to fill gaps and strengthen the open science ecosystem.
Cultivating Ecological Literacy: A Critical Framework for Understanding and Addressing Mis‐ and Disinformation
Authors: Paris Britt , Marcello Gina , Reynolds Rebecca 
Published: October 2022

ABSTRACTThis conceptual paper highlights limitations within existing approaches to mis and disinformation and offers a cross disciplinary approach that draws from social shaping of technology and critical informatics to explain and understand these complex informational phenomena. Different scholarly perspectives from policy, technical, and information literacy spheres, often narrowly focus on information practices of actors or components of the technical systems and policy frameworks undergirding these systems often their “locus of change”, or concept of the problem and solutions, do not acknowledge the interconnected complexities inherent to mis and disinformation. Our proposed conceptual intervention can be useful to the information science and technology research and teaching community as it offers opportunities to cultivate a complex form of what Milner and Phillips describe as “ecological literacy” to holistically understand the mis‐ and disinformation problem domain as an interconnected set of sociotechnical systems.
Researchers' Trends, Intentions, and Awareness, Towards Publications in Open Access
Authors: Aharony Noa , Hadad Shlomit 
Published: October 2022

ABSTRACTThis study examined Israeli researchers' trends, intentions and awareness regarding scientific publications in open access (OA) journals and repositories. A survey was distributed to 202 Israeli researchers. According to the findings, most researchers used a combination of closed (traditional/toll access) journals with OA gold/green routes. Researchers showed low awareness of OA key concepts, which was significantly associated with the tendency not to publish in OA. In addition, researchers who reported that there was a formal policy concerning publishing articles in high‐impact journals in their department tended to publish less in OA. The most common reasons that caused researchers not to publish in OA routes were lack of funding and lack of awareness. Conclusions present a need for an OA's declared policy as well as financial and informational support.
A Preliminary Study on App‐Switching during the Mobile Search
Authors: Liang Shaobo , Wei Ziyi , Zou Ning 
Published: October 2022

ABSTRACTUsers' mobile app switching behavior has recently received attention, particularly in the context of mobile search. This poster used Amazon MTurk to recruit 86 participants and used structured diaries and interviews to collect data on app switching behavior during the mobile search in daily scenes. We summarized the various behaviors after switching apps during the mobile search process. We also concluded why people switch apps based on information, personal characteristics, and mobile app features.
Impacts of Information Source and Perceived Health on Information Behavior
Authors: Park Min Sook , Lee Hyun Seung 
Published: October 2022

ABSTRACTThis preliminary study revisits a fundamental information problem of information behavior, focusing on needs, overload, and information source use, in the context of the COVID‐19 pandemic. The associations between the impact of information source use on the extent of information needs, being exposed to information, and feeling of overload was examined. Furthermore, to understand the impact of context on information behavior, the differences in the degree of information resource use, needs, exposure, and overload between the two groups with different levels of health were investigated.
Using Textual Analysis Tools to Identify Trends in Privacy Concern Research
Authors: Weinberger Maor , Bouhnik Dan 
Published: October 2022

ABSTRACTText mining is a research method that uses interdisciplinary techniques to identify patterns and trends in unstructured data and can be used to detect research trends and developments in various fields. Thus, this study attempts to identify research trends in the issue of privacy concern (PC), focusing on the differences between the first two decades of the 21st century. This is done by applying an automated textual analysis tool (Voyant Tools) on a vast corpora of academic papers conducted on this field. We found that while the first examined decade of PC research focused on commerce and marketing issues, there was much more research emphasis on the social dimension of privacy in the second decade. This difference was explained by the technological developments that were prominent in the respective decades. The research provided support for the use of textual analysis of academic literature as a tool to identify research trends in various fields, including technologically‐oriented fields.
Academic Casualization, Precarity, and Information Practices: A Scoping Review
Authors: Willson Rebekah , Stewart‐Robertson Owen , Julien Heidi , Given Lisa 
Published: October 2022

ABSTRACTIn the first phase of a larger research project exploring the information practices of contract academic staff, a review of the wider literature around academic casualization was conducted. This research begins to address the need for greater understanding of the experiences of these workers in the information‐intensive environments of higher education. A scoping review methodology was applied, and both academic and grey literature from multiple disciplines was reviewed. The literature points to casualization in academia as a growing phenomenon that has important consequences for staff, students, and universities themselves. This poster discusses the initial themes emerging from the literature, including: the precarity and marginalization of academic staff, the unrecognized emotional labor shaping information practices, and the impacts of multiple temporalities on the work, careers, and lives of such staff. The findings suggest the need for empirical research to address the lack of knowledge around the information environments of contract academics and set the stage for the next phases of the research project.
Performance, Usability, and User Experience of Rayyan for Systematic Reviews
Authors: Yu Fei , Liu Chuanrui , Sharmin Selina 
Published: October 2022

ABSTRACTThis study investigated performance, usability, and user experience with Rayyan, a systematic review (SR) tool. A remote usability inspection was conducted via the institutional Zoom platform. Each participant was randomly assigned to two groups and completed two citation screening sessions independently. Data were collected through pre‐ and post‐test questionnaires, screening sessions, and Systems Usability Scale (SUS) surveys. Thirteen participants completed the study. We found significant accuracy difference between Web Rayyan and its mobile app (t[12] = 1.877 p = .042), but no statistically sequential effect on screening performance. The average SUS scores of both Rayyan versions were below 68. More participants (77%) preferred Web Rayyan to the mobile app. The mobile Rayyan has potential if its user interface design can prevent errors or allow easy action reversal. As the first controlled experiment investigating both Web and mobile Rayyan, this study provides empirical evidence to guide the design, development, and selection of SR tools.
Nailing Jelly to the Wall: Teaching Technology in North American Graduate Archival Education Programs
Authors: Poole Alex H. , Todd‐Diaz Ashley 
Published: October 2022

ABSTRACTThis exploratory mixed‐methods case study relies on semistructured interviews with tenure‐track faculty members from North American graduate archival programs and a survey of North American graduate students and early career professionals to explore how archival education programs incorporate technology. We asked faculty members not only about the technologies they currently teach, but also their curriculum priorities, topical wish lists, and future challenges to and changes in archival education. We asked students and early career professionals whether they wished their graduate program had better prepared them technologically. Findings revealed that although both groups saw technology and digital curation as current and future areas of priority, students and early career professionals felt ill‐equipped to engage with technology in practice. We discuss the implications of these findings in light of the previous literature and adumbrate opportunities for future research.
Scientific Discourse on YouTube: Motivations for Citing Research in Comments
Authors: Striewski Sören , Zagovora Olga , Peters Isabella 
Published: October 2022

ABSTRACTYouTube is a valuable source of user‐generated content on a wide range of topics, and it encourages user participation through the use of a comment system. Video content is increasingly addressing scientific topics, and there is evidence that both academics and consumers use video descriptions and video comments to refer to academic research and scientific publications. Because commenting is a discursive behavior, this study will provide insights on why individuals post links to research publications in comments. For this, a qualitative content analysis and iterative coding approach were applied. Furthermore, the reasons for mentioning academic publications in comments were contrasted with the reasons for citing in scholarly works and with reasons for commenting on YouTube. We discovered that the primary motives for sharing research links were (1) providing more insights into the topic and (2) challenging information offered by other commentators.
“I'm really happy when sometimes I end up on a shelf that seems sort of right:” Historians' Reactions to the Cataloging and Classification of their Own Work
Authors: Watson Brian M. , Bullard Julia 
Published: October 2022

ABSTRACTThe goal of this paper is to report and discuss findings from an analysis of 14 qualitative semi‐structured interviews with historians and historical researchers on how cataloging systems commonly used in cultural heritage institutions such as libraries label and describe works dealing with the history of Indigenous Peoples of North America. These interviews are a subset of a larger project that interviewed 39 creators about their catalog record. In asking authors to evaluate their work's catalog record, this study utilized a novel method and theoretical framework, and therefore was able to derive several recommendations for future research and practice.
Bi‐Frequency Illumination: A Quantum‐Enhanced Protocol
Authors: Casariego Mateo , Omar Yasser , Sanz Mikel 
Published: October 2022

AbstractQuantum‐enhanced, idler‐free sensing protocol to measure the response of a target object to the frequency of a probe in a noisy and lossy scenario is proposed. In this protocol, a target with frequency‐dependent reflectivity embedded in a thermal bath is considered. The aim is to estimate the parameter , since it contains relevant information for different problems. For this, a bi‐frequency quantum state is employed as the resource, since it is necessary to capture the relevant information about the parameter. Computing the quantum Fisher informationHrelative to the parameter λ in an assumed neighborhood of for a two‐mode squeezed state (), and a pair of coherent states (), a quantum enhancement is shown in the estimation of λ. This quantum enhancement grows with the mean reflectivity of the probed object, and is noise‐resilient. Explicit formulas are derived for the optimal observables, and an experimental scheme based on elementary quantum optical transformations is proposed. Furthermore, this work opens the way to applications in both radar and medical imaging, in particular in the microwave domain.
Adaptive fixed‐time prescribed performance control of vehicular platoons with unknown dead‐zone and actuator saturation
Authors: Gao Zhenyu , Zhang Yi , Guo Ge 
Published: October 2022

AbstractThis article focuses on the problem of fixed‐time prescribed performance platoon control for heterogeneous vehicles with unknown dead‐zone and actuator saturation. First, an equivalent transformation is developed to approximate the actuator nonlinearity (i.e., dead‐zone and saturation), which reduces the complexity of controller design. Then, to guarantee the tracking errors converge to the predetermined region in the given time, a modified prescribed performance function is presented. Based on this, a novel adaptive sliding mode control scheme is developed in the context of fixed‐time theory, which is proved to be capable of ensuring individual vehicle stability and string stability in fixed time. In addition, under the proposed control scheme, the convergence time is independent of initial conditions of the system. Finally, numerical simulations are carried out to demonstrate the effectiveness of the proposed control scheme.
Pharmacological Investigations of Selected Multitarget‐Direct Ligands for the Treatment of Alzheimer's Disease
Authors: Manzoor Shoaib , Prajapati Santosh Kumar , Majumdar Shreyasi , Khurana Shilpi , Krishnamurthy Sairam , Hoda Nasimul 
Published: October 2022

AbstractAlzheimer's disease (AD) is a complex, degenerative condition linked to memory loss and cognitive degradation. The phenyl sulfonyl‐pyrimidine derivatives containing dimethoxy‐chloro substituent (BS‐10 and BS‐22) were previously recognized as multitarget‐directed ligands (MTDLs) due to their ability to inhibit acetylcholinesterase (AChE) at low nanomolar concentrations (IC50=47.33±0.02 and 51.36±0.04 nM respectively) while also reducing amyloid beta (Aβ) aggregation. In the current investigation, we investigated the in vivo and ex‐vivo effects of BS‐10 and BS‐22 chemicals on cognition and the cholinergic system. We have used scopolamine and Aβ1‐42 models of cognitive impairment which were measured during Y‐maze and passive avoidance apparatus. Results showed that BS‐10 at 10 mg/kg compared to BS‐22 at 20 mg/kg rescued memory impairment more significantly. Moreover, ex‐vivo and biochemical studies exhibited both compounds improved the hippocampal acetylcholine (Ach) level by reducing AChE activity as well as antioxidant properties. In addition, BS‐10 and BS‐22 attenuated Aβ1‐42 induced cognitive deficiency in rats during Y‐maze tests and significantly restored mitochondrial membrane potential and reduced the tau protein level in rats (p<0.05). In summary, our results indicated that MTDLs BS‐10 and BS‐22 would be a promising therapeutic approach in AD.
Selective and Mild Oxidation of 5‐Hydroxymethylfurfural to 5‐Hydroxymethyl‐2‐furancarboxylic Acid over Organic Polymer‐Supported Peroxidoniobium(V) Catalysts
Authors: Talukdar Hiya , Sultana Sazida Yasmin , Kalita Arnab , Islam Nashreen S. 
Published: October 2022

AbstractNiobium‐based homogeneous and heterogeneous catalysts were prepared by immobilizing triperoxidoniobium, [Nb(O2)3]− species on poly(sodium methacrylate), a linear water‐soluble polymer, and glycine functionalized poly(styrene‐divinylbenzene), a cross‐linked polymer resin, respectively. The compounds were characterized by elemental analysis, NMR (1H, 13C, and 93Nb), FTIR, Raman, XRD, XPS, SEM, EDX, UV‐Visible, BET, and TGA analysis. The catalysts were successfully applied in the targeted synthesis of 5‐hydroxymethyl‐2‐furancarboxylic acid (HMFCA) via 5‐hydroxymethylfurfural (HMF) oxidation with H2O2 as oxidant, under eco‐compatible reaction condition. Both the catalysts displayed excellent activity with 100 % conversion of HMF to yield HMFCA with 100 % selectivity. The oxidation protocol provided the highest TON and TOF values of 50 and of 78 h−1, respectively. The heterogeneity of the insoluble catalyst was confirmed by a hot filtration test. The heterogeneous catalyst showed impressive recyclability at least up to five consecutive cycles without any significant alteration in its activity or HMFCA selectivity. Overall, the use of water as a solvent, environmentally benign H2O2 as oxidant, reasonably low catalyst: substrate ratio, workable reaction temperature (60 °C), and acceptable reaction time (1.5 h), are the distinct green attributes of the developed catalytic procedure.
First‐Principles Study on the Electronic Properties and Mechanical Stabilities of Anion‐Cation Multiple‐Doped LiFePO4
Authors: Chen Jiaolan , Wang Fazhan , Yin Manxiang , Yao Chi 
Published: October 2022

AbstractIn this paper, N, Nb composite doped lithium iron phosphate structure was constructed, and its thermodynamic stability, intercalation voltages, volume change rate, electronic structure properties, and mechanical properties were systematically investigated using the first principles. The results of formation energy demonstrate that the N and Nb composite doping system meets the thermodynamic stability requirements and can exist consistently. In the process of de‐lithium, the volume change rate of the anion‐cation hybrid doping system is significantly decreased, and the intercalation voltage is increased, which indicates that the doping makes the cycling performance and energy density of the material improved. A radical shift in the material's electronic structure after doping is conducive to the enhanced conductivity of lithium iron phosphate. Besides, studies on the elastic properties of materials demonstrated that both N and Nb doping inhibited the generation of microcracks and diminished the occurrence of shear deformation.