Search (28295 results, page 1414 of 1415)

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Footnote

Beitrag in einem 'Special issue on neuro-information science'.

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Abstract

The name Paul appears in 13 epistles, but is he the real author? According to different biblical scholars, the number of letters really attributed to Paul varies from 4 to 13, with a majority agreeing on seven. This article proposes to revisit this authorship attribution problem by considering two effective methods (Burrows' Delta, Labbé's intertextual distance). Based on these results, a hierarchical clustering is then applied showing that four clusters can be derived, namely: {Colossians-Ephesians}, {1 and 2 Thessalonians}, {Titus, 1 and 2 Timothy}, and {Romans, Galatians, 1 and 2 Corinthians}. Moreover, a verification method based on the impostors' strategy indicates clearly that the group {Colossians-Ephesians} is written by the same author who seems not to be Paul. The same conclusion can be found for the cluster {Titus, 1 and 2 Timothy}. The Letter to Philemon stays as a singleton, without any close stylistic relationship with the other epistles. Finally, a group of four letters {Romans, Galatians, 1 and 2 Corinthians} is certainly written by the same author (Paul), but the verification protocol also indicates that 2 Corinthians is related to 1 Thessalonians, rendering a clear and simple interpretation difficult.

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Abstract

Purpose Taking the researchers' perspective, the purpose of this paper is to examine the types of context information needed to preserve data's meaning in ways that support data reuse. Design/methodology/approach This paper is based on a qualitative study of 105 researchers from three disciplinary communities: quantitative social science, archaeology and zoology. The study focused on researchers' most recent data reuse experience, particularly what they needed when deciding whether to reuse data. Findings Findings show that researchers mentioned 12 types of context information across three broad categories: data production information (data collection, specimen and artifact, data producer, data analysis, missing data, and research objectives); repository information (provenance, reputation and history, curation and digitization); and data reuse information (prior reuse, advice on reuse and terms of use). Originality/value This paper extends digital curation conversations to include the preservation of context as well as content to facilitate data reuse. When compared to prior research, findings show that there is some generalizability with respect to the types of context needed across different disciplines and data sharing and reuse environments. It also introduces several new context types. Relying on the perspective of researchers offers a more nuanced view that shows the importance of the different context types for each discipline and the ways disciplinary members thought about them. Both data producers and curators can benefit from knowing what to capture and manage during data collection and deposit into a repository.

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Abstract

Next-generation catalogues are providing opportunities for library professionals and users to interact, collaborate, and enhance core library functions. Technology, innovation, and creativity are all components that are merging to create a localized, online social space that brings our physical library services and experiences into an online environment. While patrons are comfortable creating user-generated information on commercial Web sites and social media Web sites, library professionals should be exploring alternative methods of use for these tools within the library setting. Can the library catalogue promote remote readers' advisory services and act as a localized "Google"? Will patrons or library professionals be the driving force behind user-generated content within our catalogues? How can cataloguers be sure that the integrity of their bibliographic records is protected while inviting additional data sources to display in our catalogues? As library catalogues bring our physical library services into the online environment, catalogues also begin to encroach or "mash-up" with other areas of librarianship that have not been part of a cataloguer's expertise. Using library catalogues beyond their traditional role as tools for discovery and access raises issues surrounding the expertise of library professionals and the benefits of collaboration between frontline and backroom staff.

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Abstract

The University of Toronto Libraries is currently reviewing technology to support its Collections U of T service. Collections U of T provides search and browse access to 375 digital collections (and over 203,000 digital objects) at the University of Toronto Libraries. Digital objects typically include special collections material from the university as well as faculty digital collections, all with unique metadata requirements. The service is currently supported by IIIF-enabled Islandora, with one Fedora back end and multiple Drupal sites per parent collection (see attached image). Like many institutions making use of Islandora, UTL is now confronted with Drupal 7 end of life and has begun to investigate a migration path forward. This article will summarise the Collections U of T functional requirements and lessons learned from our current technology stack. It will go on to outline our research to date for alternate solutions. The article will review both emerging micro-service solutions, as well as out-of-the-box platforms, to provide an overview of the digital collection technology landscape in 2019. Note that our research is focused on reviewing technology solutions for providing access to digital collections, as preservation services are offered through other services at the University of Toronto Libraries.

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Abstract

The rapid and wide dissemination of up-to-date, localized information is a central issue during disasters. Being attributed to the original 140-character length, Twitter provides its users with quick-posting and easy-forwarding features that facilitate the timely dissemination of warnings and alerts. However, a concern arises with respect to the terseness of tweets that restricts the amount of information conveyed in a tweet and thus increases a tweet's uncertainty. We tackle such concerns by proposing entropy as a measure for a tweet's uncertainty. Based on the perspectives of Uncertainty Reduction Theory (URT), we theorize that the more uncertain information of a disaster tweet, the higher the entropy, which will lead to a lower retweet count. By leveraging the statistical and predictive analyses, we provide evidence supporting that entropy validly and reliably assesses the uncertainty of a tweet. This study contributes to improving our understanding of information propagation on Twitter during disasters. Academically, we offer a new variable of entropy to measure a tweet's uncertainty, an important factor influencing disaster tweets' retweeting. Entropy plays a critical role to better comprehend URLs and emoticons as a means to convey information. Practically, this research suggests a set of guidelines for effectively crafting disaster messages on Twitter.

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Abstract

Scholarly identity refers to endeavors by scholars to promote their reputation, work and networks using online platforms such as ResearchGate, Academia.edu and Twitter. This exploratory research investigates benefits and drawbacks of scholarly identity efforts and avenues for potential library support. Design/methodology/approach Data from 30 semi-structured phone interviews with faculty, doctoral students and academic librarians were qualitatively analyzed using the constant comparisons method (Charmaz, 2014) and Goffman's (1959, 1967) theoretical concept of impression management. Findings Results reveal that use of online platforms enables academics to connect with others and disseminate their research. scholarly identity platforms have benefits, opportunities and offer possibilities for developing academic library support. They are also fraught with drawbacks/concerns, especially related to confusion, for-profit models and reputational risk. Research limitations/implications This exploratory study involves analysis of a small number of interviews (30) with self-selected social scientists from one discipline (communication) and librarians. It lacks gender, race/ethnicity and geographical diversity and focuses exclusively on individuals who use social networking sites for their scholarly identity practices. Social implications Results highlight benefits and risks of scholarly identity work and the potential for adopting practices that consider ethical dilemmas inherent in maintaining an online social media presence. They suggest continuing to develop library support that provides strategic guidance and information on legal responsibilities regarding copyright. Originality/value This research aims to understand the benefits and drawbacks of Scholarly Identity platforms and explore what support academic libraries might offer. It is among the first to investigate these topics comparing perspectives of faculty, doctoral students and librarians.

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Abstract

This study investigated the stability of Twitter counts of scientific publications over time. For this, we conducted an analysis of the availability statuses of over 2.6 million Twitter mentions received by the 1,154 most tweeted scientific publications recorded by Altmetric.com up to October 2017. The results show that of the Twitter mentions for these highly tweeted publications, about 14.3% had become unavailable by April 2019. Deletion of tweets by users is the main reason for unavailability, followed by suspension and protection of Twitter user accounts. This study proposes two measures for describing the Twitter dissemination structures of publications: Degree of Originality (i.e., the proportion of original tweets received by an article) and Degree of Concentration (i.e., the degree to which retweets concentrate on a single original tweet). Twitter metrics of publications with relatively low Degree of Originality and relatively high Degree of Concentration were observed to be at greater risk of becoming unstable due to the potential disappearance of their Twitter mentions. In light of these results, we emphasize the importance of paying attention to the potential risk of unstable Twitter counts, and the significance of identifying the different Twitter dissemination structures when studying the Twitter metrics of scientific publications.

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Abstract

Conventional rule-based approaches use exact template matching to capture linguistic information and necessarily need to enumerate all variations. We propose a novel flexible template generation and matching scheme called the principle-based approach (PBA) based on sequence alignment, and employ it for reference metadata extraction (RME) to demonstrate its effectiveness. The main contributions of this research are threefold. First, we propose an automatic template generation that can capture prominent patterns using the dominating set algorithm. Second, we devise an alignment-based template-matching technique that uses a logistic regression model, which makes it more general and flexible than pure rule-based approaches. Last, we apply PBA to RME on extensive cross-domain corpora and demonstrate its robustness and generality. Experiments reveal that the same set of templates produced by the PBA framework not only deliver consistent performance on various unseen domains, but also surpass hand-crafted knowledge (templates). We use four independent journal style test sets and one conference style test set in the experiments. When compared to renowned machine learning methods, such as conditional random fields (CRF), as well as recent deep learning methods (i.e., bi-directional long short-term memory with a CRF layer, Bi-LSTM-CRF), PBA has the best performance for all datasets.

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Abstract

A review of a range of epistemic concepts that are commonly researched was conducted with reference to conventional epistemology and with reference to foundational approaches to justification. These were assessed in relation to previous research undertaken linking information behavior and experience with paradigm, metatheory, and discourse. This research assesses how the epistemic concept is treated, both within information science and within disciplines that have affinities to the topics or agents that have been the subject of inquiry within the field. An attempt is made to clarify the types of connections that are associated with the epistemic concept and to provide a clearer view of how research focused on information behavior might consider the questions underpinning assumptions relating to knowledge and knowing. The symbiotic connection between epistemics and information science is advanced as a suitably nuanced conception of socially organized knowledge from which to define the appropriate level at which knowledge claims can be usefully advanced. It is proposed that fostering a better understanding of epistemics as a research practice might also provide for the development of a range of insights and methods that reflect the dynamic context within which the study of information behavior and information experience is located.

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Abstract

For a special library serving its parent organization, the design and use of classification schemes primarily need to support work activities. However, when the Prince Vivadhanajaya Library at the Bank of Thailand decided to open its doors to the public in 2018, the redesign of classification that serves both internal staff work and the public interest became a challenging task. We designed a classification scheme by integrating work centered classification design approach, classification as communication framework and the service design approach. The design process included developing empathy, ideation and implementation and evaluation. As a result, the new classification scheme, including seven main classes and thirty-seven level-one subclasses and twenty-two level-two subclasses, was primarily based on the organization's strategic plans, mapping with JEL Classification Codes, Library of Congress Classification (LCC) and Library of Congress Subject Headings (LCSH). The classification scheme also includes geographical code, author cutter number, publication year, volume number and copy number. Follow up interviews with twenty-three participants were conducted two years later to evaluate user experience as well as the staff's opinion of the new classification scheme. The feedback addressed favorable outcomes and challenges to be used for the next iteration of the library service design process.

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Abstract

Data reuse has recently become significant in academia and is providing new impetus for academic research. This prompts two questions: What precisely is the data reuse process? What is the connection between each participating element? To address these issues, 42 studies were reviewed to identify the stages and primary data reuse elements. A meta-synthesis was used to locate and analyze the studies, and inductive coding was used to organize the analytical process. We identified three stages of data reuse-initiation, exploration and collection, and repurposing-and explored how they interact and form iterative characteristics. The results illuminated the data reuse at each stage, including issues of data trust, data sources, scaffolds, and barriers. The results indicated that multisource data and human scaffolds promote reuse behavior effectively. Further, two data and information search patterns were extracted: reticular centripetal patterns and decentralized centripetal patterns. Three paths with elements cooperating through flexible functions and motivated by different action items were identified: data centers, human scaffolds, and publications. This study supports improvements for data infrastructure construction, data reuse, and data reuse research by providing a new perspective on the effect of information behavior and clarifying the stages and contextual relationships between various elements.

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Abstract

Information behavior and practices (IBP) research has been repeatedly criticized for having little impact on information systems development (ISD). Claiming that there is a complete disconnect would be an exaggeration but it is apparent that it is not always easy to translate findings of IBP research to workable design recommendations. Based on a reading of earlier literature and a closer investigation of three illustrative example contexts, this article underlines that the value of IBP research for ISD lies in its capability to inform ISD of the variety of ways people deal with information beyond individual systems, their own wants and designers' assumptions. Moreover, it highlights that the implications of information systems go beyond their primary users. Instead of overemphasizing the contextuality of findings, a part of IBP research would benefit from an increased focus on explicating its epistemological extents and limits and identifying, which findings are transferable, what distinguishes specific contexts, what are their defining constraints and priorities, and what aspects of their uniqueness are assumptions and simple clichés.

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Abstract

This paper presents a contribution to the study of bibliographic corpora through science mapping. From a graph representation of documents and their textual dimension, stochastic block models can provide a simultaneous clustering of documents and words that we call a domain-topic model. Previous work investigated the resulting topics, or word clusters, while ours focuses on the study of the document clusters we call domains. To enable the description and interactive navigation of domains, we introduce measures and interfaces that consider the structure of the model to relate both types of clusters. We then present a procedure that extends the block model to cluster metadata attributes of documents, which we call a domain-chained model, noting that our measures and interfaces transpose to metadata clusters. We provide an example application to a corpus relevant to current science, technology and society (STS) research and an interesting case for our approach: the abstracts presented between 1995 and 2017 at the American Society of Clinical Oncology Annual Meeting, the major oncology research conference. Through a sequence of domain-topic and domain-chained models, we identify and describe a group of domains that have notably grown through the last decades and which we relate to the establishment of "oncopolicy" as a major concern in oncology.

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Abstract

Each section header of an article has its distinct communicative function. Citations from distinct sections may be different regarding citing motivation. In this paper, we grouped section headers with similar functions as a structural function and defined the distribution of citations from structural functions for a paper as its citation structure. We aim to explore the relationship between citation structure and the future impact of a publication and disclose the relative importance among citations from different structural functions. Specifically, we proposed two citation counting methods and a citation life cycle identification method, by which the regression data were built. Subsequently, we employed a ridge regression model to predict the future impact of the paper and analyzed the relative weights of regressors. Based on documents collected from the Association for Computational Linguistics Anthology website, our empirical experiments disclosed that functional structure features improve the prediction accuracy of citation count prediction and that there exist differences among citations from different structural functions. Specifically, at the early stage of citation lifetime, citations from Introduction and Method are particularly important for perceiving future impact of papers, and citations from Result and Conclusion are also vital. However, early accumulation of citations from the Background seems less important.

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Abstract

Scientific novelty drives the efforts to invent new vaccines and solutions during the pandemic. First-time collaboration and international collaboration are two pivotal channels to expand teams' search activities for a broader scope of resources required to address the global challenge, which might facilitate the generation of novel ideas. Our analysis of 98,981 coronavirus papers suggests that scientific novelty measured by the BioBERT model that is pretrained on 29 million PubMed articles, and first-time collaboration increased after the outbreak of COVID-19, and international collaboration witnessed a sudden decrease. During COVID-19, papers with more first-time collaboration were found to be more novel and international collaboration did not hamper novelty as it had done in the normal periods. The findings suggest the necessity of reaching out for distant resources and the importance of maintaining a collaborative scientific community beyond nationalism during a pandemic.

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Abstract

LEarning TO Rank (LETOR) algorithms are usually trained on annotated corpora where a single relevance label is assigned to each available document-topic pair. Within the Cranfield framework, relevance labels result from merging either multiple expertly curated or crowdsourced human assessments. In this paper, we explore how to train LETOR models with relevance judgments distributions (either real or synthetically generated) assigned to document-topic pairs instead of single-valued relevance labels. We propose five new probabilistic loss functions to deal with the higher expressive power provided by relevance judgments distributions and show how they can be applied both to neural and gradient boosting machine (GBM) architectures. Moreover, we show how training a LETOR model on a sampled version of the relevance judgments from certain probability distributions can improve its performance when relying either on traditional or probabilistic loss functions. Finally, we validate our hypothesis on real-world crowdsourced relevance judgments distributions. Overall, we observe that relying on relevance judgments distributions to train different LETOR models can boost their performance and even outperform strong baselines such as LambdaMART on several test collections.

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Abstract

A pidgin metadata framework based on the concept of pidgin metadata is proposed to complement the limitations of existing approaches to metadata interoperability and to achieve more reliable metadata interoperability. The framework consists of three layers, with a hierarchical structure, and reflects the semantic and structural characteristics of various metadata. Layer 1 performs both an external function, serving as an anchor for semantic association between metadata elements, and an internal function, providing semantic categories that can encompass detailed elements. Layer 2 is an arbitrary layer composed of substantial elements from existing metadata and performs a function in which different metadata elements describing the same or similar aspects of information resources are associated with the semantic categories of Layer 1. Layer 3 implements the semantic relationships between Layer 1 and Layer 2 through the Resource Description Framework syntax. With this structure, the pidgin metadata framework can establish the criteria for semantic connection between different elements and fully reflect the complexity and heterogeneity among various metadata. Additionally, it is expected to provide a bibliographic environment that can achieve more reliable metadata interoperability than existing approaches by securing the communication between metadata.

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Abstract

An exploratory study investigated the factors affecting digital literacy training offered by local community organizations, such as public libraries. Theory based on the educational assessment and information literacy instruction literatures, community informatics, and situated learning theory served as a lens of investigation. Case studies of two public libraries and five other local community organizations were carried out. Data collection comprised: one-on-one interviews with administrators, instructors, and community members who received training; analysis of training documents; observations of training sessions; and a survey administered to clients who participated in these training sessions. Data analysis yielded the generation of a holistic conceptual framework. The framework identifies salient factors of the learning environment and program components that affect learning outcomes arising from digital literacy training led by local community organizations. Theoretical propositions are made. Member checks confirmed the validity of the study's findings. Results are compared to prior theory. Recommendations for practice highlight the need to organize and train staff, acquire sustainable funding, reach marginalized populations, offer convenient training times to end-users, better market the training, share and adopt best practices, and better collect and analyze program performance measurement data. Implications for future research also are identified.