Search (209 results, page 1 of 11)

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Abstract

Purpose The purpose of this paper is to investigate the knowledge and attitude about research data management, the use of data management methods and the perceived need for support, in relation to participants' field of research. Design/methodology/approach This is a quantitative study. Data were collected by an email survey and sent to 792 academic researchers and doctoral students. Total response rate was 18% (N = 139). The measurement instrument consisted of six sets of questions: about data management plans, the assignment of additional information to research data, about metadata, standard file naming systems, training at data management methods and the storing of research data. Findings The main finding is that knowledge about the procedures of data management is limited, and data management is not a normal practice in the researcher's work. They were, however, in general, of the opinion that the university should take the lead by recommending and offering access to the necessary tools of data management. Taken together, the results indicate that there is an urgent need to increase the researcher's understanding of the importance of data management that is based on professional knowledge and to provide them with resources and training that enables them to make effective and productive use of data management methods. Research limitations/implications The survey was sent to all members of the population but not a sample of it. Because of the response rate, the results cannot be generalized to all researchers at the university. Nevertheless, the findings may provide an important understanding about their research data procedures, in particular what characterizes their knowledge about data management and attitude towards it. Practical implications Awareness of these issues is essential for information specialists at academic libraries, together with other units within the universities, to be able to design infrastructures and develop services that suit the needs of the research community. The findings can be used, to develop data policies and services, based on professional knowledge of best practices and recognized standards that assist the research community at data management. Originality/value The study contributes to the existing literature about research data management by examining the results by participants' field of research. Recognition of the issues is critical in order for information specialists in collaboration with universities to design relevant infrastructures and services for academics and doctoral students that can promote their research data management.

Date

20. 1.2015 18:30:22

Source

Aslib journal of information management. 73(2021) no.2, S.322-341

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Abstract

Purpose This paper investigates how school teachers look for informational texts for their classrooms. Access to current, varied and authentic informational texts improves learning outcomes for K-12 students, but many teachers lack resources to expand and update readings. The Web offers freely available resources, but finding suitable ones is time-consuming. This research lays the groundwork for building tools to ease that burden. Design/methodology/approach This paper reports qualitative findings from a study in two stages: (1) a set of semistructured interviews, based on the critical incident technique, eliciting teachers' information-seeking practices and challenges; and (2) observations of teachers using a prototype teaching-oriented news search tool under a think-aloud protocol. Findings Teachers articulated different objectives and ways of using readings in their classrooms, goals and self-reported practices varied by experience level. Teachers struggled to formulate queries that are likely to return readings on specific course topics, instead searching directly for abstract topics. Experience differences did not translate into observable differences in search skill or success in the lab study. Originality/value There is limited work on teachers' information-seeking practices, particularly on how teachers look for texts for classroom use. This paper describes how teachers look for information in this context, setting the stage for future development and research on how to support this use case. Understanding and supporting teachers looking for information is a rich area for future research, due to the complexity of the information need and the fact that teachers are not looking for information for themselves.

Date

20. 1.2015 18:30:22

Source

Aslib journal of information management. 72(2020) no.5, S.725-744

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Abstract

This article describes experiments in the use of machine learning techniques at the British Library to assign language codes to catalog records, in order to provide information about the language of content of the resources described. In the first phase of the project, language codes were assigned to 1.15 million records with 99.7% confidence. The automated language identification tools developed will be used to contribute to future enhancement of over 4 million legacy records.

Date

2. 3.2020 19:04:22

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Abstract

CommunityRx is a theory-driven, information technology-based intervention, developed with and in a predominantly African American/Black community, that provides patients with personalized information (a "HealtheRx") about self-management and social care resources in their community. We described patient and clinician information sharing after exposure to the intervention during a clinical trial. Survey data from 145 patients (ages 45-74) and 121 clinicians were analyzed. Of patients who shared information at least once (49%), 47% reported sharing =3 times (range 1-14). Patient sharers were in poorer physical health (mean PCS 37.6 vs. 40.8, p = .05) than nonsharers and more likely to report going to a resource on their HealtheRx (79 vs. 41%, p = .05). Most patient sharers provided others a look at or copy of their HealtheRx, keeping the original. Patients used the HealtheRx to promote credibility of the information and communicate that resources were disease-specific and local. Half of clinicians shared HealtheRx resource information with peers; sharers were 3 times more likely than nonsharers to feel they were well-informed about resources to address social needs (55 vs. 18%, p < .01). Information sharing by clinicians and patients is an understudied mechanism that could amplify the effects of a growing class of community resource referral information technologies.

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Date

22. 5.2021 12:43:05

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Abstract

Authority control enhances the accessibility of library resources by controlling the choice and form of access points, improving users' ability to efficiently find the works most relevant to their information search. While authority control and the technologies that support its implementation continue to evolve, the underlying principles and purposes remain the same. Written primarily for a new generation of librarians, this paper illuminates the importance of authority control in cataloging and library database management, discusses its history, describes current practices, and introduces readers to trends and issues in the field, including future applications beyond the library catalog.

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Abstract

Purpose This study aims to develop an in-depth understanding of the underlying dynamics of an emergent shared information practice within a Facebook group, and the resources the group develops to sustain this practice. Design/methodology/approach In-depth semi-structured interviews were carried out with twenty members from the group. The findings are based on comparative analysis combined with narrative analysis and were interpreted using theories of situated learning and Community of Practice. Findings The study shows that although members of this multicultural mothers group endorsed different, sometimes opposing parenting practices, the group had to find common ground when sharing information. Managing these challenges was key to maintaining the group as an open information resource for all members. The group produced a shared repertoire of resources to maintain its activities, including norms, rules, shared understandings, and various monitoring activities. The shared online practice developed by the community is conceptualised in this article as an information practice requiring shared, community-specific understandings of what, when, and how information can or should be sought or shared in ways that are valued in this specific community. The findings show that this shared information practice is not static but continually evolves as members negotiate what is, or not, important for the group. Originality/value The research provides novel insights into the underlying dynamics of the emergence, management, and sustainability of a shared information practice within a contemporary mothers group on Facebook.

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Abstract

To what extent is the destiny of a scientific paper shaped by the cocitation network in which it is involved? What are the social contexts that can explain these structuring? Using bibliometric data, interviews with researchers, and social network analysis, this article proposes a typology based on egocentric cocitation networks that displays a quadruple structuring (before and after publication): polarization, clusterization, atomization, and attrition. It shows that the academic capital of the authors and the intellectual resources of their research are key factors of these destinies, as are the social relations between the authors concerned. The circumstances of the publishing are also correlated with the structuring of the egocentric cocitation networks, showing how socially embedded they are. Finally, the article discusses the contribution of these original networks to the analyze of scientific production and its dynamics.

Date

21. 3.2023 19:22:14

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Abstract

Integrating resources are distinct in that they change over time in such a way that their previous content is replaced with updated content. This study examines how integrating resources can be modeled using the entities and relationships of the IFLA Library Reference Model (LRM) and clarifies how they can be identified. While monographs have been extensively analyzed, integrating resources have received very little attention. Applying the model unmodified to integrating resources is neither practical nor theoretically sound. With the addition of two proposed relationships, the model can be extended to accommodate the diachronic relationship intrinsic between expressions and manifestations exhibited by integrating resources.

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Abstract

It is widely recognized that affect and cognition can have a profound influence on information behavior. However, how these factors affect information behavior in the context of chronic, stigmatized conditions is less clear. This study employed a qualitative approach to explore the interrelatedness of affect, cognition, and information behavior among persons with fibromyalgia. Persons with fibromyalgia were recruited using multiple recruitment strategies (e.g., listservs and social media) for an interview study. The interview guided participants to tell their story as they drew a timeline. Data were analyzed using qualitative data analysis methods based on the Grounded Theory Methodology. Participants' narratives illustrated that affect and cognition had diverse effects on participants' information and health behaviors: uncertainty and negative affect promoted information seeking; affect and information facilitated reconceptualization and self-growth; and online venues facilitated venting, gave rise to validating experiences, and provided opportunities to help others. This study's findings contribute to extant knowledge by connecting affect, cognition, and action in long-term health management. The study also provides recommendations for practice: a need to focus on practical management strategies in information provision, develop information resources to address the needs of diverse populations, and promote empathy and awareness concerning invisible conditions.

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Abstract

For laypeople, searching online health information resources can be challenging due to topic complexity and the large number of online sources with differing quality. The goal of this article is to examine, among all the available online sources, which online sources laypeople select to address their health-related information needs, and whether or how much the severity of a health condition influences their selection. Twenty-four participants were recruited individually, and each was asked (using a retrieval system called HIS) to search for information regarding a severe health condition and a mild health condition, respectively. The selected online health information sources were automatically captured by the HIS system and classified at both the website and webpage levels. Participants' selection behavior patterns were then plotted across the whole information-seeking process. Our results demonstrate that laypeople's source selection fluctuates during the health information-seeking process, and also varies by the severity of health conditions. This study reveals laypeople's real usage of different types of online health information sources, and engenders implications to the design of search engines, as well as the development of health literacy programs.

Date

12.11.2020 13:22:09

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Abstract

In this article, we present a method to automatically build large labeled datasets for the author ambiguity problem in the academic world by leveraging the authoritative academic resources, ORCID and DOI. Using the method, we built LAGOS-AND, two large, gold-standard sub-datasets for author name disambiguation (AND), of which LAGOS-AND-BLOCK is created for clustering-based AND research and LAGOS-AND-PAIRWISE is created for classification-based AND research. Our LAGOS-AND datasets are substantially different from the existing ones. The initial versions of the datasets (v1.0, released in February 2021) include 7.5 M citations authored by 798 K unique authors (LAGOS-AND-BLOCK) and close to 1 M instances (LAGOS-AND-PAIRWISE). And both datasets show close similarities to the whole Microsoft Academic Graph (MAG) across validations of six facets. In building the datasets, we reveal the variation degrees of last names in three literature databases, PubMed, MAG, and Semantic Scholar, by comparing author names hosted to the authors' official last names shown on the ORCID pages. Furthermore, we evaluate several baseline disambiguation methods as well as the MAG's author IDs system on our datasets, and the evaluation helps identify several interesting findings. We hope the datasets and findings will bring new insights for future studies. The code and datasets are publicly available.

Date

22. 1.2023 18:40:36

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Abstract

Journal lists are instruments to categorize, compare, and assess research and scholarly publications. Our study investigates the remarkable proliferation of such journal lists in China, analyses their underlying values, quality criteria and ranking principles, and specifies how concerns specific to the Chinese research policy and publishing system inform these lists. Discouraged lists of "bad journals" reflect concerns over inferior research publications, but also the involved drain on public resources. Endorsed lists of "good journals" are based on criteria valued in research policy, reflecting the distinctive administrative logic of state-led Chinese research and publishing policy, ascribing worth to scientific journals for its specific national and institutional needs. In this regard, the criteria used for journal list construction are contextual and reflect the challenges of public resource allocation in a market-led publication system. Chinese journal lists therefore reflect research policy changes, such as a shift away from output-dominated research evaluation, the specific concerns about research misconduct, and balancing national research needs against international standards, resulting in distinctly Chinese quality criteria. However, contrasting concerns and inaccuracies lead to contradictions in the "qualify" and "disqualify" binary logic and demonstrate inherent tensions and limitations in journal lists as policy tools.

Date

22. 9.2023 16:39:23

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Abstract

Interdisciplinarity implies the previous existence of disciplinary fields and not their dissolution. As a general objective, we propose to establish an initial approach to the emphasis given to interdisciplinarity in the teaching of KO, through the teaching staff responsible for postgraduate courses focused on -or related to the KO, in Ibero-American universities. For conducting the research, the framework and distribution of a survey addressed to teachers is proposed, based on four lines of action: 1. The way teachers manage the concept of interdisciplinarity. 2. The place that teachers give to interdisciplinarity in KO. 3. Assessment of interdisciplinary content that teachers incorporate into their postgraduate courses. 4. Set of teaching strategies and resources used by teachers to include interdisciplinarity in the teaching of KO. The study analyzed 22 responses. Preliminary results show that KO teachers recognize the influence of other disciplines in concepts, theories, methods, and applications, but no consensus has been reached regarding which disciplines and authors are the ones who build interdisciplinary bridges. Among other conclusions, the study strongly suggests that environmental and social tensions are reflected in subject representation, especially in the construction of friendly knowl­edge organization systems with interdisciplinary visions, and in the expressions through which information is sought.

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Abstract

Domains represent concepts which belong to specific parts of the world. The particularized meaning of words linguistically encoding such domain concepts are provided by domain specific resources. The explicit meaning of such words are increasingly captured computationally using domain-specific ontologies, which, even for the same reference domain, are most often than not semantically incompatible. As information systems that rely on domain ontologies expand, there is a growing need to not only design domain ontologies and domain ontology-grounded Knowl­edge Graphs (KGs) but also to align them to general standards and conventions for interoperability. This often presents an insurmountable challenge to domain experts who have to additionally learn the construction of domain ontologies and KGs. Until now, several research methodologies have been proposed by different research groups using different technical approaches and based on scenarios of different domains of application. However, no methodology has been proposed which not only facilitates designing conceptually well-founded ontologies, but is also, equally, grounded in the general pedagogical principles of knowl­edge organization and, thereby, flexible enough to teach, and reproduce vis-à-vis domain experts. The purpose of this paper is to provide such a general, pedagogically flexible semantic knowl­edge modelling methodology. We exemplify the methodology by examples and illustrations from a professional-level digital healthcare course, and conclude with an evaluation grounded in technological parameters as well as user experience design principles.

Date

20.11.2023 17:19:22

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Abstract

The transition from secondary education to higher education could be challenging for most freshmen. For students who fail to adjust to university life smoothly, their status may worsen if the university cannot offer timely and proper guidance. Helping students adapt to university life is a long-term goal for any academic institution. Therefore, understanding the nature of the maladaptation phenomenon and the early prediction of "at-risk" students are crucial tasks that urgently need to be tackled effectively. This article aims to analyze the relevant factors that affect the maladaptation phenomenon and predict this phenomenon in advance. We develop a prediction framework (MAladaptive STudEnt pRediction, MASTER) for the early prediction of students with maladaptation. First, our framework uses the SMOTE (Synthetic Minority Oversampling Technique) algorithm to solve the data label imbalance issue. Moreover, a novel ensemble algorithm, priority forest, is proposed for outputting ranks instead of binary results, which enables us to perform proactive interventions in a prioritized manner where limited education resources are available. Experimental results on real-world education datasets demonstrate that the MASTER framework outperforms other state-of-art methods.

Date

27.12.2022 18:34:22

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Abstract

The forced displacement and transnational migration of millions of people around the world is a growing phenomenon that has been met with increased surveillance and datafication by a variety of actors. Small humanitarian organizations that help irregular migrants in the United States frequently do not have the resources or expertise to fully address the implications of collecting, storing, and using data about the vulnerable populations they serve. As a result, there is a risk that their work could exacerbate the vulnerabilities of the very same migrants they are trying to help. In this study, we propose a conceptual framework for protecting privacy in the context of humanitarian information activities (HIA) with irregular migrants. We draw from a review of the academic literature as well as interviews with individuals affiliated with several US-based humanitarian organizations, higher education institutions, and nonprofit organizations that provide support to undocumented migrants. We discuss 3 primary issues: (i) HIA present both technological and human risks; (ii) the expectation of privacy self-management by vulnerable populations is problematic; and (iii) there is a need for robust, actionable, privacy-related guidelines for HIA. We suggest 5 recommendations to strengthen the privacy protection offered to undocumented migrants and other vulnerable populations.

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Abstract

Previous studies on crisis knowledge organization mostly focused on the categorization of crisis knowledge without regarding its dynamic trend and temporal-spatial features. In order to emphasize the dynamic factors of crisis collaboration, a fine-grained crisis knowledge model is proposed by integrating temporal-spatial analysis based on ontology, which is one of the commonly used methods for knowledge organization. The reconstruction of ontologybased crisis knowledge will be implemented through three steps: analyzing temporal-spatial features of crisis knowledge, reconstructing crisis knowledge ontology, and verifying the temporal-spatial ontology. In the process of ontology reconstruction, the main classes and properties of the domain will be identified by investigating the crisis information resources. Meanwhile the fine-grained crisis ontology will be achieved at the level of characteristic representation of crisis knowledge including temporal relationship, spatial relationship, and semantic relationship. Finally, we conducted case addition and system implementation to verify our crisis knowledge model. This ontology-based knowledge organization method theoretically optimizes the static organizational structure of crisis knowledge, improving the flexibility of knowledge organization and efficiency of emergency response. In practice, the proposed fine-grained ontology is supposed to be more in line with the real situation of emergency collaboration and management. Moreover, it will also provide the knowledge base for decision-making during rescue process.

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Abstract

Data lifecycle models are used to visualize the stages data resources pass through from creation to completion of a research project and beyond. Although helpful, these models tend to depict idealized and impersonal circumstances that often involve curation actions taken by researchers themselves, while neglecting to represent dynamics particular to researchers' lives and careers. Meanwhile, research data are still infrequently managed successfully according to these models, which is a particular concern for "long tail" data, where sharing tends to depend on individual researchers' decisions and preservation actions. The paper addresses these considerations by exploring the ways in which long tail data lifecycles are entwined with human career lifecycles. Through interviews with astronomers, six affective dimensions that may impact data and career lifecycle dynamics are identified: painstakingness, loose ends, altruism, intellectual passion, legacy, and nostalgia. Building upon these insights and holistically drawing connections between human information behavior and data lifecycle modeling literature and frameworks, a researcher-centered lifecycle model is proposed that seeks to depict the unique motivations and changing needs of researchers to share data throughout the courses of their careers. The paper concludes with suggestions for theoretical development and curatorial interventions in current data lifecycle modeling and data management practice.

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Abstract

There are several ways to employ machine learning for automating subject indexing. One popular strategy is to utilize a supervised learning algorithm to train a model on a set of documents that have been manually indexed by subject matter using a standard vocabulary. The resulting model can then predict the subject of new and previously unseen documents by identifying patterns learned from the training data. To do this, the first step is to gather a large dataset of documents and manually assign each document a set of subject keywords/descriptors from a controlled vocabulary (e.g., from Agrovoc). Next, the dataset (obtained from Agris) can be divided into - i) a training dataset, and ii) a test dataset. The training dataset is used to train the model, while the test dataset is used to evaluate the model's performance. Machine learning can be a powerful tool for automating the process of subject indexing. This research is an attempt to apply Annif (http://annif. org/), an open-source AI/ML framework, to autogenerate subject keywords/descriptors for documentary resources in the domain of agriculture. The training dataset is obtained from Agris, which applies the Agrovoc thesaurus as a vocabulary tool (https://www.fao.org/agris/download).

Source

¬SRELS Journal of Information Management. 60(2023) no.2, S.85-95