28,862 research outputs found

    The structure of the Arts & Humanities Citation Index: A mapping on the basis of aggregated citations among 1,157 journals

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    Using the Arts & Humanities Citation Index (A&HCI) 2008, we apply mapping techniques previously developed for mapping journal structures in the Science and Social Science Citation Indices. Citation relations among the 110,718 records were aggregated at the level of 1,157 journals specific to the A&HCI, and the journal structures are questioned on whether a cognitive structure can be reconstructed and visualized. Both cosine-normalization (bottom up) and factor analysis (top down) suggest a division into approximately twelve subsets. The relations among these subsets are explored using various visualization techniques. However, we were not able to retrieve this structure using the ISI Subject Categories, including the 25 categories which are specific to the A&HCI. We discuss options for validation such as against the categories of the Humanities Indicators of the American Academy of Arts and Sciences, the panel structure of the European Reference Index for the Humanities (ERIH), and compare our results with the curriculum organization of the Humanities Section of the College of Letters and Sciences of UCLA as an example of institutional organization

    Bibliometric Maps of BIM and BIM in Universities: A Comparative Analysis

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    Building Information Modeling (BIM) is increasingly important in the architecture and engineering fields, and especially in the field of sustainability through the study of energy. This study performs a bibliometric study analysis of BIM publications based on the Scopus database during the whole period from 2003 to 2018. The aim was to establish a comparison of bibliometric maps of the building information model and BIM in universities. The analyzed data included 4307 records produced by a total of 10,636 distinct authors from 314 institutions. Engineering and computer science were found to be the main scientific fields involved in BIM research. Architectural design are the central theme keywords, followed by information theory and construction industry. The final stage of the study focuses on the detection of clusters in which global research in this field is grouped. The main clusters found were those related to the BIM cycle, including construction management, documentation and analysis, architecture and design, construction/fabrication, and operation and maintenance (related to energy or sustainability). However, the clusters of the last phases such as demolition and renovation are not present, which indicates that this field suntil needs to be further developed and researched. With regard to the evolution of research, it has been observed how information technologies have been integrated over the entire spectrum of internet of things (IoT). A final key factor in the implementation of the BIM is its inclusion in the curriculum of technical careers related to areas of construction such as civil engineering or architecture

    Understanding audiences from industry sectors in knowledge exchange

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    This essay discusses the concept of Knowledge Exchange between industry and academia. In particular it focuses on ways in which academic organisations can learn about different industry sectors in order to identify potential Knowledge Exchange partners and how they operate. Three case studies of scoping approaches taken in the understanding of these audiences are presented followed by a discussion of their different strengths and weaknesses. This essay concludes with presentation of an initial framework for scoping and suggestions for where this work can be developed in the future

    What do faculties specializing in brain and neural sciences think about, and how do they approach, brain-friendly teaching-learning in Iran?

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    Objective: to investigate the perspectives and experiences of the faculties specializing in brain and neural sciences regarding brain-friendly teaching-learning in Iran. Methods: 17 faculties from 5 universities were selected by purposive sampling (2018). In-depth semi-structured interviews with directed content analysis were used. Results: 31 sub-subcategories, 10 subcategories, and 4 categories were formed according to the “General teaching model”. “Mentorship” was a newly added category. Conclusions: A neuro-educational approach that consider the roles of the learner’s brain uniqueness, executive function facilitation, and the valence system are important to learning. Such learning can be facilitated through cognitive load considerations, repetition, deep questioning, visualization, feedback, and reflection. The contextualized, problem-oriented, social, multi-sensory, experiential, spaced learning, and brain-friendly evaluation must be considered. Mentorship is important for coaching and emotional facilitation

    The Research Space: using the career paths of scholars to predict the evolution of the research output of individuals, institutions, and nations

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    In recent years scholars have built maps of science by connecting the academic fields that cite each other, are cited together, or that cite a similar literature. But since scholars cannot always publish in the fields they cite, or that cite them, these science maps are only rough proxies for the potential of a scholar, organization, or country, to enter a new academic field. Here we use a large dataset of scholarly publications disambiguated at the individual level to create a map of science-or research space-where links connect pairs of fields based on the probability that an individual has published in both of them. We find that the research space is a significantly more accurate predictor of the fields that individuals and organizations will enter in the future than citation based science maps. At the country level, however, the research space and citations based science maps are equally accurate. These findings show that data on career trajectories-the set of fields that individuals have previously published in-provide more accurate predictors of future research output for more focalized units-such as individuals or organizations-than citation based science maps

    Software tools for conducting bibliometric analysis in science: An up-to-date review

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    Bibliometrics has become an essential tool for assessing and analyzing the output of scientists, cooperation between universities, the effect of state-owned science funding on national research and development performance and educational efficiency, among other applications. Therefore, professionals and scientists need a range of theoretical and practical tools to measure experimental data. This review aims to provide an up-to-date review of the various tools available for conducting bibliometric and scientometric analyses, including the sources of data acquisition, performance analysis and visualization tools. The included tools were divided into three categories: general bibliometric and performance analysis, science mapping analysis, and libraries; a description of all of them is provided. A comparative analysis of the database sources support, pre-processing capabilities, analysis and visualization options were also provided in order to facilitate its understanding. Although there are numerous bibliometric databases to obtain data for bibliometric and scientometric analysis, they have been developed for a different purpose. The number of exportable records is between 500 and 50,000 and the coverage of the different science fields is unequal in each database. Concerning the analyzed tools, Bibliometrix contains the more extensive set of techniques and suitable for practitioners through Biblioshiny. VOSviewer has a fantastic visualization and is capable of loading and exporting information from many sources. SciMAT is the tool with a powerful pre-processing and export capability. In views of the variability of features, the users need to decide the desired analysis output and chose the option that better fits into their aims

    A visual exploration workflow as enabler for the exploitation of Linked Open Data

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    Abstract. Semantically annotating and interlinking Open Data results in Linked Open Data which concisely and unambiguously describes a knowledge domain. However, the uptake of the Linked Data depends on its usefulness to non-Semantic Web experts. Failing to support data consumers to understand the added-value of Linked Data and possible exploitation opportunities could inhibit its diffusion. In this paper, we propose an interactive visual workflow for discovering and ex-ploring Linked Open Data. We implemented the workflow considering academic library metadata and carried out a qualitative evaluation. We assessed the work-flow’s potential impact on data consumers which bridges the offer: published Linked Open Data; and the demand as requests for: (i) higher quality data; and (ii) more applications that re-use data. More than 70 % of the 34 test users agreed that the workflow fulfills its goal: it facilitates non-Semantic Web experts to un-derstand the potential of Linked Open Data.
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