15,126 research outputs found

    Issues in student training and use of electronic bibliographic databases

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    In an article in this journal Ottewill and Hudson (1997) raised a number of issues concerning students’ use of electronic bibliographic databases. They emphasized the need for co‐operation between academics and librarians in database training and in coursework where databases would be used. We report a project on students’ use of bibliographic databases. Our findings reveal that access to these databases, whilst solving many of the problems students experience in sourcing reference material for coursework and research, raises new intellectual problems due to the sheer breadth and depth of their coverage of subject matter. Typically database training programmes focus on search skills and the use of different interfaces. However, our findings demonstrate that students should be encouraged to develop a more critical perspective on databases since these can be seductive, time‐consuming and, in certain circumstances, counterproductive resources. Students would benefit from more guidance on the quality cues that academics and librarians employ when evaluating different databases and their contents

    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 comparison of the performance of seven key bibliographic databases in identifying all relevant systematic reviews of interventions for hypertension

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    BACKGROUND: Bibliographic databases are the primary resource for identifying systematic reviews of health care interventions. Reliable retrieval of systematic reviews depends on the scope of indexing used by database providers. Therefore, searching one database may be insufficient, but it is unclear how many need to be searched. We sought to evaluate the performance of seven major bibliographic databases for the identification of systematic reviews for hypertension. METHODS: We searched seven databases (Cochrane library, Database of Abstracts of Reviews of Effects (DARE), Excerpta Medica Database (EMBASE), Epistemonikos, Medical Literature Analysis and Retrieval System Online (MEDLINE), PubMed Health and Turning Research Into Practice (TRIP)) from 2003 to 2015 for systematic reviews of any intervention for hypertension. Citations retrieved were screened for relevance, coded and checked for screening consistency using a fuzzy text matching query. The performance of each database was assessed by calculating its sensitivity, precision, the number of missed reviews and the number of unique records retrieved. RESULTS: Four hundred systematic reviews were identified for inclusion from 11,381 citations retrieved from seven databases. No single database identified all the retrieved systematic reviews for hypertension. EMBASE identified the most reviews (sensitivity 69 %) but also retrieved the most irrelevant citations with 7.2 % precision (Pr). The sensitivity of the Cochrane library was 60 %, DARE 57 %, MEDLINE 57 %, PubMed Health 53 %, Epistemonikos 49 % and TRIP 33 %. EMBASE contained the highest number of unique records (n = 43). The Cochrane library identified seven unique records and had the highest precision (Pr = 30 %), followed by Epistemonikos (n = 2, Pr = 19 %). No unique records were found in PubMed Health (Pr = 24 %) DARE (Pr = 21 %), TRIP (Pr = 10 %) or MEDLINE (Pr = 10 %). Searching EMBASE and the Cochrane library identified 88 % of all systematic reviews in the reference set, and searching the freely available databases (Cochrane, Epistemonikos, MEDLINE) identified 83 % of all the reviews. The databases were re-analysed after systematic reviews of non-conventional interventions (e.g. yoga, acupuncture) were removed. Similarly, no database identified all the retrieved systematic reviews. EMBASE identified the most relevant systematic reviews (sensitivity 73 %) but also retrieved the most irrelevant citations with Pr = 5 %. The sensitivity of the Cochrane database was 62 %, followed by MEDLINE (60 %), DARE (55 %), PubMed Health (54 %), Epistemonikos (50 %) and TRIP (31 %). The precision of the Cochrane library was the highest (20 %), followed by PubMed Health (Pr = 16 %), DARE (Pr = 13 %), Epistemonikos (Pr = 12 %), MEDLINE (Pr = 6 %), TRIP (Pr = 6 %) and EMBASE (Pr = 5 %). EMBASE contained the most unique records (n = 34). The Cochrane library identified seven unique records. The other databases held no unique records. CONCLUSIONS: The coverage of bibliographic databases varies considerably due to differences in their scope and content. Researchers wishing to identify systematic reviews should not rely on one database but search multiple databases

    CitNetExplorer: A new software tool for analyzing and visualizing citation networks

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    We present CitNetExplorer, a new software tool for analyzing and visualizing citation networks of scientific publications. CitNetExplorer can for instance be used to study the development of a research field, to delineate the literature on a research topic, and to support literature reviewing. We first introduce the main concepts that need to be understood when working with CitNetExplorer. We then demonstrate CitNetExplorer by using the tool to analyze the scientometric literature and the literature on community detection in networks. Finally, we discuss some technical details on the construction, visualization, and analysis of citation networks in CitNetExplorer

    "Seed+Expand": A validated methodology for creating high quality publication oeuvres of individual researchers

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    The study of science at the individual micro-level frequently requires the disambiguation of author names. The creation of author's publication oeuvres involves matching the list of unique author names to names used in publication databases. Despite recent progress in the development of unique author identifiers, e.g., ORCID, VIVO, or DAI, author disambiguation remains a key problem when it comes to large-scale bibliometric analysis using data from multiple databases. This study introduces and validates a new methodology called seed+expand for semi-automatic bibliographic data collection for a given set of individual authors. Specifically, we identify the oeuvre of a set of Dutch full professors during the period 1980-2011. In particular, we combine author records from the National Research Information System (NARCIS) with publication records from the Web of Science. Starting with an initial list of 8,378 names, we identify "seed publications" for each author using five different approaches. Subsequently, we "expand" the set of publication in three different approaches. The different approaches are compared and resulting oeuvres are evaluated on precision and recall using a "gold standard" dataset of authors for which verified publications in the period 2001-2010 are available.Comment: Paper accepted for the ISSI 2013, small changes in the text due to referee comments, one figure added (Fig 3

    Impact of the Information and Communication Technologies on the Education of Students with Down Syndrome: a Bibliometric Study (2008- 2018)

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    This article analyzes the impact of the Information and Communication Technologies (ICT) on students with Down syndrome through the consult of scientific articles published during the 2008 to 2018 period, in five scientific journal databases utilized in the academic world. Through a descriptive and quantitative methodology, the most significant bibliometric data according to citation index is shown. Likewise, a methodology based on the analysis of co-words and clustering techniques is applied through a bibliometric maps, in order to determine the fields of scientific study. The results show that articles published have a medium-low index of impact. There are linked with the importance of using ICT with these students, from educational inclusion and accessibility perspective

    Contextualization of topics - browsing through terms, authors, journals and cluster allocations

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    This paper builds on an innovative Information Retrieval tool, Ariadne. The tool has been developed as an interactive network visualization and browsing tool for large-scale bibliographic databases. It basically allows to gain insights into a topic by contextualizing a search query (Koopman et al., 2015). In this paper, we apply the Ariadne tool to a far smaller dataset of 111,616 documents in astronomy and astrophysics. Labeled as the Berlin dataset, this data have been used by several research teams to apply and later compare different clustering algorithms. The quest for this team effort is how to delineate topics. This paper contributes to this challenge in two different ways. First, we produce one of the different cluster solution and second, we use Ariadne (the method behind it, and the interface - called LittleAriadne) to display cluster solutions of the different group members. By providing a tool that allows the visual inspection of the similarity of article clusters produced by different algorithms, we present a complementary approach to other possible means of comparison. More particular, we discuss how we can - with LittleAriadne - browse through the network of topical terms, authors, journals and cluster solutions in the Berlin dataset and compare cluster solutions as well as see their context.Comment: proceedings of the ISSI 2015 conference (accepted

    ADAPTS: An Intelligent Sustainable Conceptual Framework for Engineering Projects

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    This paper presents a conceptual framework for the optimization of environmental sustainability in engineering projects, both for products and industrial facilities or processes. The main objective of this work is to propose a conceptual framework to help researchers to approach optimization under the criteria of sustainability of engineering projects, making use of current Machine Learning techniques. For the development of this conceptual framework, a bibliographic search has been carried out on the Web of Science. From the selected documents and through a hermeneutic procedure the texts have been analyzed and the conceptual framework has been carried out. A graphic representation pyramid shape is shown to clearly define the variables of the proposed conceptual framework and their relationships. The conceptual framework consists of 5 dimensions; its acronym is ADAPTS. In the base are: (1) the Application to which it is intended, (2) the available DAta, (3) the APproach under which it is operated, and (4) the machine learning Tool used. At the top of the pyramid, (5) the necessary Sensing. A study case is proposed to show its applicability. This work is part of a broader line of research, in terms of optimization under sustainability criteria.Telefónica Chair “Intelligence in Networks” of the University of Seville (Spain
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