26,910 research outputs found

    Untangling the Web of E-Research: Towards a Sociology of Online Knowledge

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    e-Research is a rapidly growing research area, both in terms of publications and in terms of funding. In this article we argue that it is necessary to reconceptualize the ways in which we seek to measure and understand e-Research by developing a sociology of knowledge based on our understanding of how science has been transformed historically and shifted into online forms. Next, we report data which allows the examination of e-Research through a variety of traces in order to begin to understand how the knowledge in the realm of e-Research has been and is being constructed. These data indicate that e-Research has had a variable impact in different fields of research. We argue that only an overall account of the scale and scope of e-Research within and between different fields makes it possible to identify the organizational coherence and diffuseness of e-Research in terms of its socio-technical networks, and thus to identify the contributions of e-Research to various research fronts in the online production of knowledge

    Bibliometric Perspectives on Medical Innovation using the Medical Subject Headings (MeSH) of PubMed

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    Multiple perspectives on the nonlinear processes of medical innovations can be distinguished and combined using the Medical Subject Headings (MeSH) of the Medline database. Focusing on three main branches-"diseases," "drugs and chemicals," and "techniques and equipment"-we use base maps and overlay techniques to investigate the translations and interactions and thus to gain a bibliometric perspective on the dynamics of medical innovations. To this end, we first analyze the Medline database, the MeSH index tree, and the various options for a static mapping from different perspectives and at different levels of aggregation. Following a specific innovation (RNA interference) over time, the notion of a trajectory which leaves a signature in the database is elaborated. Can the detailed index terms describing the dynamics of research be used to predict the diffusion dynamics of research results? Possibilities are specified for further integration between the Medline database, on the one hand, and the Science Citation Index and Scopus (containing citation information), on the other.Comment: forthcoming in the Journal of the American Society for Information Science and Technolog

    Citation Analysis: A Comparison of Google Scholar, Scopus, and Web of Science

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    When faculty members are evaluated, they are judged in part by the impact and quality of their scholarly publications. While all academic institutions look to publication counts and venues as well as the subjective opinions of peers, many hiring, tenure, and promotion committees also rely on citation analysis to obtain a more objective assessment of an author’s work. Consequently, faculty members try to identify as many citations to their published works as possible to provide a comprehensive assessment of their publication impact on the scholarly and professional communities. The Institute for Scientific Information’s (ISI) citation databases, which are widely used as a starting point if not the only source for locating citations, have several limitations that may leave gaps in the coverage of citations to an author’s work. This paper presents a case study comparing citations found in Scopus and Google Scholar with those found in Web of Science (the portal used to search the three ISI citation databases) for items published by two Library and Information Science full-time faculty members. In addition, the paper presents a brief overview of a prototype system called CiteSearch, which analyzes combined data from multiple citation databases to produce citation-based quality evaluation measures

    Reviewing Research Trends:A Scientometric Approach Using Gunshot Residue (GSR) Literature as an Example

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    The ability to manage, distil and disseminate the significant amount of information that is available from published literature is fast becoming a core and critical skill across all research domains, including that of forensic science. In this study, a simplified scientometric approach has been applied to available literature on gunshot residue (GSR) as a test evidence type aiming to evaluate publication trends and explore the interconnectivity between authors. A total of 731 publications were retrieved using the search engine ‘Scopus’ and come from 1589 known authors, of whom 401 contributed to more than one research output on this subject. Out of the total number of publications, only 35 (4.8%) were found to be Open Access (OA). The Compound Annual Growth Rate (CAGR) for years 2006 and 2016 reveals a much higher growth in publications relating to GSR (8.0%) than the benchmark annual growth rate of 3.9%. The distribution of a broad spectrum of keywords generated from the publications confirms a historical trend, in particular regarding the use of analytical techniques, in the study of gunshot residue. The results inform how relevant information extracted from a bibliometric search can be used to explore, analyse and define new research areas

    A Multi-Level Analysis of World Scientific Output in Pharmacology

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    The purpose of this chapter is to analyse international research in “pharmacology, toxicology and pharmaceutics” (hereafter pharmacology) on the basis of the scientific papers listed in the Scopus multidisciplinary database. This primary objective is reached by answering the following questions (in the section on results). What weight does the subject area “pharmacology, toxicology and pharmaceutics” carry in world-wide science? What is the percentage contribution made by the various regions of the world to the subject area “pharmacology, toxicology and pharmaceutics”? Can certain regions be identified as leaders on that basis, as in other scientific contexts? Are emerging countries present in the field? Do the most productive countries also publish the largest number of journals? What features characterise the scientific output of companies that publish pharmacological papers

    ELeCTRA: Induced Usage Limitations Calculation in RESTful APIs

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    As software architecture design is evolving to microservice paradigms, RESTful APIs become the building blocks of applications. In such a scenario, a growing market of APIs is proliferating and developers face the challenges to take advantage of this reality. For example, third-party APIs typically define different usage limitations depending on the purchased Service Level Agreement (SLA) and, consequently, performing a manual analysis of external APIs and their impact in a microservice architecture is a complex and tedious task. In this demonstration paper, we present ELeCTRA, a tool to automate the analysis of induced usage limitations in an API, derived from its usage of external APIs. This tool takes the structural, conversational and SLA specifications of the API, generates a visual dependency graph and translates the problem into a constraint satisfaction optimization problem (CSOP) to obtain the optimal usage limitations.Ministerio de Economía y Competitividad TIN2015-70560-RJunta de Andalucía P12–TIC–1867Ministerio de Economía y Competitividad TIN2014-53986-REDTMinisterio de Educación, Cultura y Deporte FPU15/0298

    Forecasting the Spreading of Technologies in Research Communities

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    Technologies such as algorithms, applications and formats are an important part of the knowledge produced and reused in the research process. Typically, a technology is expected to originate in the context of a research area and then spread and contribute to several other fields. For example, Semantic Web technologies have been successfully adopted by a variety of fields, e.g., Information Retrieval, Human Computer Interaction, Biology, and many others. Unfortunately, the spreading of technologies across research areas may be a slow and inefficient process, since it is easy for researchers to be unaware of potentially relevant solutions produced by other research communities. In this paper, we hypothesise that it is possible to learn typical technology propagation patterns from historical data and to exploit this knowledge i) to anticipate where a technology may be adopted next and ii) to alert relevant stakeholders about emerging and relevant technologies in other fields. To do so, we propose the Technology-Topic Framework, a novel approach which uses a semantically enhanced technology-topic model to forecast the propagation of technologies to research areas. A formal evaluation of the approach on a set of technologies in the Semantic Web and Artificial Intelligence areas has produced excellent results, confirming the validity of our solution
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