Mapping Patent Classifications: Portfolio and Statistical Analysis, and the Comparison of Strengths and Weaknesses

The Cooperative Patent Classifications (CPC) jointly developed by the European and US Patent Offices provide a new basis for mapping and portfolio analysis. This update provides an occasion for rethinking the parameter choices. The new maps are significantly different from previous ones, although this may not always be obvious on visual inspection. Since these maps are statistical constructs based on index terms, their quality--as different from utility--can only be controlled discursively. We provide nested maps online and a routine for portfolio overlays and further statistical analysis. We add a new tool for "difference maps" which is illustrated by comparing the portfolios of patents granted to Novartis and MSD in 2016.Comment: Scientometrics 112(3) (2017) 1573-1591; http://link.springer.com/article/10.1007/s11192-017-2449-

Publications on Germanistics in the Scopus Database: A Science Mapping Study

It is aimed to reveal the current state in the field of Germanistics on a global scale in this study. In this direction, the Scopus database was searched for the publications in the field of Germanistics, and the publications related to the relevant literature between the years 2018-2022 were examined with bibliometric analysis. The vast majority of the publications included in the scope of the study are in the article type, and their language is mostly English. The data obtained were visualized with science mapping, which is one of the bibliometric analysis techniques. The VOSviewer program was employed for this. Among the science maps created using this program, there are network maps of the most productive country, keyword co-occurrence analysis, bibliographic coupling analyses of institutions and countries, author and reference co-citation analyses, and co-authorship analysis of countries. The maps were presented in the study’s findings section, and the bibliometric information and relationships in each of these maps were assessed separately

Digital economy – a bibliometric addition to understanding an “undefined” domain of the economy

Purpose: The definition of the digital economy changes depending on the time period the definition comes from and the prevailing technology of that period, from the Internet to advanced robotics or artificial intelligence. The purpose of this paper is to identify the core terms, give a definition of the digital economy, identify the most influential journals, authors and documents that deal with the topic and provide an overview of the development of academic literature over the years. Methodology: 293 documents related to the term “digital economy” were retrieved from the Scopus database. By using citation, co-citation, bibliographic coupling analysis and co-occurrence of the keywords, this paper identifies a list of the most influential journals, authors and documents in the field of digital economy. The analysis was conducted by using the VOSviewer tool. An in-depth analysis of the documents was used to prepare an overview of the definitions of the digital economy. Results: The research proves inconsistency of the definition and context of the digital economy as well as a significant impact of a small number of authors and journals in the area under study. Keyword analysis shows that the term digital economy is related not to macroeconomic terms but to more specific industrial terms. Conclusion: Guidelines are provided for future scientific research to fill the gaps in the definition and scope of the digital economy

The Impact of Research Data Sharing and Reuse on Data Citation in STEM Fields

Despite the open science movement and mandates for the sharing of research data by major funding agencies and influential journals, the citation of data sharing and reuse has not become standard practice in the various science, technology, engineering and mathematics (STEM) fields. Advances in technology have lowered some barriers to data sharing, but it is a socio-technical phenomenon and the impact of the ongoing evolution in scholarly communication practices has yet to be quantified. Furthermore, there is need for a deeper and more nuanced understanding of author self-citation and recitation, the most often cited types of data, disciplinary differences regarding data citation and the extent of interdisciplinarity in data citation. This study employed a mixed methods approach that combined coding with semi-automatic text-searching techniques in order to assess the impact of data sharing and reuse on data citation in STEM fields. The research considered over 500,000 open research data entities, such as datasets, software and data studies, from over 350 repositories worldwide. I also examined 705 bibliographic publications with a total of 15,261 instances of data sharing, reuse, and citation the data, article, discipline and interdisciplinary levels. More specifically, I measured the phenomenon of data sharing in terms of formal data citation, frequently cited data types, and author self-citation, and I explored recitation at the levels of both data- and bibliography-level, and data reuse practices in bibliographies, associations of disciplines, and interdisciplinary contexts. The results of this research revealed, to begin with, disciplinary differences with regard to the impact of data sharing and reuse on data citation in STEM fields. This research also yielded the following additional findings regarding the citation of data by STEM researchers; 1) data sharing practices were diverse across disciplines: 2) data sharing has been increasing in recent years; 3) each discipline made use of major digital repositories; 4) these repositories took various forms depending on the discipline; 5) certain data types were more often cited in each discipline, so that the frequency distribution of the data types was highly skewed; 6) author self-citation and recitation followed similar trends at the data and bibliographic levels, but specific practices varied within each discipline; 7) associations between and across data and author self-citation and recitation at the bibliographic level were observed, with the self-citation rate differing significantly among disciplines;8) data reuse in bibliographies was rare yet diverse; 9) informal citation of data sharing and reuse at the bibliographic level was more common in certain fields, with astronomy/physics showing the highest amount (98%) and technology the lowest (69%); 10) within bibliographic publications, the documentation of data sharing and reuse occurred mainly in the main text; 11) publications in certain disciplines, such as chemistry, computing and engineering, did not attract citations from more than one field (i.e., showed no diversity); and, on the other hand,12) publications in other fields attracted a wide range of interdisciplinary data citations. This dissertation, then, contributes to the understanding of two key areas aspects of the current citation systems. First, the findings have practical implications for individual researchers, decision makers, funding agencies and publishers with regard to giving due credits to those who share their data. Second, this research has methodological implications in terms of reducing the labor required to analyze the full text of associated articles in order to identify evidence of data citation

A Journal-Driven Bibliography of Digital Humanities

Digital Humanities Quarterly (DHQ) seeks Level II funding to develop a bibliographic resource through which the journal can create, manage, export, and publish high-quality bibliographic data from DHQ articles and their citations, as well as from the broader digital humanities research domain. Drawing on data from this resource, we will develop visualizations through which readers can explore citation networks and find related articles. We will also publish the full bibliography as a public web-based service that reflects the profile of current digital humanities research. The bibliography will be maintained and expanded through incoming DHQ articles and citations, and through contributions from the DH community. DHQ is an open-access online journal published by the Alliance of Digital Humanities Organizations (ADHO), hosted at Brown University and Indiana University, and serves as a crucial point of encounter between digital humanities research and the wider humanities community

A global–local approach to the high-fidelity impact analysis of composite structures based on node-dependent kinematics

The objective of the present work is to investigate progressive damage in fibre-reinforced composites under varying load conditions, and in particular transverse impact loads, using a global–local approach. The numerical models are built using higher-order structural theories based on the Carrera Unified Formulation (CUF). The Node-Dependent Kinematics (NDK) technique, an intrinsic feature of CUF models, is employed which enables the selective refinement of critical regions of interest within the structure and results in a global–local analysis. Progressive damage is governed by the CODAM2 material model, which is based on continuum damage mechanics. A series of numerical assessments are performed on composite laminates under varying load conditions, and predicted results of the global–local analysis are found to be in good agreement with experimental data, thereby validating the proposed approach. A comparison of its performance with reference high-fidelity CUF models of the full structure demonstrates the computational efficiency that can be achieved using the CUF-NDK global–local approach

Structural studies on Functional Materials using Solid-State NMR, Powder X-ray Diffraction and DFT Calculations

Analytical and theoretical techniques were used in this work for structural studies of framework materials. One and two dimensional 31P and 17O solid state NMR experiments highlight subtle thermally induced structural changes in (MoO2)2P2O7 pyrophosphate, tungsten trioxide WO3 and negative thermal expansion ZrW2O8. DFT methods using CASTEP software to calculate 31P and 17O NMR parameters are performed on these structures and discussed in comparison to experimental results, published structures and thermal mechanisms

A new electron diffraction approach for structure refinement applied to Ca3Mn2O7

The digital large-angle convergent-beam electron diffraction (D-LACBED) technique is applied to Ca3Mn2O7 for a range of temperatures. Bloch-wave simulations are used to examine the effects that changes in different parameters have on the intensity in D-LACBED patterns, and atomic coordinates, thermal atomic displacement parameters and apparent occupancy are refined to achieve a good fit between simulation and experiment. The sensitivity of the technique to subtle changes in structure is demonstrated. Refined structures are in good agreement with previous determinations of Ca3Mn2O7 and show the decay of anti-phase oxygen octahedral tilts perpendicular to the c axis of the A21am unit cell with increasing temperature, as well as the robustness of oxygen octahedral tilts about the c axis up to ∼400°C. The technique samples only the zero-order Laue zone and is therefore insensitive to atom displacements along the electron-beam direction. For this reason it is not possible to distinguish between in-phase and anti-phase oxygen octahedral tilting about the c axis using the [110] data collected in this study