Department of Library, Information and Archives Management, School of Economics and Management

University of Chinese Academy of Sciences

Covid-related Papers Contribute 50% on the JIF of High Impact Medicine Journals

How does the Research Capacity Gap among Institutions Change over Time?

<abstract xmlns="http://www.w3.org/1999/xhtml">

<sec><h3>Purpose</h3>
<p>We aim to extend our investigations related to the Relative Intensity of Collaboration (RIC) indicator, by constructing a confidence interval for the obtained values.</p>
</sec>
<sec><h3>Design/methodology/approach</h3>
<p>We use Mantel-Haenszel statistics as applied recently by Smolinsky, Klingenberg, and Marx.</p>
</sec>
<sec><h3>Findings</h3>
<p>We obtain confidence intervals for the RIC indicator</p>
</sec>
<sec><h3>Research limitations</h3>
<p>It is not obvious that data obtained from the Web of Science (or any other database) can be considered a random sample.</p>
</sec>
<sec><h3>Practical implications</h3>
<p>We explain how to calculate confidence intervals. Bibliometric indicators are more often than not presented as precise values instead of an approximation depending on the database and the time of measurement. Our approach presents a suggestion to solve this problem.</p>
</sec>
<sec><h3>Originality/value</h3>
<p>Our approach combines the statistics of binary categorical data and bibliometric studies of collaboration.</p>
</sec>
</abstract>

Confidence Intervals for Relative Intensity of Collaboration (RIC) Indicators

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<p>This paper reviews literature pertaining to the development of data science as a discipline, current issues with data bias and ethics, and the role that the discipline of information science may play in addressing these concerns. Information science research and researchers have much to offer for data science, owing to their background as transdisciplinary scholars who apply human-centered and social-behavioral perspectives to issues within natural science disciplines. Information science researchers have already contributed to a humanistic approach to data ethics within the literature and an emphasis on data science within information schools all but ensures that this literature will continue to grow in coming decades. This review article serves as a reference for the history, current progress, and potential future directions of data ethics research within the corpus of information science literature.</p>
</abstract>

What Does Information Science Offer for Data Science Research?: A Review of Data and Information Ethics Literature

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<sec><h3>Purpose</h3>
<p>The 5th Plenary Session of the 19th Communist Party of China (CPC) Central Committee clearly states that developing science and technology through self-reliance and self-strengthening provides the strategic underpinning for China's development. Based on this background, this paper explores a metric model for assessing national scientific research strength through collaboration on research papers.</p>
</sec>
<sec><h3>Design/methodology/approach</h3>
<p>We propose a novel metric model for assessing national scientific research strength, which sets two indicators, national scientific self-reliance (<italic>SR</italic>) and national academic contribution (<italic>CT</italic>), to reflect “self-reliance” and “self-strengthening” respectively. Taking the research papers in quantum technology as an example, this study analyzes the scientific research strength of various countries around the world, especially China in quantum technology.</p>
</sec>
<sec><h3>Findings</h3>
<p>The results show that the research of quantum technology in China has always been relatively independent with fewer international collaboration papers and located in a more marginal position in cooperation networks. China's academic contribution (<italic>CT</italic>) to global quantum technology research is increasing and has been greater than that of the United States in 2020. Combining the two indicators, <italic>CT</italic> and <italic>SR</italic>, China's research strength in the quantum field closely follows the United States, and the United States is the most powerful with high research autonomy.</p>
</sec>
<sec><h3>Research limitations</h3>
<p>This paper only reflects China's scientific research strength in quantum technology from collaboration on research papers and doesn’t consider the segmentation of quantum technology and the industrial upstream and downstream aspects, which need further study.</p>
</sec>
<sec><h3>Practical implications</h3>
<p>The model is helpful to better understand the national scientific research strength in a certain field from “self-reliance” and “self-strengthening”.</p>
</sec>
<sec><h3>Originality/value</h3>
<p>We propose a novel metric model to measure the national scientific research strength from the perspective of “self-reliance” and “self-strengthening”, which provides a solid basis for the assessment of the strength level of scientific research in countries/regions and institutions.</p>
</sec>
</abstract>

A Novel Metric for Assessing National Strength in Scientific Research: Understanding China's Research Output in Quantum Technology through Collaboration

<abstract xmlns="http://www.w3.org/1999/xhtml">

<sec><h3>Purpose</h3><p>The aim of our paper is to investigate the role of a mentor leading a research team in the overall scientific performance of an academic institution and the possible risks of their departure with a special attention to their publication output.</p></sec>
<sec><h3>Design/methodology/approach</h3><p>By using SciVal subject area data, we composed a formula describing the level of vulnerability of any given university in the case of losing any of its leading mentors, identifying other risk factors by dividing their careers into separate stages.</p></sec>
<sec><h3>Findings</h3><p>It turns out that the higher field-weighed citation impact is, the better position universities reach in the rankings by subject and the vulnerability of institutions highly depends on the mentors, especially in view of their contribution to the topic clusters.</p></sec>
<sec><h3>Research limitations</h3><p>The analysis covers the publication output of leading researchers working at four Hungarian universities, the scope of the analysis is worth being extended.</p></sec>
<sec><h3>Practical implications</h3><p>Our analysis has the potential to give an applicable systemic approach as well as a data collection scheme to university managements so as to formulate an inclusive and comprehensive research strategy involving the introduction of a reward system aimed at publications and further encouraging national and international research cooperation.</p></sec>
<sec><h3>Originality/value</h3><p>The methodology and the principles of risk assessment laid down in our paper are not restricted to measuring the vulnerability level of a limited group of academic institutions, they can be appropriately used for investigating the role of mentors or leading researchers at every university across the globe.</p></sec>
</abstract>

Public Governance and International Studies

Subject Area Risk Assessment of Four Hungarian Universities with a View to the QS University Rankings by Subject

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Journal of Data and Information Science

Journal of Data and Information Science (JDIS, formerly Chinese Journal of Library and Information Science), sponsored by the Chinese Academy of Sciences (CAS) and published quarterly by the National Science Library of CAS, is the first internationally published English-language academic journal in Library and Information Science and related fields from China.  The Journal of Data and Information Science (JDIS) focuses on data-based research oriented toward the exploration of scientific research and innovation. The main areas of interest are science of science, evidence-based policymaking, research evaluation, computational social science, and scientometrics/bibliometrics/altmetrics/ informetrics. Emphasis is given to research that focuses on data, analytics, and knowledge discovery, and supports decision making and science policy. This includes modeling, innovation, data security, media and communications, and social development. Topics may include studies of metadata or full content data, text or non-textural data, structured or non-structural data, domain-specific or cross-domain data, and dynamic or interactive data.  Specific topic areas may include (but are not limited to):    Knowledge organization  Knowledge discovery and data mining  Knowledge integration and fusion  Semantic Web  Science of science  Bibliometrics and scientometrics  Analytic and diagnostic informetrics  Competitive intelligence  Predictive analysis  Social network analysis and metrics  Semantic and interactively analytic retrieval  Evidence-based policy analysis  Intelligent knowledge production  Knowledge-driven workflow management and decision-making  Knowledge-driven collaboration and its management  Domain knowledge infrastructure with knowledge fusion and analytics  Training for data &amp; information scientists  Development of data and information services    JDIS publishes theoretical and empirical work. Systematic reviews are welcome and applied research in development of advanced methods, services, and best practices is also an important part. But simple application of established informetrics on a specific research field or country is out of the scope.Welcome to submit your papers to JDIS.  Why subscribe and read  JDIS is the first and only English journal from China in Library and Information Science and related fields. With an aim to disseminate the cutting-edge research in these fields, it is devoted to the study and application of the theories, methods, techniques, services, and infrastructural facilities using big data to support knowledge discovery for decision and policy making. The basic emphasis is big data-based, analytics centered, knowledge discovery driven, and decision making supporting. JDIS has gathered a big body of high profile experts across the world who contribute their research to the journal. The international authors account for around 62% in its first publication year (2016).  Why submit  JDIS is the first and only English journal from China in Library and Information Science and related fields. It owns a number of world front-line scholars as editorial board members or reviewers. The turnaround time on average for a manuscript from submission to final decision is less than two and a half months.  Archiving  Sciendo archives the contents of this journal in Portico- digital long-term preservation service of scholarly books, journals and collections.  Plagiarism Policy  The editorial board is participating in a growing community of Similarity Check System's users in order to ensure that the content published is original and trustworthy. Similarity Check is a medium that allows for comprehensive manuscripts screening, aimed to eliminate plagiarism and provide a high standard and quality peer-review process. 

Journal of Data and Information Science

Volume 7 (2022): Issue 4 (November 2022)

Research Note

Covid-related Papers Contribute 50% on the JIF of High Impact Medicine Journals

How does the Research Capacity Gap among Institutions Change over Time?

Letter

Confidence Intervals for Relative Intensity of Collaboration (RIC) Indicators

Review

What Does Information Science Offer for Data Science Research?: A Review of Data and Information Ethics Literature

Research Paper

A Novel Metric for Assessing National Strength in Scientific Research: Understanding China's Research Output in Quantum Technology through Collaboration

Subject Area Risk Assessment of Four Hungarian Universities with a View to the QS University Rankings by Subject

Chercher

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