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This paper aims to provide a process-driven scientific data quality (DQ) monitoring framework by information product map (IP-Map) in identifying the root causes of poor DQ issues so as to assure the quality of scientific data.

First, a general scientific data life cycle model is constructed based on eight classical models and 37 researchers’ experience. Then, the IP-Map is constructed to visualize the scientific data manufacturing process. After that, the potential deficiencies that may arise and DQ issues are examined from the aspects of process and data stakeholders. Finally, the corresponding strategies for improving scientific DQ are put forward.

The scientific data manufacturing process and data stakeholders’ responsibilities could be clearly visualized by the IP-Map. The proposed process-driven framework is helpful in clarifying the root causes of DQ vulnerabilities in scientific data.

As for the implications for researchers, the process-driven framework proposed in this paper provides a better understanding of scientific DQ issues during implementing a research project as well as providing a useful method to analyse those DQ issues based on IP-Map approach from the aspects of process and data stakeholders.

The process-driven framework is beneficial for the research institutions, scientific data management centres and researchers to better manage the scientific data manufacturing process and solve the scientific DQ issues.

This research proposes a general scientific data life cycle model and further provides a process-driven scientific DQ monitoring framework for identifying the root causes of poor data issues from the aspects of process and stakeholders which have been ignored by existing information technology-driven solutions. This study is likely to lead to an improved approach to assuring the scientific DQ and is applicable in different research fields.

Accurate information is the basis for well-informed decision-making, which is particularly challenging in the dynamic reality of a pandemic. Search engines are a major gateway for obtaining information, yet little is known about the quality and scientific accuracy of information answering conspiracy-related queries about COVID-19, especially outside of English-speaking countries and languages.

The authors conducted an algorithmic audit of Google Search, emulating search queries about COVID-19 conspiracy theories in 10 different locations and four languages (English, Arabic, Russian, and Hebrew) and used content analysis by native language speakers to examine the quality of the available information.

Searching the same conspiracies in different languages led to fundamentally different results. English had the largest share of 52% high-quality scientific information. The average quality score of the English-language results was significantly higher than in Russian and Arabic. Non-English languages had a considerably higher percentage of conspiracy-supporting content. In Russian, nearly 40% of the results supported conspiracies compared to 18% in English.

This study’s findings highlight structural differences that significantly limit access to high-quality, balanced, and accurate information about the pandemic, despite its existence on the Internet in another language. Addressing these gaps has the potential to improve individual decision-making collective outcomes for non-English societies.

Given the magnitude of the literature, a researcher must be selective of research papers and publications in general. In other words, only papers that meet strict standards of academic integrity and adhere to reliable and credible sources should be referenced. The purpose of this paper is to approach this issue from the prism of scientometrics according to the following research questions: Is it necessary to judge the quality of scientific production? How do we evaluate scientific production? What are the tools to be used in evaluation?

This paper presents a comparative study of scientometric evaluation practices and tools. A systematic literature review is conducted based on articles published in the field of scientometrics between 1951 and 2022. To analyze data, the authors performed three different aspects of analysis: usage analysis based on classification and comparison between the different scientific evaluation practices, type and level analysis based on classifying different scientometric indicators according to their types and application levels and similarity analysis based on studying the correlation between different quantitative metrics to identify similarity between them.

This comparative study leads to classify different scientific evaluation practices into externalist and internalist approaches. The authors categorized the different quantitative metrics according to their types (impact, production and composite indicators), their levels of application (micro, meso and macro) and their use (internalist and externalist). Moreover, the similarity analysis has revealed a high correlation between several scientometric indicators such as author h-index, author publications, citations and journal citations.

The interest in this study lies deeply in identifying the strengths and weaknesses of research groups and guides their actions. This evaluation contributes to the advancement of scientific research and to the motivation of researchers. Moreover, this paper can be applied as a complete in-depth guide to help new researchers select appropriate measurements to evaluate scientific production. The selection of evaluation measures is made according to their types, usage and levels of application. Furthermore, our analysis shows the similarity between the different indicators which can limit the overuse of similar measures.

This study aims to reveal the factors that drive researchers to share data and to provide reference for promoting open scientific data.

Based on the theory of social capital and the theory of planned behaviour, hypotheses were proposed and the model was developed. The authors acquired 479 valid samples of Chinese researchers through questionnaires and conducted an empirical analysis via AMOS 23.0.

Attitudes towards data sharing are significantly and positively correlated with trust, reciprocity and social interaction, but not with a shared vision; willingness to share data is significantly and positively correlated with attitudes and perceived behavioural control, but not with subjective norms; furthermore, data quality, which performed the function of a moderating variable, was found to play a facilitating role in the above correlations. Based on the findings, suggestions for relevant entities were specified.

The study developed and validated an integrated theoretical framework, clarified the mechanism by which social capital and planned behaviour affect willingness to share data, hoping to provide reference and empirical support for subsequent studies as well as new ideas for data management and sharing.

This paper seeks to show the limitations of citation analysis to measure the quality of scientific contributions, also exploring the consequences of the assessment of research performance for educational institutions.

The study reviews the literature about citation and assessment of the research endeavour to identify problems that clearly affect the administration of the institutions of higher education

Citation and other metrics are being used increasingly by the educational administration. Citation indexes can be considered as useful indicators, but they do not represent the quality of research. For this reason, bibliometric measurement cannot be the essential part of academic appraisal.

The paper highlights the fact that administrators in higher education institutions and academic authorities need to be conscious of the essential role of peer review.

The purpose of this paper is to explore and explicate documentation ideals parallel to information policy, and by means of this analysis demonstrate how the concept “documentation ideals” is an analytical tool for engaging with political and institutional contexts of information practices.

The paper is based on a case study of documentation ideals in a debate about quality in archaeological documentation. The methodology draws on idea analysis, and on the science and technology studies’ controversy studies approach.

The paper explicates three documentation ideals, how these ideals allocate responsibility for documentation to different actors, how the ideals assign roles to practitioners, and how the ideals point to different beneficiaries of the documentation. Furthermore, the analysis highlights ideas about two different means to reach the documentation ideals.

The case’s debate reflects opinions of Northern European professionals.

The paper illuminates how documentation ideals tweak and even contest formal information policy in claims on the documentation and on the practitioners doing documentation.

Documentation ideal analysis is crucial as a complement to formal information policy analysis and to analysis guided by practice theory in attempts to understand the contexts of information practices and documentation, insights central for developing information literacies.

This paper aims to propose a new qualitative indicator for the evaluation of the productions of researchers in any discipline.

Based on the study of existing quantitative indicators, the authors’ approach consisted of the hybridization of two indicators. This hybridization is based on the individual H_index (Hi_index) and H_index contemporary (Hc_index) weighted by qualitative factors. The initial sources of the data are online bibliographic databases, such as Google Scholar and Publish or Perish.

A new scientometric indicator was used to compare the scientific production quality of researchers and their classification (as part of a research community) as the classification of national and international research institutions. The authors have applied a new indicator to compare and classify the members of their laboratory, RIADI, according to their quality of scientific production.

The indicator is an improvement of the H_index. It is a measure that can have an impact on society (influencing research attitudes, affecting quality of research). By this contribution, the authors measure more than one aspect by involving all the external factors that can affect the quality of research.

This paper fulfils a gap in the literature concerning the absence of a qualitative indicator among the set of existing quantitative measures. Additionally, this paper addresses the limitations of the existing qualitative practices, such as peer review and citation analysis. In the new qualitative indicator, the authors involve all of these qualitative aspects: the influence of the age of the paper, the number of co-authors, the order of the co-authors, the impact factor of journals and the conference rankings.

Over the past few decades, university reforms in line with management and enterprise ideals have been well documented. Changes in the ideals underlying the missions of universities have led to changes in their modes of governing and organizing, which in turn drive further transformation of their missions. One set of reforms in Swedish higher education has been the dissolution of collegial bodies and procedures. At the same time, in recent years, we have witnessed an increased interest in collegiality and a reintroduction of collegial bodies and procedures. New translations of collegiality appear not only in how universities are organized, but also in other core aspects of research and higher education. We review examples of peer reviewing, research assessment, and direct recruitment of professors and ask: Can these new translations of collegiality be understood as a revitalization of collegiality, or is it – to draw a parallel with greenwashing – rather a matter of collegiality-washing?

The online Question and Answer community is full of a large number of science and technology topics, the discussion and dissemination of which play an important role in promoting the popularization of new technologies and cultivating public enthusiasm for science. However, the spread of false information and rumors weakens the community's positive effect, making the community more difficult for people to obtain useful information on such topics. Research on the influencing factors and governance of the spread of false information on science and technology topics has become the key to the spread of popular science.

Therefore, this paper uses the Elaboration Likelihood Model as the theoretical framework to examine the role of the factors influencing the spread of false information on science and technology topics in Zhihu community on the information persuasion and the impact on public behavior attitude from the core path and the edge path. This paper compiles a crawler program to capture 12,893 response information under the “Metaverse” topic in Zhihu community as an empirical sample and uses text mining and conducts visual correlation analysis to explore the key factors affecting the persuasive transmission path of information on science and technology topics.

The research finds that the content specialization, content consistency and content coherence of science and technology topics affect personal judgment from the aspect of information content through the core path and have a positive correlation with information persuasion; the number of comments, the length of the text and the publishing authors' influence from the edge image characteristics through the edge path are positively correlated with the information persuasion. Then, from the perspective of topic platform, government and topic participants, this paper puts forward a general plan to improve the information persuasion of science and technology topics so as to deal with false information.

Compared with the small data set of the traditional questionnaire survey, the research based on community empirical big data is more reliable. The model takes into account the attitude and behavior of users and is more suitable for the research on the transmission path of scientific and technological information in the internet era. This research provides a direction for analyzing the text characteristics and development trends of information in the field of science and technology and is conducive to promoting the optimization of the network information environment and building a good ecology, with the spread of rumors about science and technology topics curbed and the governance of false information strengthened.

The aim of the paper is to evidence the development of scientific management through the lens of postmodernism.

The four principles of scientific management are deconstructed through a postmodern lens. Current management practices are analyzed for indicators of development in scientific management.

The principles of scientific management are found within current management examples; measurement of knowledge production; empowerment; total quality management; teamwork. Scientific management, when deconstructed through the lens of postmodernism, is discovered to have developed over time.

The limitation to this study is a precise definition for postmodernism and postmodern management against which to “prove” any findings. The implication is to extend research on the development of scientific management in postmodern management.

A practical implication for management practitioners is to apply a tenet of postmodernism to management i.e. there are a myriad of managerial approaches that work.

The paper's contribution is that the principles of scientific management originated in modern times and are developed in postmodern management.