Since content audiences, including libraries and information centres, are increasingly geared to digital environments and virtual networks, the production and delivery of high-quality digital content are becoming continuously important. So far, several components have been introduced by researchers for evaluating the quality of digital content generation. However, due to the uncertainty of the importance rate and value of each of these components, it has not yet been possible to use them effectively to evaluate the content produced. This study aimed to rank the components of content generation to allow accurate evaluation of them for users as well as content providers and distributors including libraries and marketers. The ranked content can motivate digital content producers and distributors to better evaluate the quality of digital content, better attract customers and make more effective decisions about the quality of digital content use based on their specific goals. Initially, 42 of the most important components were identified from the literature. Then, the next steps were taken to rank these components, and based on three rounds of Delphi interviews, the experts’ views on the importance rate of each of the components were obtained, analysed and ranked. Since in this ranking, the importance of a wide range of components should be highlighted towards each other, the fuzzy TOPSIS technique was emphasised for analysing the views of 16 experts in the field of content generation in Iran. This ranking indicated that components such as ‘findable and access’, ‘non-disturbing and helpful’, ‘clear’ and ‘remarkable’ are the main pillars of content generation and are of the utmost importance. The results can be used as an effective tool to improve the quality of content. Moreover, it increases audience engagement in digital environments and social networks, and encourages them to make more use of the digital content of libraries.

Background: Sharing research outputs with open science methods for different stakeholders causes better access to different studies to solve problems in diverse fields, which leads to equal access conditions to research resources, as well as greater scientific productivity. Therefore, the aim of this study was to perceive the concept of openness in research among Iranian health researchers.Methods: From the beginning of August to the middle of November 2021, twenty semi-structured interviews were held with Iranian health researchers from different fields using purposeful, snowball, and convenience sampling. The interviews continued until data saturation. Data analysis was performed with thematic analysis using MAXQDA 20. Finally, seven main issues related to open science were identified.Results: Through analysis of the interviews, 235 primary codes and 173 main codes were extracted in 22 subclasses. After careful evaluation and integration of subclasses and classes, they were finally classified into nine categories and three main themes. Analysis showed that openness in research was related to three main themes: researchers’ understanding of open science, the impact of open science on publication and sharing of research, concerns and reluctance to open research.Conclusion: The conditions of access to research output should be specified given the diversity of studies conducted in the field of health; issues like privacy as an important topic of access to data and information in the health system should also be specified. Our analysis indicated that the conditions of publication and sharing of research processes should be stated according to different scopes of health fields. The concept of open science was related to access to findings and other research items regardless of cost, political, social, or racial barriers, which could create collective wisdom in the development of knowledge. The process of publication and sharing of research related to open access applies to all types of outputs, conditions of access, increasing trust in research, creation of diverse publication paths, and broader participation of citizens in research. Open science practices should be promoted to increase the circulation and exploitation rates of knowledge while adjusting and respecting the limits of privacy, intellectual property and national security rights of countries.

The aim of this study was to conduct a comprehensive literature review of the dimensions of open science in research processes. A total of four databases and snowball searching were used for the comprehensive literature review during 2011–2020; then, we were able to find 98 studies based on the inclusion criteria. Also, we used thematic method to review the relevant studies and identified three categories of dimensions in the research process, namely (1) the publication and sharing category including open access, open data, transparency and reproducibility, citizen science, and crowd sourcing; (2) the infrastructure and cultural category including open infrastructure, open education, open tools, budget mechanism, open culture, and communication; and (3) governance and evaluation including policies, governance, and the ethical principles associated with open science. Open science emphasizes the efforts to open and make the scientific research process more inclusive so as to engage the inside and outside actors in the research process.

Introduction: The development and use of digital tools in various stages of research highlight the importance of novel open science methods for an integrated and accessible research system. The objective of this study was to design and validate a conceptual model of open science on healthcare research processes. Methods: This research was conducted in three phases using a mixed-methods approach. The first phase employed a qualitative method, namely purposive sampling and semi-structured interview guides to collect data from healthcare researchers and managers. Influential factors of open science on research processes were extracted for refining the components and developing the proposed model; the second phase utilized a panel of experts and collective agreement through purposive sampling. The final phase involved purposive sampling and Delphi technique to validate the components of the proposed model according to researchers’ perspectives. Findings: From the thematic analysis of 20 interview on the study topic, 385 codes, 38 sub-themes, and 14 main themes were extracted for the initial proposed model. These components were reviewed by expert panel members, resulting in 31 sub-themes, 13 main themes, and 4 approved themes. Ultimately, the agreed-upon model was assessed in four layers for validation by the expert panel, and all the components achieved a score of > 75% in two Delphi rounds. The validated model was presented based on the infrastructure and culture layers, as well as supervision, assessment, publication, and sharing. Conclusion: To effectively implement these methods in the research process, it is essential to create cultural and infrastructural backgrounds and predefined requirements for preventing potential abuses and privacy concerns in the healthcare system. Applying these principles will lead to greater access to outputs, increasing the credibility of research results and the utilization of collective intelligence in solving healthcare system issues.