The main object of this study is analyzing the components and indicators of the scholarly Publication System in the scholarly Publication databases in terms of access, communication, control, infrastructure, language, materials (information resources), support, technology, economics, evaluation, education, ethics and their characteristics. The research community has been identified by content analyzing and 73 databases were extracted, based on the frequency and approval of experts the sample limited to 12 scholarly publication databases. These include the ArXiv, DOAJ, Elsevier, Springer, Google Scholar, PubMed, Nature, Web of Science, Scopus, National Institutes of Health (NIH), SPARC (Scholarly Publishing and Academic Resource Coalition), and Amazon databases. The checklist designed to study these databases is taken from the scholarly Publication System dimensions. Research findings show that all components have been considered in publication databases and the difference between them returned in scholarly Publication indicators. however, according to the type, age and general policy of the databases, some indicators of components, Like education, economics, and information resources has not received enough attention, in all databases, some components such as technology, support and control and their indicators have an equal importance.

The Challenges of Implementing a National Scholarly Publication System in IranBackground and Objectives: In order to achieve a stronger position in international scientific communities, it is necessary to strengthen the country's science publishing ecosystem by tackling pathology and removing barriers. In this research, we have explored the complex challenges facing the Iranian scientific publishing ecosystem in order to find out which obstacles are preventing an effective implementation of a robust scholarly publication system.Methodology: This research employed a qualitative methodology, utilizing content analysis to delve into the experiences and perspectives of Iranian scientific publishing experts. The primary data collection tool was a semi-structured interview, designed to elicit rich and nuanced insights from participants. A purposive sample of 19 specialists, actively engaged in scientific or executive roles within scientific centers, was selected for the study. To facilitate data analysis, the researchers utilized MaxQDA software. Within this platform, answers to each interview question were meticulously coded as open codes, allowing for the identification of patterns, themes, and recurring ideas across participant responses. Findings: the obstacles to the scientific publishing ecosystem were examined in 4 dimensions, which include the disadvantages of the lack of an integrated system in the direction of scientific publishing, possible issues in the implementation of the scientific publishing system in Iran, Lack of determination of responsibility and management in the scientific publishing system. The lack of identification of the core players in the planning and decision-making of scientific publishing.Discussion: The problems of the scientific publishing ecosystem of Iran are generally divided into current problems and future problems of the scientific publishing. The findings of this research in the field of current problems include the lack of integration of science publishing systems, the lack of foresight and forecasting for future crises, the lack of a defined institution for the management of scientific publishing; And in the section of future problems include the non-comprehensive laws or outdated regulations and the lack of laws that are suitable for an integrated system of scientific publication, the exclusive rules given to some organizations according to the statutes or regulations, the lack of concern and priority of the future of scientific publication for policy makers and the scientific community, independence and reluctance of scientific centers to participate in the integrated system of scholarly publications.

This article aimed to review the present crisis and problems in academic and special libraries vedarding the scholarly journals due to the increase in the subscription fees of such journals. It also investigated the history of the publication of free scientific journals called "Open Access (OA) Journals and discussem 4 current patterns of meeting the funds needed for their publication. The aim of OA journals which are generally published electronically is to provide free access to scientific articles for all users. In the traditional model the publication cost of a journal was provided through subscription fee while OA journals try to meal the costs through ways other than subscription fees. What follow are some ways such journals use to meet the budget needed for their publication: requesting authors to pay for publication of their articles (author-pays model), advertisement and organizational supports. Although there are some doubts about the success of this model in long term, the increasing number of such journals is an indication of the fact that OA journals and traditional journals may be able to exist side by side and move into the future.

This study sought to investigate how doctoral candidates are positioned by journal editors and reviewers and how they establish their own position while attempting to get published, as well as the challenges and opportunities they confront throughout this process. Data were gathered from two doctoral candidates at a public university employing a mixed-methods conversion design whose qualitative phase was a multiple case study. In-depth interviews, metalinguistic commentary, and document analysis were used to track the positioning patterns. Data analysis utilizing the Appraisal model revealed that doctoral candidates were perceived as novice researchers by journal editors and reviewers. In addition, doctoral candidates’ own positioning gradually shifted from being novice and intolerant researchers to being independent and tolerant ones. Moreover, the findings revealed that doctoral candidates face different challenges during the process of writing for publication, which makes this process more difficult for them. Based on the interviews, different requirements from different journals, obligations, limited sources of help, and lack of experience were among the most important challenges the participants had to deal with. On the other hand, they mentioned that publication provided them with the chance of expressing themselves and having their own voice, which could be considered as an opportunity in this process.

Purpose: Science and technology are the most critical infrastructures for the country's progress and essential tools for competition in various fields. Evaluation is at the core of all scientific efforts, which has become increasingly important with the proliferation of scientific publications. Evaluation is not a simple and transparent process; it is considered a delicate activity. The presence of multiple evaluation indicators to assess the value of scientific outputs in texts, databases, and scientific centers or publications has prompted a study of these three sources (texts, scientific networks, and experts) to establish integrated criteria for evaluating outputs in the scholarly publication ecosystem. Some scientific outputs, such as lectures, workshops, and scientific meetings, are often overlooked due to the absence of an integrated framework in the scholarly publication ecosystem. Additionally, only a few specific quantitative aspects, such as the impact factor, the number of citations, or the number of uses, are typically considered in the evaluation of scientific works. Moreover, evaluations are usually confined to a short timeframe. Identifying and categorizing these indicators within a framework can positively impact addressing these issues and establishing a continuous evaluation process for both pre and post-publication of scientific works. Therefore, the current research aims to identify comprehensive evaluation criteria in the scholarly publication ecosystem by taking into account texts, scholarly publication networks, and the perspectives of scientific publication experts.Methodology: Results from all three methods indicate that there are three key indicators and nine sub-indicators crucial for evaluating research outcomes within the Scientific Publishing System. These indicators are predominantly categorized based on form, type, and format. The triangulation method has introduced a conceptual framework of evaluation indicators in the scholarly publication ecosystem. Initially, a systematic review was conducted to extract evaluation criteria from 331 sources. Subsequently, to validate the extracted criteria and finalize the initial framework, the identified criteria were scrutinized across 12 scientific databases, and ultimately, it was endorsed by 30 domestic and international scholarly publication experts. The purposive sampling method was employed in all three studies.Findings: Research shows that the ecosystem of scientific publication consists of various components, including experts, scientific centers, information media, subject areas, information, and knowledge systems, which require different indicators and methods. The data extracted from the systematic review in the field of evaluation were classified into three groups: form, type, and format. Evaluation forms include content, open, altmetric, and bibliographic evaluations (creative and source evaluation). However, some experts distinguish between bibliometric evaluation indicators and scientometric and informatics evaluation indicators, and most experts in different subject areas define all three categories as bibliographic evaluations. In the evaluation form, creators include individuals and scientific organizations such as universities. Open evaluation can refer to judging an output not just by a jury of experts but rather by a jury of anyone interested in the output. In other words, open evaluations are an ongoing post-publication process of transparent peer evaluation. Multiple paper evaluation functions freely defined by individuals or groups provide various perspectives on the scientific literature. Multiple paper evaluation functions alongside more diverse research evaluation criteria beyond traditional methods are emerging, and with these come a range of practical, ethical, and social factors to consider. Altmetric evaluations are a set of methods based on the social web that measure and monitor the reach and impact of scholarly output through online interactions. Simply, altmetrics are metrics beyond traditional citations. This evaluating form measures cite, like, view, reuse, discussion, bookmark, etc. The types of evaluations include quantitative, qualitative, and mixed evaluations. The form of evaluation also includes technical evaluation and non-technical evaluation (researcher-made evaluation, discussion-based evaluation). Technical evaluations are indicators that follow predefined procedures or repetitive processes to reach the result, while experts define non-technical evaluations according to specific situations and conditions.Conclusion: The results of all three methods indicate that there are three key indicators and nine sub-indicators crucial for evaluating scientific output within the scholarly publication ecosystem. These indicators are predominantly grouped based on form, type, and format. The findings demonstrate alignment among the three studies (systematic review, observation of scholarly publication networks, and survey of experts). However, each study has highlighted specific evaluation indicators. According to the systematic review, observation of scholarly publication networks, and expert opinions, the primary focus in evaluating the scholarly publication ecosystem is on the form and type of evaluation. There is a greater emphasis on common and well-established formats in the evaluation process. Furthermore, individual and organizational needs and objectives significantly influence the selection of evaluation indicators. Categorizing evaluation indicators will assist stakeholders in understanding the evaluation procedures of scholarly publication ecosystems and in choosing appropriate evaluation methods.

This research aimed to screen ' essay writing' difficulties that non-native university students at postgraduate levels usually experience regarding scholarly publication in mainstream, English journals. Two sets of variables including written literacy competencies in Persian and English languages were mapped over language uses (General vs. Academic). Initial screenings from one hundred Iranian students at PhD and MA levels with publication experiences in both Persian and English languages gave rise to some fifty-five participants randomly selected from different university disciplines (Humanities, Engineering, Medicine and Basic Sciences) and diverse university settings (Public and Private) across the country and classified via stratified sampling. A validated questionnaire from a large-scale project called ENEIDA (Moreno, 2011) was used for collecting the required data. Two measures were used to assess written literacy competencies across language uses: 1) participants' assumed, self-reported written literacy competencies in using English and Persian languages for General and Academic purposes were denoted as ' perceived' measures and 2) further supported by actual measures: mostly received comments from reviewers in the mainstream, English journals by the target group above. Findings were discussed in the light of recent lines of enquiries in Academic Literacy (AL) trends.

Purpose: The present study aims to compare the specialization of Tehran Universities of Technology in the field of engineering. Material and methods: In this applied and scientometric study, data of Tehran Universities of Technology was collected using the Advanced Search section of the Web of Science database. These data related to the engineering field and its subfields scholarly publication between 1999 to 2018. HistCite and Excel have been used to analyze the data. Findings: The findings showed that RSI score of Sharif University of Technology, Amirkabir University of Technology, K. N. Toosi University of Technology, Iran University of Science and Technology, Malek-Ashtar University of Technology was in order 0, 576; 0, 568; 0, 566; 0, 605; and 0, 407. Also, the RSI score for each Tehran Universities of Technology has been calculated in engineering fields. In the final section, Tehran Universities of Technology ranked in terms of RSI score in engineering subfields. Conclusion: The results indicated the desirable situation of Tehran Universities of Technology specialization in the field of engineering. Sharif University of Technology also ranked first in the most of engineering subfields specialization.

Introduction: Today, researchers prefer to have most of their required information at their fingertips. Scholarly or research paper recommender systems are intelligent systems that aim to recommend the most appropriate scientific papers or resources based on users' needs. Past studies have shown that contextual information such as users', system' and environment' contexts influence the quality of recommendations. Therefore, the goal of this research is to identify effective user-oriented contextual information which influences the process of recommendation to scholars in medical area and then to present an architecture to design and develop an scholarly recommender system. Methods: Semi-structured interviews were carried out with 50 medical science professors and PhD studies in order to identify contextual information. Data resulted from interviews were analyzed in three stages using open coding, followed by axial and selective coding, developed in the Grounded Theory methodology. Then, contextual information has been exploited for a multi-layer architecture in design of a scholarly recommender system. Results: The results of our data analysis showed that scholars’ attributes such as purposes, literacy, skills, mental status, suppositions and assumptions, occupational condition, and social status are among the most influential factors which should be considered in designing a scholarly recommender system. Finally, based on the findings, we designed a multilayer system. Conclusion: Exploitation of contextual information in intelligent systems such as recommender systems and search engines leads to a better interaction between users and systems; therefore, the results of this study can be beneficial for designing other systems in this area.