Negin Shokrzadeh; Zoya Abam; Seyed Mahdi Taheri
Abstract
Objective: Today, meta-models are used to organize and manage metadata, therefore, the aim of this review was to examine the research related to the design techniques of meta-models.Methodology: This study was conducted based on a systematic review method. In this review, the Preferred Reporting Items ...
Read More
Objective: Today, meta-models are used to organize and manage metadata, therefore, the aim of this review was to examine the research related to the design techniques of meta-models.Methodology: This study was conducted based on a systematic review method. In this review, the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) framework was employed to ensure a focused review and to present coherent findings. Relevant research was identified through databases and citation sources such as Web of Science, Scopus, Emerald, Taylor & Francis, and Science Direct, and by applying inclusion and exclusion criteria, 22 scholarly outputs were selected for the systematic review.Findings: The findings of the review indicated that metamodel refers to metadata about metadata, providing a higher-level framework that describes the structure, relationships, and contextual purpose of metadata elements in various systems. It essentially aids in the standardization, organization, and interpretation of metadata from multiple sources, facilitating and expediting the integrity, interoperability, and usability of data. Metamodel elements within systems serve as key components for information management and organization. These elements include characteristics related to the quality of metadata, like accuracy, completeness, and currency of the metadata. Meta-models aim to enhance the capabilities of data management and retrieval in complex and heterogeneous systems, incorporating flexible and practical features into their structures.Conclusion: Meta-metadata models,, play a crucial role in optimizing information management and retrieval processes, especially in complex and diverse environments. Implementing these approaches can lead to the development of effective and efficient systems across various fields.
Knowledge Management Systems and Technologies
Seyed Mahdi Taheri; Negin Shokrzadeh
Abstract
IntroductionScientific outputs that report on the findings of scientific research play a crucial role in enhancing knowledge, advancing science, and promoting research within academic communities. Therefore, the aim of this research project was to analyze the scientific outputs of Allameh Tabataba'i ...
Read More
IntroductionScientific outputs that report on the findings of scientific research play a crucial role in enhancing knowledge, advancing science, and promoting research within academic communities. Therefore, the aim of this research project was to analyze the scientific outputs of Allameh Tabataba'i University and to represent them in the form of scientific maps. Research Question(s)What is the status of the university's scientific output in international citation indexes and the scientific maps of co-authorship networks, co-occurrence of terms, inter-terms, and their frequent terms?What is the status of the publication of books by researchers and faculty members of the university, and how is the scientific map of their co-occurrence of terms drawn?What is the status of the theses/dissertations of Allameh Tabataba'i University in terms of publication and subject area, and how is the scientific map of their frequent terms drawn?What is the status of the publication of articles by Allameh Tabataba'i University in internal and external systems that do not have citation indexes (not indexed), and how is their scientific map drawn?What is the status of research projects at Allameh Tabataba'i University and how is their scientific map drawn?Literature ReviewPrevious studies in the field of scientific mapping were categorized into two groups. The first group contains research that has focused on mapping scientific fields across various disciplines. Notable studies include those by Meskarpour Amiri et al. (2022); Varnaseri et al. (2022); Mohammadzadeh & Baghernejad (2023); Alipour Hafezi and Matlabi (2022); Yao et al. (2014); and Masoumi and Khajavi (2023). In the second group, studies are included that address scientific mapping in different universities. Research by Mohammadian, Esmaeili Givi, and Nahghineh (2016); VahdatZad et al. (2017); Galyani-Moghaddam and Taheri (2018); Ghasemian, Asnafi, & Erfanmanesh (2021); Soltani et al. (2022); Goftari (2024); Sandler and Gladyrev (2020); Chen and Zhang (2023) fall into this category. An examination of the research conducted has shown that in recent years, there has been an increasing interest in evaluating the scientific outputs of universities as a way to assess their performance and research impact. One of the most common criteria used for evaluating scientific outputs is the number of publications produced by a university. Additionally, studies have indicated that apart from the number of publications, other metrics such as the number of citations, journal impact factors, and H-index scores are often used to assess the scientific outputs of universities. Furthermore, in recent years, there has been significant interest in developing alternative metrics or altmetrics to evaluate scientific outputs.MethodologyThis paper was conducted using scientometrics research methods. The aim of this research was to analyze the status of the scientific outputs from Allameh Tabataba'i University and represent them in the form of scientific maps using bibliometric research methods. The statistical population of this study included all research outputs (international articles, books, theses/dissertations, domestic journal articles, and research projects) from Allameh Tabataba'i University in Persian and other languages between the years 1974 to 2024, totaling 69,420 titles. In this study, analytical tools from citation databases, reports from the university's research systems, and bibliometric tools were utilized to collect the necessary data. Data analysis was performed using descriptive statistics, social network analysis, and co-occurrence of keywords. Excel software was used to create tables, UCINET and VOSviewer softwares were employed for analyzing centrality indicators and visualizing the networks.ResultsAmong the 3,227 articles published by researchers from Allameh Tabataba'i University in the Scopus citation index, 1,091 articles, accounting for 18.6%, are in the field of social sciences; 666 articles, representing 11.4%, are in the field of medicine; 493 articles, also at 8.4%, are in the field of computer science; and 492 articles, another 8.4%, are in the fields of business, management, and accounting. The lowest number of articles are in the fields of veterinary science, with 4 articles; immunology and microbiology, with 21 articles; and chemical engineering, with 23 articles. In total, 1,105 article titles from the university have been published in the Web of Science index, of which 23 are among the highly cited articles. The most common keywords were Iran, decision-making, supply chain management, and policymaking. The subject area of statistics and probability, with 114 titles, and the subject area of artificial intelligence, with 103 titles, were identified as the most active research areas at Allameh Tabataba'i University. An investigation of the theses and dissertations from the university indicated that the keywords Iran, education, learning, quality of life, economic growth, job satisfaction, and others were frequently used. A review of over 28,000 domestic articles from the university showed that the keywords Iran, effectiveness, students, and quality evaluation were most commonly employed. Most research projects at Allameh Tabataba'i University were centered around topics such as educational satisfaction, employment status, and students' social activities.DiscussionThe findings indicate that in recent years, the number of publications from Allameh Tabataba'i University in international indexes has increased, reflecting the university's greater focus on publishing articles in international journals. However, the conducted reviews show that, in terms of citations, the articles from Allameh Tabataba'i University require more visibility, as only 23 out of the 1,105 articles published in the Web of Science index are classified as highly cited. It can be stated that Allameh Tabataba'i University has a favorable status in conducting research across various thematic areas.ConclusionOverall, it can be stated that mapping scientific outputs can lead to improvements and advancements in scientific fields, development of knowledge, enhancement of universities' credibility, facilitation and acceleration of data understanding and analysis, improvement of communication and collaboration among researchers, knowledge sharing, and increased transparency of research and its results. Undoubtedly, evaluating scientific outputs requires the participation and collaboration of all university members to be favorably integrated into the university's overarching policies. It is expected that by utilizing these tools, Allameh Tabataba'i University and other educational and research institutions can enhance their research processes and improve the quality of their research outcomes, thereby contributing to knowledge development and increasing the scientific credibility of the country. To enhance the functionality of scientific outputs, it is recommended to use specific keywords that are suitable for the thematic context of the research to clarify the subjects of the outputs.AcknowledgmentsThis research has been conducted with the support of the Research Vice-Presidency of Allameh Tabataba'i University. In this regard, the researchers express their gratitude.
Semantic Web and Ontology
Seyyed Mahdi Taheri; Elham Hooshmand; Esmat Momeni; Negin Shokrzadeh Hashtroudi; Mehdi Alipour Hafezi
Abstract
IntroductionOrganizational ontologies are a type of ontology that focuses on identifying and documenting organizational entities. These tools provide a common conceptualization of organizational entities and are utilized for representing organizational knowledge, describing organizational structures, ...
Read More
IntroductionOrganizational ontologies are a type of ontology that focuses on identifying and documenting organizational entities. These tools provide a common conceptualization of organizational entities and are utilized for representing organizational knowledge, describing organizational structures, identifying entities, and revealing the features and relationships of entities. They also, support the dissemination of organizational data, generated reports, organizational history, human resources, and the roles of each of these through a linked data approach. Therefore, the purpose of this research was to design the business ontology of Ehya Sepahan Company based on semantic web data models.Research Question(s)In the present research, the following questions have been addressed:- What are the internal and external entities of the Ehya Sepahan Company and their attributes?- To what extent do the entities and attributes of the Ehya Sepahan Company align with the Schema.org data model?- How is the organizational ontology of the Ehya Sepahan Company structured based on the organizational ontology of the World Wide Web Consortium?Literature ReviewResearch related to ontology design can be divided into two main categories:2.1. Studies that examine the application of ontologiesThe first category includes studies that examine the application of ontologies or the design of ontologies in specific contexts. Research by Sharif (2008), Bavakhani (2015), Hassanzadeh, Kahani, and Pourmasoumi (2016), Mardpour and Dehghan-Tafti (2017), Akbari and Rajabi-Bahjat (2018), Fuchs-Kittowski and Faust (2008), Cavaliere et al. (2019), and Outa et al. (2020) fall into this category. In this context, Bavakhani (2015) explored the interrelationship between ontologies and knowledge management. Cavalier et al. (2019) designed an ontology design model for analyzing video content captured by drones in their study. The findings of the studies in this group indicate that in contemporary organizations, there is a necessity to utilize ontologies in processes related to existing knowledge. 2.2. Studies that specifically address the design of organizational ontologiesThe second category includes studies that specifically address the design of organizational ontologies for various organizations. Research by Delavari (2018), Rajabi and Alineghizadeh Ardestani (2019), Gualtieri and Rafolu (2005), Santos et al. (2013), and Elnagar et al. (2022) are included in this group. Rajabi and Alineghizadeh Ardestani (2019) presented a data-driven approach to develop an architectural model using organizational ontology. Elnagar et al. (2022) offered a framework for the automatic production of ontologies from an organizational perspective in their research.MethodologyThis study was developmental-applied research in nature and qualitative research in terms of approach, conducted using qualitative content analysis and design methods. The statistical population includes all entities of the Ehya Sepahan Company (data entities, human resources, organizational positions), as well as the classes and attributes present in the organizational ontology.The research was conducted in several sections; initially, by examining the organizational ontology, the classes and attributes needed for modeling the entities and attributes present in the Ehya Sepahan Company were identified. Subsequently, through reviewing organizational documents, the organizational structure, job descriptions, and various departments of the company, the organizational entities and the characteristics of each were identified. With the identification of the entities and main concepts of the company, the necessary classes and attributes were determined. Since the aim of this study was to design a company ontology based on a semantic web data model, alongside the main classes and attributes of its organizational ontology, standard metadata classes and attributes from the Schema.org data model were used. In this research, Observation and documentary methods and a checklist are utilized for gathering the required data.ResultsThe findings of this research revealed that the entities of Ehya Sepahan Company are divided into internal and external entities. In total, 9 main entities and 3 external entities were identified for the company’s ontology. Various attributes were provided for each of these 12 entities. A total of 152 attributes were identified for the 12 entities of the company, and these attributes were assigned to different entities. For the internal entities, 147 attributes were used, while for the external entities, 21 attributes were utilized.The findings revealed that most of the attributes considered for company entities are presented in the schema.org standard. So, all the mentioned attributes for Organization, Person, Website, and Product entities in schema.org are consistent with the attributes needed to describe the company entities. the investigation of organizational ontology showed that this ontology has 9 entities and all these entities were used to design the ontology of Ehya Sepahan company. Likewise, the results showed that there is a good alignment between the attributes of the organizational ontology and the schema.org metadata standard. DiscussionBased on the finding it could be said that the entities of the company each possess unique characteristics. Accordingly, specific attributes were considered in the organizational ontology based on the features of each of these entities to provide an accurate and appropriate description of the company and its entities. For a large number of attributes considered for the company’s entities, suitable attributes are provided in schema.org. All the attributes mentioned for organizational entities, such as person, website, and product, align with the necessary attributes needed to describe the company’s entities in schema.org. The reason for this suitable alignment between entities and the attributes of the organizational ontology and schema.org is the comprehensive perspective of schema.org as a semantic web data model for describing various types of data entities.ConclusionIn general, it can be stated that organizational ontologies are one of the efficient tools for accurate description and knowledge discovery of data entities of organizations that can be used to facilitate and speed up processes and decisions in the organization.
