Knowledge Retrieval and Semantic Systems

Abstract Abstract

Organizing information in digital archives, particularly historical ones such as the Islamic Revolution Document Center of Iran, faces challenges like the inefficiency of traditional information retrieval systems. This center, with over 4.5 million document pages, 31 thousand hours of oral history, and millions of news titles and articles, requires innovative approaches such as domain ontology and knowledge graphs to improve semantic access to key entities. The aim of this research is to model a domain ontology for the digital archive of this center using a hybrid approach of text analysis and reuse of existing ontologies. The research method is mixed: semi-automatic and automatic text analysis for entity extraction, model design based on ontology principles, and validation of findings using the nominal group technique. The findings include 535 classes that, after validation with criteria of 1) hierarchical logic, 2) historical/cultural accuracy, 3) alignment and equivalence, and 4) completeness and simplicity, resulted in 457 classes confirmed, 70 classes added, 53 classes relocated in the hierarchy, and 19 classes removed. This ontology provides a foundation for a knowledge graph, enhances semantic retrieval, and serves as a logical basis for artificial intelligence systems in managing Iran's historical documents. This research fills the gap in designing practical ontologies for contemporary Iranian history and is extensible to similar domains.

Abstract Introduction Regarding the increase in digital images and easy access to digital cameras, image processing and retrieval have become an important research field. Image retrieval is one of the important subfields of information retrieval that usually uses different techniques and models than text retrieval. The main expectation of users of information retrieval systems is to find relevant resources among thousands of resources available in these systems. Creating a scientific map of articles in the field of image retrieval using ontology can provide awareness of the status of published research; it can also help to show thematic relationships, identify influential topics, mature, emerging, and undeveloped topics, thematic gaps, and create appropriate scientific policies in this field. Literature Review A small number of studies have been conducted in the field of image retrieval using ontology, none of which have examined the hierarchical diagram. In the field of scientometric research, such as Daniali, Naghshineh, and Fadaei (2017); Daniali and Naghshineh (2018); Azimi and Jozi (2014); Ghanbari et al. (2014); Liu et al. (2021); Jo (2024); Khan et al. (2024). Scientometric studies often focus on assessing publication patterns, citation networks, co-authorship, and research productivity. These studies help researchers understand the structure and evolution of the scientific literature in a given field. Methodology In terms of type, the present study is in the category of applied research in which scientometric techniques and social network analysis have been used. The research community consists of those studies in the field of information retrieval with ontology that have been indexed in the Scopus database from the beginning to the end of 2024. Based on the formula in the search, 716 indexed articles were found in Scopus in the desired field. To be more precise, the statistical population of this study consists of all 716 published articles in the field of image retrieval using ontology. After retrieving relevant records and integrating data, based on the research objectives and questions, data analysis was carried out using BibExcel, Gephi, Excel, and SPSS, and the maps were created by VOSviewer software. In order to draw thematic maps and analyze them correctly, keywords were controlled and standardized by creating a Thesaurus in the software. In such a way that identical and similar keywords and plural and singular forms were merged and non-specialized and searched keywords were removed. In order to classify words in published documents based on semantic similarity using algorithms such as Euclidean distance and..., hierarchical clustering is usually used. Hierarchical clustering was performed using SPSS software. In order to implement and achieve the analysis, requirements such as a co-occurrence matrix must first be prepared, and then the co-occurrence matrix must be converted into a correlation matrix. The statistical population of the present study was the entire population. In order to perform a more accurate synonym analysis and final synonym analysis, the matrix was called through SPSS software, and the regular matrix was converted into a correlation matrix by SPSS software. The correlation matrix that was based on the obtained cognates frequency matrix, clusters and hierarchical were drawn using hierarchical clustering using the Ward method and squared Euclidean distance. Among the 716 retrieved articles, keywords with a frequency of 11 and more were selected for the research to prepare the matrix, and finally a square matrix of 142 by 142 was formed for the research. The diagonal cells of the matrices were considered zero and then these ordinary matrices were converted into a correlation matrix. Finally, the clustering of concepts was drawn based on statistical software (SPSS version 26). Finally, to draw a scatter diagram and identify the development and maturity status of the topics, the frequency matrix of each cluster was drawn separately, then their correlation matrix was drawn, and with the help of the strategic diagram, using the density and centrality of each cluster, their coherence and maturity were calculated. In the next step, a strategic diagram of thematic clusters was drawn; the strategic diagram describes the internal relationship and correlation between the different thematic clusters. Excel, Gephi, Babel Excel, and SPSS software were used to analyze the data, and Word Viewer, Excel, and SPSS software were used to draw the diagram. Results The results showed that among the keywords, the keyword image retrieval is in the first place with a frequency of 572. Among them, the keywords ontology and semantics are in the second and third places, respectively. Also, the analysis of the findings related to the synonym of image retrieval using ontology took the form of six thematic areas. Infrastructures and fundamental technologies of image retrieval, techniques of concepts and image analysis, intelligent machines and applications in image retrieval, web concepts and search based on ontology, managerial and human aspects in information retrieval, quality improvement and query processing in image retrieval. The results obtained from the hierarchical diagram formed four topic clusters. Also, the findings from the strategic map of image retrieval topics using ontology indicate that cluster 1 was placed in the first part due to its high centrality and density. These clusters are higher in centrality and density. Clusters 2 and 4 are placed in the second part. The clusters that are located in the second part of the strategic picture are regional clusters. But they are developed. Cluster 3 is located in the fourth part. The clusters in the fourth part are the main ones, but are undeveloped and immature. Discussion With the help of scientometrics, a macro picture of the state of research and how different domains are related, can be presented. Co-occurrence analysis led to the formation of six clusters. Fundamental infrastructures and technologies of image retrieval, semantic techniques and image content analysis, machine learning and intelligent applications in image retrieval, semantic web and ontology-based search, managerial and human aspects of information retrieval, quality improvement and query processing in image retrieval. Among the existing concepts, some of them have received the highest number of citations: such as image retrieval, machine learning, computer vision, deep learning, database systems, digital libraries, Internet, WordNet, artificial intelligence, and information retrieval. A hierarchical diagram of four thematic clusters was formed: semantic-based image retrieval, intelligent image retrieval with learning algorithms, semantic image retrieval with annotations, and intelligent image retrieval. Conclusion Studies in the field of image retrieval using ontology as a useful tool for effective retrieval can play an effective role. Most studies are in the field of ontology and ontology construction, but no specific research has specifically addressed this area. In this study, the emphasis is on image retrieval, but the high importance of this area, the recognition of the components of this area, and the impact of ontology on semantic retrieval require researchers to focus on these issues, and the results of this study indicate that very little attention has been paid to this area, especially in Iran. Scientific maps are a suitable method for displaying the increasing growth of scientific activities and organizing the intellectual and scientific structure that constitutes a thematic domain. Researchers, science policymakers, and other interested parties can advance their own goals and advance with greater awareness in this field by being aware of this structure.

Abstract The purpose of the current research is to draw and analyze the intellectual structure and evolution of knowledge in the field of RDF with the method of co-occurrence analysis of words and clustering of concepts and events in this field. This is an applied research that was carried out with a scientometric approach. The statistical population of this research includes all the researches conducted in the field of RDF in the Web of Science database from 1998-2021. Also, the data collection tool in this research is note-taking and the data analysis tool is co-occurrence analysis of words and network analysis using Vosviewer, Netdrow, SPSS and Bibexecl software. The findings of the research showed that the keywords RDF, Semantic web, Ontology, linked data and SPARQL are the most frequent words and the keywords RDF* semantic web, RDF* Academic Ontology and RDF* SPARQL are the most frequent word pairs. Also, the co-occurrence analysis of words network includes six clusters named "data model scalability", "RDF representation of bibliographic entities and relations", "ontology alignment", "semantic web and linked data", "data management and publishing" and "data mining". In addition, the network density is equal to 0.068, which is not in a favorable condition. The clusters of "data model scalability", "ontology alignment", "data management and publishing" and "data mining" have not yet reached sufficient maturity and require a lot of follow-up and research in these fields. The results showed that the scientific productions of the RDF field, despite its upward publication trend, have more subject dispersion and are more oriented towards the semantic web, and the analysis of the co-occurrence network of words in this field also has a greater subject dispersion, which indicates the interest of researchers to various topics in this area.

1.Introduction

The abundance of publications in the field of Resource Description Framework (RDF) presents a challenge for researchers seeking a comprehensive understanding of the domain. RDF, a graph-based data model crucial to the Semantic Web, enables machine-readable data representation and interoperability across systems. The growing volume of RDF-related literature highlights the need for a structured analysis to identify key concepts, trends, and thematic evolution in this interdisciplinary field. Therefore, creating a scientific map of articles in the RDF field using the thesaurus method and presenting a strategic diagram will enhance awareness of published research status, illustrate topic relationships, identify influential topics, mature, emerging, and underdeveloped topics, thematic gaps, and establish sound scientific policies in the field. This study aims to map the intellectual structure and track the knowledge evolution in the RDF domain using scientometric approaches.

Research Question(s)

What has been the trend in scientific publications within the field of RDF from 1998 to 2021 in the Web of Science database?
How the frequency distribution of the most is commonly used keywords in RDF-related articles from 1900 to 2021?
What does the co-word network in the RDF domain look like during the period 1900 to 2021?
How are the co-word clusters in the RDF domain structured, and what are the thematic topics within each cluster from 1900 to 2021?
To what extent have the co-word clusters in the RDF domain matured over the period from 1900 to 2021

2.Literature Review

Previous studies have utilized co-word analysis in various domains such as digital libraries, military trauma, COVID-19, and knowledge management to reveal thematic structures and developmental trajectories. However, there is a gap in applying this approach specifically within the RDF domain. Studies by Alipour-Hafezi et al. (2017), Rezaeizadeh & KaramAli (2018), and Jin & Li (2019) demonstrate the effectiveness of scientometric techniques in visualizing knowledge structures, identifying research gaps, and tracing emergent topics. This study builds upon these methodological foundations to comprehensively explore the RDF field.

3.Methodology

This applied research employs a scientometric methodology grounded in co-word analysis. The dataset includes 1,271 scholarly articles published between 1998 and 2021 and indexed in the Web of Science database. Tools such as VOSviewer, Netdraw, SPSS, BibExcel, and UCINET were used to conduct word co-occurrence analysis, hierarchical clustering, and strategic diagramming. The analytical process involved keyword standardization, matrix generation, network visualization, and calculation of centrality and density indices for identified clusters.

4.Results

The research findings reveal that keywords such as RDF, Semantic Web, Ontology, Linked Data, and SPARQL are the most frequent, while word pairs like RDF* Semantic Web, RDF* Academic Ontology, and RDF* SPARQL are common. The co-occurrence analysis of the word network reveals six clusters named "data model scalability", "RDF representation of bibliographic entities and relations", "ontology alignment", "semantic web and linked data", "data management and publishing", and "data mining". The network density is 0.068, indicating a less favorable condition. Clusters like "data model scalability", "ontology alignment", "data management and publishing", and "data mining" are not yet mature and require further research.

5.Discussion

The findings suggest that while the RDF domain has seen an increase in publication volume, it still faces thematic fragmentation and limited interdisciplinary integration. High centrality in certain clusters indicates dominance, but low-density values suggest underdeveloped interrelations among concepts. This highlights the need for broader collaboration and diversification of research topics within RDF. The prevalence of semantic web topics reflects current research interests, while emerging areas like data scalability and ontology alignment require more attention.

6.Conclusion

This study offers a detailed intellectual mapping of the RDF field, highlighting dominant themes and emerging areas for further exploration. The low network density and dispersed thematic structure emphasize the need for increased interdisciplinary collaboration. Policymakers and researchers are encouraged to support studies in underdeveloped RDF subdomains to promote comprehensive scientific growth. The strategic insights provided by this analysis can guide future research priorities and contribute to the development of a cohesive knowledge structure within the RDF domain.

Abstract Introduction

The present research attempts to identify standard metadata elements for organizing learning objects in the organizational repositories of Iranian medical sciences universities based on the learning object metadata standard. The present research aims to design an ontology model of electronic learning objects in the organizational repositories of Iranian medical sciences universities in order to better display the identification metadata elements. From the semantic point of view, showing semantic relationships between learning objects and better retrieval of learning objects in order to take an effective step towards managing and making information resources available for e-learning.

Literature Review

The Institute of Electrical and Electronics Engineers Learning Technology Standards Committee defines a learning object as a digital entity that can be used, reused, or referenced during learning (reusability). One of the electronic learning resources is online learning object repositories. Repositories of learning objects are basically the storage of research data and educational materials. To efficiently retrieve educational materials according to the needs of e-learners, educational materials are tagged with a set of metadata that describe educational works such as document topic, document type, etc. Metadata is an important component of learning object description resources. Metadata is also important for interoperability operations. This is because schema metadata is transferable in interoperability standards. The ontology of learning objects for the field of e-learning provides semantic connections between learning objects and provides high-level information and the development of e-learning. Therefore, the ontology of e-learning objects for organizational repositories of Iranian medical sciences universities provides accurate and meaningful learning objects for the e-learning community. The proposed ontology in this research is based on the metadata standard of the learning object and the characteristics of the learning objects to help the organizational repositories of Iranian medical sciences universities in organizing their information, quickly and accurately retrieving educational materials, facilitating the reuse of content and improving the quality of the electronic learning process and it even provides the use of objects to create a general context of learning environments using a concept map of e-learning. In fact, the ontology design of electronic learning objects for the organizational repositories of Iranian medical sciences universities based on the learning object metadata standard helps to describe the learning objects in a structured way, and this importantly improves the retrieval of learning content and better access to electronic learning content in the repositories.
 

Methodology

The purpose of the research is applied research. In the current research, the observation and survey method was used and the matching of the standard metadata elements of the learning object with the metadata elements of the learning objects in the organizational repositories of the research community was discussed. Then, the researcher-made questionnaire was provided to the experts to perform the Delphi technique in order to modify and validate the identified elements. In the next step, a verified set of elements and entities for e-learning objects was obtained in the organizational repositories of Iranian universities of medical sciences. Finally, based on the identified entities, the ontological model of electronic learning objects was designed based on the learning object metadata standard in the organizational repositories of Iranian medical sciences universities.The data collection tool is a researcher-made questionnaire and a standard metadata framework of the learning object. Version 5.6.1 of Protege software was used. During the ontology construction process, the software outputs were evaluated by experts in the field. After confirming the concepts and relationships, a conceptual structure was presented based on the findings.

Results

 The findings showed that the designed ontological model consisting of 162 classes with a total of 189 types of relationships and 2220 samples located in the classes was illustrated.

Conclusion

 The results of the research showed that the learning object metadata standard is comprehensive as a combined standard that includes all types of metadata. Based on the identified entities based on the learning object metadata standard, the ontological model of electronic learning objects was designed in the organizational repositories of Iranian universities of medical sciences. The designed ontology has the overall accuracy as well as the accuracy of different components. The result of this ontology is to present a conceptual structure consisting of concepts in an explicit form in a formal format. By applying ontology based on the learning object metadata standard in the structure of organizational repositories of medical sciences universities of Iran, it is possible to fix possible errors in the semantic level of data, including improving retrieval, better access, and designing intelligent systems.

Abstract Introduction

Ontologies offer a structured framework for information sharing across various systems and fields. This framework facilitates data integration from diverse sources, enabling accurate searches based on semantic relationships between concepts. Additionally, ontologies allow for analysis and logical inference from datasets, improving information retrieval speed and accuracy in various scientific disciplines, including the humanities and Islamic studies. This research explores the creation of an ontology for weak narrators in the field of Hadith studies, specifically focusing on the book "Ma'refah al-Hadith" by Mohammad Bagher Behboodi, which examines the conditions of 150 weak narrators. By structuring and analyzing the information on these narrators, the ontology aims to facilitate faster and more efficient analysis of the "Causes of narrators' weakness."

Literature Review

Several research efforts have explored the design and application of ontologies in various disciplines. These studies include:

The necessity of creating an ontology of jurisprudence to manage jurisprudential information in the digital space (Hasanzadeh, 2018)

2.       Basmaleh Ontology, a Window for Creating an Ontology of Qur'anic Studies (Hasanzadeh, 2021)

A network approach in the interpretation of the Qur'an as an infrastructure to achieve the ontology of the Qur'an (Vaseti, 2023)
Semantic Hadith: An ontology-driven knowledge graph for the hadith corpus(Binte Kamran. 2023)
Creation of Arabic Ontology for Hadith Science(Abdelkader, 2021)
Quran Intelligent Ontology Construction Approach Using Association Rules Mining(Harrag, 2013)
Arabic Ontology for Hadith texts - A survey(Muhammed. 2024)
Building Hadith Ontology to Support the Authenticity of Isnad (Baraka.2014)

These studies demonstrate the benefits of ontologies in facilitating faster and more intelligent information retrieval across various fields.

Methodology

The research method is content analysis using Protege software version 5.5.0. The steps of forming OWL ontologies according to the features of the Protégé software are as follows:

Identify concepts, extract them, and document them to create terms.
Place these terms in the form of main and sub-classes as well as examples or members in the respective views in the software.
Create relationships (attributes) between classes and examples and between these terms and values.
Evaluate the quality and effectiveness of the ontology and its ability to support knowledge representation.
Results

The initial data collection involved identifying two main classes in the Protégé software: "Hadith Narrators" and "Invalidation words". Under the "Hadith Narrators" class, the names of the 150 weak narrators were included. The "Invalidation words" class encompasses terms used by Hadith scholars and various expressions indicating the weakness of narrators. Sample sentences from Hadith scholars were placed as examples under each subclass. Object properties were then employed to establish connections between these classes and the specific narrators exhibiting the identified weaknesses. These object properties linked the sayings of renowned Hadith scholars such as Sheikh Tusi, Ayyashi, Allameh Majlesi, and others, to the relevant narrators.

Discussion

Analysis of the collected data revealed diverse reasons for the weakening of Hadith narrators. Some terms point to the "weakness of the narrator and their character," including instances of deviant beliefs, affiliation with questionable sects, or the presence of negative personality traits that could potentially compromise the reliability of their narrations. Additionally, other terms may signify the "weakness of the hadith itself" narrated by a particular individual. The ontology construction process identified 107 terms representing concepts related to the weaknesses of narrators. Subsequently, 645 examples were incorporated into the Protégé software, all derived from the text of the book and the statements of Hadith scholars.

Conclusion

Ontologies provide a valuable platform within the semantic web, enabling machines to understand and process information in a more intelligent and nuanced manner. Their role in facilitating data sharing and information retrieval across diverse systems is crucial. By creating a structured framework for integrating data from various sources, ontologies empower researchers to conduct more precise searches based on semantic relationships. Furthermore, they enable analysis and logical inference from datasets, ultimately enhancing knowledge sharing within a specific domain. This research contributes to the field of Hadith studies by proposing an ontology for weak narrators. The ontology explores the words of established scholars and analyzes their statements regarding the weaknesses of 150 narrators in "Ma'rifa al-Hadith" by Mohammad Bagher Behboodi. Through this analysis, as many as 107 words or concepts indicating the weakening of the narrators and the number of 645 samples were obtained and by creating an ontology through the two classes "Hadith Narrators" and "Invalidation words" in the Protégé software, a meaningful connection was established between them. This engineered knowledge base facilitates efficient access to information regarding narrator weaknesses and will lead to the collection of extensive information in the field of hadith and the investigation of the causes of the weakening of the narrators, which will provide the basis for wider and deeper research.

Abstract Introduction
Organizational 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 Review

Research related to ontology design can be divided into two main categories:
2.1. Studies that examine the application of ontologies
The 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 ontologies
The 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.

Methodology

This 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.

Results

The 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. 

Discussion

Based 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.

Conclusion

In 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.

Abstract 1. Introduction
The importance of this research will be to add more color to the inherent characteristics of the field of information science and epistemology in terms of storing and retrieving information and meeting the information needs of the clients by producing an archive ontology and the role and impact of the information profession in meeting the information needs of the clients.

2. Literatur Review
Since librarians play an intermediary role in the exchange of knowledge. In the new era, their challenges and the scope of their responsibilities have increased significantly so that they are able to be important helpers to control the expanding world of information.
What constitutes the main problem of information science today is the methods of accessing information. If previously the concern of information science specialists was to regularly collect resources and provide bibliographies, now most efforts are focused on providing more information about resources and delivering them to the end user. For these reasons, it can be said that today the traditional structures of libraries have collapsed and the new order has replaced it. In the past, the traditional role of reference department employees of libraries and information centers was to provide bibliographic information to the referents, that is, to provide information about the information, but today their duty is to guide the referents to the same information. Another important thing that happened in the process of the information revolution is the sharing of resources, the creation of information networks using new information technologies made not only the information centers of a country but all the information centers of the world share in each other's resources. (Mahdavi, 1998)
Libraries play an intermediary role in the exchange of knowledge, the emergence of the Internet created the impression that libraries will go away, but the passage of time has shown that this impression only stems from a lack of proper understanding of the position and function of the library (Middleton, 2012)

3. Methodology
This research is applied in terms of purpose and sequential combination (qualitative-quantitative) in terms of type. In this way, first by using the library method based on the study of literature and backgrounds related to the subject, the components and characteristics of the dictionary were extracted, then by using the qualitative method (Delphi study) based on the opinions of experts in information science and an in-depth interview was conducted in three stages, the components were extracted by the content analysis method and the lexical circle was determined. After the analysis of quantitative data, the necessity of creating an ontology for radio and television archives became clearer, and in the following, the proposed ontology model of radio and television archives was presented.
In this research, the studied community of archivists of radio and television archives in Tehran, whose number was 120, has been investigated through a census through a digital questionnaire. Also, in order to present the proposed ontology model, the words related to the topics and production programs in the broadcasting organization were collected and a preliminary ontology was prepared for the broadcasting archive as a sample using Protege software. The proposed ontology resulting from the transformation of concepts in the field of radio and television programs, which is available in its archives, was carried out in four stages: collecting concepts, discovering and determining the relationships between concepts, creating a worksheet for each concept and implementing the ontology in the project environment. This proposed model can be useful for producing the ontology of radio and television archives.
​​​4. Results
After three rounds of interviews with experts in the field of archives (10 experts in the field of archives and managers of radio and television archives in Tehran) and analysis of the opinions of the participants in the Delphi study panel, it was determined that 15 components were used to measure vocabulary. From these main components, a number of quantitative questions were developed by the researcher. 85 questions were asked from the statistical population. The following results are the results of the analysis of the research questionnaire for the section related to the vocabulary of radio and television archivists:
Descriptive statistics indices such as: frequency, percentage, mean, and standard deviation have been used to examine and analyze the respondents' information. Research hypotheses are also used. The structural equation modeling technique has been tested. In order to get a better understanding of the research community and get more familiar with the research variables, before analyzing the statistical data, it is necessary to describe these data. Therefore, before testing the research hypotheses, the descriptive statistics of the variables used in the research were examined. The average, as one of the central parameters, represents the center of gravity of the society, and in other words, it shows that if the average is placed instead of all the observations of the society, there will be no change in the sum total of the society's data. Also, the maximum shows the highest variable number in the statistical population and the minimum shows the lowest variable number in the statistical population.

5. Discussion and Conclusion
Broadcasting archives play a role in program production as the beating heart of programming, since these centers are considered as a center for storing the produced resources, less attention has been paid to their role and influence in the program production process. Radio archivists, since they are educated in information science and science, and professionally, can play an effective role in retrieving information and providing optimal information for producing programs and helping to improve the programming process. Archive ontology and training related to information retrieval and the use of information retrieval tools can play a more colorful role in professional activity. The strength of the relationship between the rich vocabulary and the quality of the information provided by radio archivists has been calculated as 0.74, which shows that there is a favorable correlation between vocabulary and ontology in information delivery. The t-statistic of the test is also 2.14, which is greater than the critical value of t at the 5% error level, i.e. 1.96, and it shows that the observed correlation is significant. Therefore, the hypothesis of the research is confirmed and it can be said that there is a direct relationship between the rich vocabulary and the quality of information provided by radio archivists and the ontology of the archive.
Enhancing their vocabulary, which is one of the main components of the field of information science and epistemology, can help in achieving the goal of providing quality information and retrieving resources in archives and using them in programming. The results of the present research also confirm the opinion that an archivist with a rich vocabulary using archive ontology can be useful in retrieving information and providing information optimally. The proposed ontology resulting from the transformation of concepts in the field of radio and television programs, which is available in its archives, was carried out in four stages: collecting concepts, discovering and determining the relationships between concepts, creating a worksheet for each concept and implementing the ontology in the project environment. This proposed model can be useful for the production of the ontology of radio and television archives.

Abstract Introduction
The emergence of the web facilitated the retrieval of information. This made libraries as one of the most important centers of information considering the web for the information retrieval process. However, the fast change of the web leads to the transformation of library functions. The semantic web is an opportunity for libraries to change their functions. Linked data as a method in the semantic web can make a major change in library functions. It can improve the discoverability, visibility, and interoperability of the resources. For example, all libraries use authority controls for organizing their information. But using authority controls in a traditional way can be challenging. Therefore, using the web can help libraries tackle these potential challenges and problems. Transforming authority data into linked data which seems an innovative and faster way for finding the resources can be a step forward for libraries and users. This paper aims to design a framework for transforming the National Library of Iran Subject Headings into linked data and publish them on the web.
Literature Review
Designing and proposing a framework for linking the data was the topic of some research papers. Linking the university data (Behkamal et al., 2011) linking and visualizing medicine information (Sekhavati, Farahi, & Jalali, 2011) web objects (Hosseini, 2020), table data (Mulwad et al., 2010), Industrial Data (Graube et al.,2012), and government data (Villazón-Terraza, Vilches-Blázquez, Corcho, & Gómez-Pérez, 2011; Mulwad, Finin, & Joshi, 2011) were the topics for some reviewed studies. The results of their studies indicated that in general, linked data could improve information retrieval. Implementing a linked data method in library data was discussed in some papers. Kar & Das (2020) designed a methodology for linking bibliographic information in a digital repository. Similarly, Ryan et al. (2015) examined the linking of place names in a dataset, transferring them into RDF and linking them with other similar datasets. Summers, et al (2008) provide a methodology for transferring subject headings into linked data. their results showed that transferring LCSH into SKOS affects information retrieval. The linking and publishing National Library of Iran data were also investigated by Eslami & Vaghefzadeh (2013). Fathian Dastgerdi et al (2020) tried to make a pattern for linking data in library systems. They examined the components which are needed for implementing the linked data method in library systems. Their result showed that using linked data in library systems affects the visibility of bibliographic metadata. Based on the reviewed studies, many international papers discussed publishing library linked data in theoretical and practical ways. Whereas studies done in Iran focusing on linked data mostly developed patterns and models for linking data (e.g., Fathian Dastgerrdi; 2020). Few Persian studies were done for publishing bibliographic data (e.g., Eslami & Vaghefzadeh, 2013; Sekhavati, 2011). Although there is a significant number of papers discussing linked data, the technical aspect for publishing and linking library data was rarely examined. To fill this gap, this study aims to develop a framework for publishing National Library of Iran subject headings which is unlike Fathian Dastgerdi et al., (2020) paper considers the technical tools and aspects and unlike Sekhavati’s (2011) paper examines the Persian subject headings.
Methodology
This research is an applied study that utilizes a library method for designing a publishing framework. Linked data was implemented to ensure the possibility of publishing the research data. First, Persian subject headings which are represented in Iran MARC format were obtained in Marc XML files From the National Library of Iran. Then the method for transferring and publishing the data was applied.
Results
The framework developed in this research collected National Library of Iran subject headings randomly. The selected data were first cleaned by Microsoft Excel and MarcEdit. In the next step, cleaned data were converted into RDF Using OpenRefine. The study’s project was imported to Open Refine software, linked with external datasets, and saved in a triple store. Finally, the linked subject headings were displayed through the Skosmos interface.

Discussion
Publishing library data as linked data is an example of utilizing Web 3 in library systems. National libraries worldwide have tried linking their data including subject headings with other datasets. However, there remains a gap in publishing linked Persian subject headings and to the best of the authors' knowledge it seems that no paper has pointed to technical aspects of implementing Persian subject headings.
Conclusion
The current paper has transformed the Persian subject headings into a linked dataset in an RDF turtle format. Then, it visualized the linked data in the Skosmos interface. But there can be some limitations to this study. Using OpenRefine was reported successfully in this paper, but it seems that there may be a problem in data with larger sizes. In conclusion, since this framework improve the retrieval of authority data in this research, it can be used for publishing National library of Iran subject headings.