Introduction: Ontologies improve the quality of information retrieval (IR). Therefore, it is important to better know the process of ontology engineering and their application in IR. The aim of this research was to identify the engineering methods of ontologies and also their application in biomedical IR.Method: This review was done through library research method with an analytical approach.Required information for the review was retrieved from Pubmed, Scopus and Web of Science using keywords: "Ontology-based biomedical Information Retrieval", "Information Retrieval", "Biomedical Information Retrieval", "Ontology engineering", "Ontology construction", "Biomedical Ontology" and "Ontology building" without time limit. Five articles addressing an ontology-based biomedical IR system were reviewed.Results: Studies on ontology based biomedical IR, started in 2004, are not limited to a single country. In general, ontologies are used to manage the semantic metadata. Although most IRs try to develop their own ontologies, reuse of earlier ontologies is a priority. The material for developing ontologies is taken from the literature in the domain. The studied ontologies have been produced by centralized approaches and decentralized approaches and different groups have not been used.Conclusion: The main purpose of systems for applying ontologies is using them to develop semantic metadata for helping machine reasoning.

Background and Aim: Ontologies facilitate data integration, exchange, searching and querying. Open Biomedical Ontologies (OBO) Foundry is a solution for creating reference ontologies. In this foundry, the design of ontologies is based on established principles which allow for their interactions as a single system. The purpose of this study is to determine the main features of ontologies developed based on foundry principles. Materials and Methods: This descriptive cross-sectional study (2017) retrieved data about the ontology components, subject, language and tool from the OBO foundry website, and OntoBee (the default linked data server for the foundry ontologies). The frequency of classes, instances, Object Properties, DataType Properties and Annotation Properties are classified by the use of descriptive statistics. Results: The main subjects of 151 ontologies were Anatomy, health and Phenotype. Most languages and tools were, respectively, OBO and OBO-edit versions used for the development of ontologies. Five percent of ontologies contained more than 78977 classes, 150 object relations, 39 DataType relations, 110 annotation relations, and 356 instances. Conclusion: Increasing the number of ontologies developed based on OBO foundry principles as well as using OBO language and OBO-Edit is indicative of the fact that ontology developers have accepted the principles and tools.

Nowadays, standardized metadata for geospatial data is a key in sharing and finding information on the web and crucial in building Geospatial Data Infrastructure (GDI). The main objective of this paper was to develop a web-based metadata dissemination system for in-situ sensors based on, most importantly, interoperable, standard and open technologies introduced by Open GIS Consortium (OGC), namely Geography Markup Language (GML). In this research, at first a use case diagram was developed to demonstrate the user’s requirement. Then, an application XML schema based on user’s requirement was created. To build this schema, some GML schema documents (developed by Open GIS Consortium (OGC)) were imported into the application schema. System architecture was designed based on client/server model and a UML class diagram was also developed to present all classes and their attributes, operations and associations within the system. Implementation was conducted using GML, XML, XMLHTTP, DOM, ASP, and VBScript that brought out a web-network-based in-situ sensors metadata application. This application provided a user friendly interface to search and find sensor related information. Results showed that although GML and XML are powerful tools to build geo-metadata, it is important to note that GML document size may be a problem when dealing with huge amount of data.

Objective: The aim of this research is to conduct an analysis of qualitative and quantitative studies on applying thesauri to the construction and development of ontologies and the identification of subject domains. We will investigate the approaches and methods used in these studies.Method: This descriptive-analytical research was conducted following the seven stages of systematic review suggested by Petticrew and Roberts (2008). Data analysis and visualization were facilitated using the DatawRapper software.Results: The analysis of studies in the area of applying thesauri in the construction and development of ontologies, while identifying and presenting the subject trends of studies, frequency, methods, languages and approaches, showed that the studies in this area include six main topics as follows: applying thesauri in the construction and development of ontologies in connection with multilingual information retrieval, applying thesauri in the construction and development of ontologies to cover a specific subject domain, applying the ISO 25964 standard in the development of ontologies using thesauri, presenting the framework, methods and tools for the use of thesauri in construction and development of ontologies, improving semantic relations and concept mapping using thesauri in the construction and development of ontologies and review studies of thesauri conversion to ontologies. Conclusions: Various subject domains, across different time periods, have benefited from applying thesauri for the construction and development of ontologies. Thesauri, as semantic tools, have provided the context for organizing, retrieving and accessing information more accurately and easily for stakeholders and applicants across various domains. Despite these advancements, the lack of a standardized and consensual framework, coupled with the need to update methods, approaches, and tools due to the reliance on natural language processing (NLP) technologies and knowledge engineering, has necessitated further research to mature this field.

Ontology and social tagging, despite the differences they have with each other, are the new ways of organizing, representing and sharing knowledge in the electronic environment and can help promote each other. The aim of this research is to describe the relationships and applications of these two in conjunction with each other. The present study is written with a library and conceptual approach. Necessary information was gathered using the study of printed and electronic information resources available in libraries, the Internet, and Persian and English databases. Although the position of tags is in Web 2. 0 and the ontology position is in Semantic Web 2. 0, but we can use tags in the semantic web and ontologies in Web 2. 0. The use of ontology in Web 2. 0 causes creation of semantic structure and fixes its defects and weaknesses in organizing and retrieving that resulting from difficulties related to users, vocabulary as well as system weaknesses in the tagging in Web 2. 0. The use of tags in ontology, also, causes updating, making them more functional and accepting them in the user community. The lack or deficiency of these is due to the lack of attention paid to end users by ontology and also the literature and resources used to create ontologies are not up to date.

Purpose: Designing metadata ontology model for semantic representation of Theses by using the SPAR (Semantic Publishing and Referencing) Ontologies.Method: This study was an applied form and two methods were used, Content Analysis and mapping. The metadata of 69 theses and dissertations on the National Library and Archive of Iran in three Databases: 1) Digital Library of National Library and Archive of Iran. 2) Rasa Software and 3) Ganj in the Iranian Research Institute for Information Science and Technology were selected modified and completed by mapping. On the other hand, by analyzing the entities of each SPAR ontology and suggesting another entity to the researcher, the checklist was formed. This checklist included classes, properties, and individuals. At last, by entering them into Protégé software version 5.5, the model of metadata ontology, MdOntTDs, was drawn.Findings: Findings identified deficiencies in the existence of four important metadata elements (subject, supervisor, advisor, and abstract) in RASA and NLAI Digital Library. Among the 18 SPAR Ontologies, the most entities were selected from FaBiO, FRAPO, and CiTO respectively. All entities of BiDO, BiRO, C4O, Fivestar, FR, FRBR, PO, PRO, PSO, and PWO were suitable for theses. 195 individuals from 6 SPAR Ontologies, 292 individuals labeled with MdTDs from theses, and 100 individuals labeled with SUNMdTDs were selected by the researcher and entered into the software. 1558 entities categorized by class, Properties (object, data, and Annotation), and individuals along with the description and definition of each entity were placed in the software, in the form of hierarchical and determining axioms for classes. And specifying domain and range for relationships. Finally, the RDF graph was drawn using the OntoGraf plugin, and the final Model, MdOntTDs was developed. this research has proposed three new types of metadata: 1) Except for the existing keywords, topics have been categorized and modeled up to three levels including 4 main categories, 16 subcategories, and many units. Each of these final topics has been related to “hasSubject” and “isSubjectOf” properties. 2) The research methods of Theses that were connected with “hasMethod” and “used in” properties. 3) The papers taken from Theses were also searched, as far as possible, and were connected with “hasJournalArticle” and “journalArticleOf” properties.Conclusion: This model, if implemented, can overcome keyword search limitations, the problem of linking and Data sharing on the web, and the inconsistency of data. In the software, classes and their related individuals are visible in the form of a hierarchical network in RDF triples, and the connection between entities with increasing access points promises deeper semantic searches. However, due to the absence or lack of tagged and linked data, usage of the some of selected entities is not possible.

Objective: This paper aims to provide a comprehensive and systematic review of published studies on the topic of developing ontologies based on folksonomies as a means of information management in electronic environments. Method: This study is conducted using the systematic review method. After designating the questions, input, and output criteria, 87 papers published during 2003-2019 were obtained through querying domestic and international research databases. After screening the results, 29 papers (27 papers in English and 2 papers in Farsi) were closely studied and systematically analyzed. The data was entered into Excel for further statistical analysis and visualization. Findings: This study verifies the positive results of using folksonomized ontologies in central areas, including information management, and recovery and machine learning. The purpose of organizing knowledge is the quick transfer and retrieval of information. The inefficiency of traditional information organizing tools has always made it difficult to access information quickly and easily. The growth and development of information organization over time indicates a twoway relationship between knowledge growth and organizational evolution. This mutual influence between human knowledge and its organization has been accepted as a principle and its importance has increased over time. It seems that along with the increasing development of the world of knowledge, continuous review and improvement of organizational systems are inevitable. Moreover, this study shows the increasing popularity of folksonomized ontologies among users for determining semantic relationships between tags benefiting from more extensive sets of data. Furthermore, this study demonstrates that the synthesis between ontologies and folksonomies can facilitate semantic web development by leveraging their differences. An important factor in emphasizing the use of the tacit meanings of folksonomy is the high potential of folksonomy in facilitating the creation of semantic relationships. Conclusion: Although studies of the application of folksonomy in the development of ontologies have been conducted since 2003, semantic limitations in folksonomy have remained a challenging issue over last decades. However, the vast majority of user-generated folksonomies offer a promising future for semantic web development. Considering the significance of synthesizing folksonomies and ontologies in improving the semantic relationships in information systems and attending to users’,needs by obtaining useful data from tags, further studies are required to find effective solutions to the semantic ambiguities tags and to structure them. This study offers new perspectives to assist experts in the fields of information management and the semantic web.