Pub Date : 2022-01-01DOI: 10.5771/0943-7444-2022-6-411
Priscila Basto Fagundes, Douglas Dyllon, Jeronimo de Macedo
Some of the fundamental activities of the software development process are related to the discipline of Requirements Engineering. Their objectives are to discover, analyze, document, and verify the system’s requirements. The requirements are the conditions or capabilities that software needs to have or fulfill to meet its users’ needs, and problems in its identification can mean the failure of a software project. This study is part of the research that is being developed to propose a model based on Knowledge Organization Systems to be used in the Requirements engineering process. This article aims to present the results of an analysis on a set of Knowledge Organization Systems to identify whether they are likely to be applied in the Requirements engineering process and identify at which stage of this process each one of them can be implemented. The Knowledge Organization Systems analyzed were the authority files, gazetteers, glossaries, subject headings, classification systems, thesauri, semantic networks, and ontologies. Based on the results obtained, it was possible to conclude that the Knowledge Organization Systems analyzed can be used in the Requirements engineering process and, consequently, contribute to increasing the software requirements’ quality.
{"title":"An Analysis on the Use of Knowledge Organization Systems in the Process of Requirements Engineering","authors":"Priscila Basto Fagundes, Douglas Dyllon, Jeronimo de Macedo","doi":"10.5771/0943-7444-2022-6-411","DOIUrl":"https://doi.org/10.5771/0943-7444-2022-6-411","url":null,"abstract":"Some of the fundamental activities of the software development process are related to the discipline of Requirements Engineering. Their objectives are to discover, analyze, document, and verify the system’s requirements. The requirements are the conditions or capabilities that software needs to have or fulfill to meet its users’ needs, and problems in its identification can mean the failure of a software project. This study is part of the research that is being developed to propose a model based on Knowledge Organization Systems to be used in the Requirements engineering process. This article aims to present the results of an analysis on a set of Knowledge Organization Systems to identify whether they are likely to be applied in the Requirements engineering process and identify at which stage of this process each one of them can be implemented. The Knowledge Organization Systems analyzed were the authority files, gazetteers, glossaries, subject headings, classification systems, thesauri, semantic networks, and ontologies. Based on the results obtained, it was possible to conclude that the Knowledge Organization Systems analyzed can be used in the Requirements engineering process and, consequently, contribute to increasing the software requirements’ quality.","PeriodicalId":46091,"journal":{"name":"Knowledge Organization","volume":"1 1","pages":""},"PeriodicalIF":0.7,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70901812","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-01-01DOI: 10.5771/0943-7444-2022-1-3
R. Fugmann
{"title":"What is Information? An Information Veteran Looks Back","authors":"R. Fugmann","doi":"10.5771/0943-7444-2022-1-3","DOIUrl":"https://doi.org/10.5771/0943-7444-2022-1-3","url":null,"abstract":"","PeriodicalId":46091,"journal":{"name":"Knowledge Organization","volume":"1 1","pages":""},"PeriodicalIF":0.7,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70900222","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-01-01DOI: 10.5771/0943-7444-2022-1-22
Zhangchao Li, Lin He, Dan Gao
Against the background that the top-level semantic framework of Chinese traditional culture is not comprehensive and unified, this study aims to preserve and disseminate cultural heritage information about Chinese traditional culture through the development of a domain ontology which is constructed from ancient books. A combination of top-down and bottom-up approaches was used to construct the ontology for Chinese traditional culture (CTCO). An investigation of historians’ needs, and LDA topic clustering model were conducted, understanding the specific needs of historians, collecting the topic, concepts and relationships. CIDOC CRM was reused to construct the basic framework of CTCO. Ontology structure and function were adopted to evaluate the effectiveness of CTCO. Evaluation results show that the ontology meets all the quality criteria of OntoMetrics, and the experts agreed on content representation (average score = 4.30). CTCO contributes to the organization of traditional Chinese culture and the construction of related databases. The study also forms a common path and puts forward proposals for the construction of domain ontology, which has great social relevance.
{"title":"Ontology Construction and Evaluation for Chinese Traditional Culture: Towards Digital Humanity","authors":"Zhangchao Li, Lin He, Dan Gao","doi":"10.5771/0943-7444-2022-1-22","DOIUrl":"https://doi.org/10.5771/0943-7444-2022-1-22","url":null,"abstract":"Against the background that the top-level semantic framework of Chinese traditional culture is not comprehensive and unified, this study aims to preserve and disseminate cultural heritage information about Chinese traditional culture through the development of a domain ontology which is constructed from ancient books. A combination of top-down and bottom-up approaches was used to construct the ontology for Chinese traditional culture (CTCO). An investigation of historians’ needs, and LDA topic clustering model were conducted, understanding the specific needs of historians, collecting the topic, concepts and relationships. CIDOC CRM was reused to construct the basic framework of CTCO. Ontology structure and function were adopted to evaluate the effectiveness of CTCO. Evaluation results show that the ontology meets all the quality criteria of OntoMetrics, and the experts agreed on content representation (average score = 4.30). CTCO contributes to the organization of traditional Chinese culture and the construction of related databases. The study also forms a common path and puts forward proposals for the construction of domain ontology, which has great social relevance.","PeriodicalId":46091,"journal":{"name":"Knowledge Organization","volume":"1 1","pages":""},"PeriodicalIF":0.7,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70900140","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-01-01DOI: 10.5771/0943-7444-2022-4-236
B. Sterner, Atriya Sen, J. Witteveen
Consensus about a classification is defined as agreement on a set of classes (concepts or categories) and their relations (such as generic relations and whole-part relations) for us in forming beliefs. While most research on scientific consensus has focused on consensus about a belief as a mark of truth, we highlight the importance of consensus in justifying shared classificatory language. What sort of consensus, if any, is the best basis for communicating and reasoning with scientific classifications? We describe an often-overlooked coordinative role for consensus that leverage agreement on how to disagree such that actors involved can still achieve one or more shared aims even when they do not agree on shared beliefs or categories. Looking forward, we suggest that investigating structures and methods for coordinative consensus provides an important new direction for research on the epistemic foundations of knowledge organization.
{"title":"Consensus and Scientific Classification","authors":"B. Sterner, Atriya Sen, J. Witteveen","doi":"10.5771/0943-7444-2022-4-236","DOIUrl":"https://doi.org/10.5771/0943-7444-2022-4-236","url":null,"abstract":"Consensus about a classification is defined as agreement on a set of classes (concepts or categories) and their relations (such as generic relations and whole-part relations) for us in forming beliefs. While most research on scientific consensus has focused on consensus about a belief as a mark of truth, we highlight the importance of consensus in justifying shared classificatory language. What sort of consensus, if any, is the best basis for communicating and reasoning with scientific classifications? We describe an often-overlooked coordinative role for consensus that leverage agreement on how to disagree such that actors involved can still achieve one or more shared aims even when they do not agree on shared beliefs or categories. Looking forward, we suggest that investigating structures and methods for coordinative consensus provides an important new direction for research on the epistemic foundations of knowledge organization.","PeriodicalId":46091,"journal":{"name":"Knowledge Organization","volume":"16 1","pages":""},"PeriodicalIF":0.7,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70901049","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-01-01DOI: 10.5771/0943-7444-2022-5-371
Arthur C. Smith
SKOS (Simple Knowledge Organization System) is a recommendation from the World Wide Web Consortium (W3C) for representing controlled vocabularies, taxonomies, thesauri, classifications, and similar systems for organizing and indexing information as linked data elements in the Semantic Web, using the Resource Description Framework (RDF). The SKOS data model is centered on “concepts”, which can have preferred and alternate labels in any language as well as other metadata, and which are identified by addresses on the World Wide Web (URIs). Concepts are grouped into hierarchies through “broader” and “narrower” relations, with “top concepts” at the broadest conceptual level. Concepts are also organized into “concept schemes”, also identified by URIs. Other relations, mappings, and groupings are also supported. This article discusses the history of the development of SKOS and provides notes on adoption, uses, and limitations.
{"title":"Simple Knowledge Organization System (SKOS)","authors":"Arthur C. Smith","doi":"10.5771/0943-7444-2022-5-371","DOIUrl":"https://doi.org/10.5771/0943-7444-2022-5-371","url":null,"abstract":"SKOS (Simple Knowledge Organization System) is a recommendation from the World Wide Web Consortium (W3C) for representing controlled vocabularies, taxonomies, thesauri, classifications, and similar systems for organizing and indexing information as linked data elements in the Semantic Web, using the Resource Description Framework (RDF). The SKOS data model is centered on “concepts”, which can have preferred and alternate labels in any language as well as other metadata, and which are identified by addresses on the World Wide Web (URIs). Concepts are grouped into hierarchies through “broader” and “narrower” relations, with “top concepts” at the broadest conceptual level. Concepts are also organized into “concept schemes”, also identified by URIs. Other relations, mappings, and groupings are also supported. This article discusses the history of the development of SKOS and provides notes on adoption, uses, and limitations.","PeriodicalId":46091,"journal":{"name":"Knowledge Organization","volume":"1 1","pages":""},"PeriodicalIF":0.7,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70901616","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-01-01DOI: 10.5771/0943-7444-2022-8-563
Susmita Bardhan, Biswanath Dutta
In the process of searching for a particular course on e-learning platforms, it is required to browse through different platforms, and it becomes a time-consuming process. To resolve the issue, an ontology has been developed that can provide single-point access to all the e-learning platforms. The modelled ONline Course Ontology (ONCO) is based on YAMO, METHONTOLOGY and IDEF5 and built on the Protégé ontology editing tool. ONCO is integrated with sample data and later evaluated using pre-defined competency questions. Complex SPARQL queries are executed to identify the effectiveness of the constructed ontology. The modelled ontology is able to retrieve all the sampled queries. The ONCO has been developed for the efficient retrieval of similar courses from massive open online course (MOOC) platforms.
{"title":"ONCO: An Ontology Model for MOOC Platforms","authors":"Susmita Bardhan, Biswanath Dutta","doi":"10.5771/0943-7444-2022-8-563","DOIUrl":"https://doi.org/10.5771/0943-7444-2022-8-563","url":null,"abstract":"In the process of searching for a particular course on e-learning platforms, it is required to browse through different platforms, and it becomes a time-consuming process. To resolve the issue, an ontology has been developed that can provide single-point access to all the e-learning platforms. The modelled ONline Course Ontology (ONCO) is based on YAMO, METHONTOLOGY and IDEF5 and built on the Protégé ontology editing tool. ONCO is integrated with sample data and later evaluated using pre-defined competency questions. Complex SPARQL queries are executed to identify the effectiveness of the constructed ontology. The modelled ontology is able to retrieve all the sampled queries. The ONCO has been developed for the efficient retrieval of similar courses from massive open online course (MOOC) platforms.","PeriodicalId":46091,"journal":{"name":"Knowledge Organization","volume":"1 1","pages":""},"PeriodicalIF":0.7,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70901523","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-01-01DOI: 10.5771/0943-7444-2022-4-213
Ningyuan Song, Hanghang Cheng, Huimin Zhou, Xiaoguang Wang
In this study, we propose a way to link the scholarly contents of scientific papers by constructing a knowledge graph based on the semantic organization of argumentation units and relations in scientific papers. We carried out an argumentation graph data model aimed at linking multiple discourses, and also developed a semantic annotation platform for scientific papers and an argumentation graph visualization system. A construction experiment was performed using 12 articles. The final argumentation graph has 1,262 nodes and 1,628 edges, including 1,628 intra-article relations and 190 inter-article relations. Knowledge evolution representation, strategic reading, and automatic abstracting use cases are presented to demonstrate the application of the argumentation graph. In contrast to existing knowledge graphs used in academic fields, the argumentation graph better supports the organization and representation of scientific paper content and can be used as data infrastructure in scientific knowledge retrieval, reorganization, reasoning, and evolution. Moreover, it supports automatic abstract and strategic reading.
{"title":"Linking Scholarly Contents: The Design and Construction of an Argumentation Graph","authors":"Ningyuan Song, Hanghang Cheng, Huimin Zhou, Xiaoguang Wang","doi":"10.5771/0943-7444-2022-4-213","DOIUrl":"https://doi.org/10.5771/0943-7444-2022-4-213","url":null,"abstract":"In this study, we propose a way to link the scholarly contents of scientific papers by constructing a knowledge graph based on the semantic organization of argumentation units and relations in scientific papers. We carried out an argumentation graph data model aimed at linking multiple discourses, and also developed a semantic annotation platform for scientific papers and an argumentation graph visualization system. A construction experiment was performed using 12 articles. The final argumentation graph has 1,262 nodes and 1,628 edges, including 1,628 intra-article relations and 190 inter-article relations. Knowledge evolution representation, strategic reading, and automatic abstracting use cases are presented to demonstrate the application of the argumentation graph. In contrast to existing knowledge graphs used in academic fields, the argumentation graph better supports the organization and representation of scientific paper content and can be used as data infrastructure in scientific knowledge retrieval, reorganization, reasoning, and evolution. Moreover, it supports automatic abstract and strategic reading.","PeriodicalId":46091,"journal":{"name":"Knowledge Organization","volume":"1 1","pages":""},"PeriodicalIF":0.7,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70900662","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-01-01DOI: 10.5771/0943-7444-2022-4-257
R. Szostak, Deborah Lee
We investigate how the Basic Concepts Classification (BCC) can best incorporate schedules addressing musical form, genre, and type. We show that the synthetic possibilities within the BCC facilitate the classification of form/genre/type. In particular, many challenges identified in the literature on musical classification are addressed. The BCC also serves to make evident various connections between music and other schedules in BCC.
{"title":"Classifying Musical Genres. Building Musical Form and Genre into BCC: Repurposing LCGFT Terms for Music into the Basic Concepts Classification","authors":"R. Szostak, Deborah Lee","doi":"10.5771/0943-7444-2022-4-257","DOIUrl":"https://doi.org/10.5771/0943-7444-2022-4-257","url":null,"abstract":"We investigate how the Basic Concepts Classification (BCC) can best incorporate schedules addressing musical form, genre, and type. We show that the synthetic possibilities within the BCC facilitate the classification of form/genre/type. In particular, many challenges identified in the literature on musical classification are addressed. The BCC also serves to make evident various connections between music and other schedules in BCC.","PeriodicalId":46091,"journal":{"name":"Knowledge Organization","volume":"1 1","pages":""},"PeriodicalIF":0.7,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70901172","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-01-01DOI: 10.5771/0943-7444-2022-7-483
Jing Xiong, Tao Guo, Guoying Liu, Yining Chen
Oracle Bone Studies (OBS) benefit a lot from the introduction of computer science and artificial intelligence (AI), which changes the traditional way of organization of OBS knowledge, and results in a rapid accumulation of important research data. However, these data are not fully explored, and the processing faces challenges in the storage, representation, sharing and reuse of OBS big data, due to the lack of knowledge organization and management tools and knowledge application models for OBS. To address the two outstanding problems faced by OBS research bottleneck: high dependence on expert knowledge but low degree of knowledge sharing and reuse; poor computability and interpretability due to qualitative analysis. A new knowledge organization model carved from multiple dimensions such as refinement, fragmentation, conceptualization, networking, vectorization, and multimodal fusion is proposed. The OBS Knowledge application Pyramid (OBSKP) model is proposed from the perspective of Computational Oracle Bone Studies (COBS). The OBSKP shows the direction for the OBS research in the era of AI and provides the storage and representation standards and specifications for the subsequent OBS research data. Moreover, several important applications based on the OBSKP are presented.
{"title":"OBSKP: Oracle Bone Studies Knowledge Pyramid Model With Applications","authors":"Jing Xiong, Tao Guo, Guoying Liu, Yining Chen","doi":"10.5771/0943-7444-2022-7-483","DOIUrl":"https://doi.org/10.5771/0943-7444-2022-7-483","url":null,"abstract":"Oracle Bone Studies (OBS) benefit a lot from the introduction of computer science and artificial intelligence (AI), which changes the traditional way of organization of OBS knowledge, and results in a rapid accumulation of important research data. However, these data are not fully explored, and the processing faces challenges in the storage, representation, sharing and reuse of OBS big data, due to the lack of knowledge organization and management tools and knowledge application models for OBS. To address the two outstanding problems faced by OBS research bottleneck: high dependence on expert knowledge but low degree of knowledge sharing and reuse; poor computability and interpretability due to qualitative analysis. A new knowledge organization model carved from multiple dimensions such as refinement, fragmentation, conceptualization, networking, vectorization, and multimodal fusion is proposed. The OBS Knowledge application Pyramid (OBSKP) model is proposed from the perspective of Computational Oracle Bone Studies (COBS). The OBSKP shows the direction for the OBS research in the era of AI and provides the storage and representation standards and specifications for the subsequent OBS research data. Moreover, several important applications based on the OBSKP are presented.","PeriodicalId":46091,"journal":{"name":"Knowledge Organization","volume":"62 1","pages":""},"PeriodicalIF":0.7,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70901404","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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