{"title":"Citation content/context data as a source for research cooperation analysis","authors":"S. Parinov, V. Antonova","doi":"10.1504/IJMSO.2020.10030300","DOIUrl":"https://doi.org/10.1504/IJMSO.2020.10030300","url":null,"abstract":"Using citation relationships, one can build three groups of papers: (1) the papers of a selected author; (2) those papers cited by the author; (3) papers citing the author. Authors of papers from these three groups can be presented as a fragment of a research cooperation network, because they use/cite research outputs of each other. Their papers' full texts and especially the contexts of their in-text citations contain some information about the character of this research cooperation. We present a concept of research cooperation, based on publications and the current results of the Cirtec project for building the research cooperation characteristics. This work is based on the processing of citation content/context data. The results include an on-line service for authors to monitor the citation content data extractions and three types of built indicators/parameters: co-citation statistics, spatial distribution of citations over papers' body and topic models for citation contexts.","PeriodicalId":111629,"journal":{"name":"Int. J. Metadata Semant. Ontologies","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127395835","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Intermediary XML schemas: constraint, templating and interoperability in complex environments","authors":"R. Gartner","doi":"10.1504/ijmso.2020.10030292","DOIUrl":"https://doi.org/10.1504/ijmso.2020.10030292","url":null,"abstract":"The methodology of intermediary XML schemas is introduced and its application to complex metadata environments is explored. Intermediary schemas are designed to mediate to other ‘referent’ schemas: instances conforming to these are not generally intended for dissemination but must usually be realized by XSLT transformations for delivery. In some cases, these schemas may also generate instances conforming to themselves. Three subsidiary methods of this methodology are introduced. The first is application-specific schemas that act as intermediaries to established schemas which are problematic by virtue of their over-complexity or flexibility. The second employs the METS packaging standard as a template for navigating instances of a complex schema by defining an abstract map of its instances. The third employs the METS structural map to define templates or conceptual models from which instances of metadata for complex applications may be realized by XSLT transformations. The first method is placed in the context of earlier approaches to semantic interoperability such as crosswalks, switching across, derivation and application profiles. The second is discussed in the context of such methods for mapping complex objects as OAI-ORE and the Fedora Content Model Architecture. The third is examined in relation to earlier approaches to templating within XML architectures. The relevance of these methods to contemporary research is discussed in three areas: digital ecosystems, archival description and Linked Open Data in digital asset management and preservation. Their relevance to future research is discussed in the form of suggested enhancements to each, a possible synthesis of the second and third to overcome possible problems of interoperability presented by the first, and their potential role in future developments in digital preservation. This methodology offers an original approach to resolving issues of interoperability and the management of complex metadata environments; it significantly extends earlier techniques and does so entirely within XML architectures.","PeriodicalId":111629,"journal":{"name":"Int. J. Metadata Semant. Ontologies","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129854277","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Service traceability in SOA-based software systems: a traceability network add-in for BPAOntoSOA framework","authors":"Rana Yousef, Sarah Imtera","doi":"10.1504/ijmso.2020.10030302","DOIUrl":"https://doi.org/10.1504/ijmso.2020.10030302","url":null,"abstract":"BPAOntoSOA is a generic framework that generates a service model from a given organisational business process architecture. Service Oriented Architecture (SOA) traceability is essentially important to facilitate change management and support reusability of an SOA; it has a wide application in the development and maintenance process. Such a traceability network is not available for BPAOntoSOA framework. This paper introduces an ontology-based traceability network for BPAOntoSOA framework that semantically generates trace links between services and business process architectural elements in both forward and backward directions. The proposed traceability approach was evaluated using the postgraduate faculty information system case study in order to assess the framework behaviour in general. As a continued evaluation effort, a group of parameters have been selected to create an evaluation criterion, which was used to compare the BPAOntoSOA trace solution to one of the most related traceability frameworks, STraS traceability framework.","PeriodicalId":111629,"journal":{"name":"Int. J. Metadata Semant. Ontologies","volume":"89 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125728463","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Unique challenges facing Linked Data implementation for National Educational Television","authors":"Chris Pierce","doi":"10.1504/ijmso.2020.10030295","DOIUrl":"https://doi.org/10.1504/ijmso.2020.10030295","url":null,"abstract":"Implementing Linked Data involves a costly process of converting metadata into an exchange format substantially different from traditional library \"records-based\" exchange. To achieve full implementation, it is necessary to navigate a complex process of data modelling, crosswalking, and publishing. This paper documents the transition of a data set of National Educational Television (NET) collection records to a \"data-based\" exchange environment of Linked Data by discussing challenges faced during the conversion. These challenges include silos like the Library's media asset management system Merged Audio-Visual Information System (MAVIS), aligning PBCore with the bibliographic Linked Data model BIBFRAME, modelling differences in works between archival moving image cataloguing and other domains using Entertainment Identifier Registry IDs (EIDR IDs), and possible alignments with EBUCore (the European Broadcasting Union Linked Data model) to address gaps between PBCore and BIBFRAME.","PeriodicalId":111629,"journal":{"name":"Int. J. Metadata Semant. Ontologies","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133462262","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Extending the GLOBDEF framework with support for semantic enhancement of various data formats","authors":"Maria Nisheva-Pavlova, A. Alexandrov","doi":"10.1504/ijmso.2020.10030301","DOIUrl":"https://doi.org/10.1504/ijmso.2020.10030301","url":null,"abstract":"Semantic enhancement links sections of data files with well-described concepts from some knowledge domain. This allows for further automated reasoning about that data and can be especially useful for extracting value from Big Data. Most of the available enhancement tools focus on specific enhancement needs and data types. In this paper we present our efforts to expand the GLOBDEF framework, introduced in an earlier work, which aims to find a way for processing of large amounts of data and enhancing the data automatically. The framework is designed to leverage a variety of external enhancement tools and has no limitations on the format of the enhanced data. We demonstrate how the framework behaves on a mixed data set of texts and images and explain how an image can be semantically enhanced with a simple automated combination of an object recogniser and a text-based automated enhancer.","PeriodicalId":111629,"journal":{"name":"Int. J. Metadata Semant. Ontologies","volume":"67 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134517791","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Layout logical labelling and finding the semantic relationships between citing and cited paper content","authors":"S. Parinov, Amir Bakarov, Daniil Vodolazcky","doi":"10.1504/ijmso.2020.10030006","DOIUrl":"https://doi.org/10.1504/ijmso.2020.10030006","url":null,"abstract":"Currently, large data sets of in-text citations and citation contexts are becoming available for research and developing tools. Using the \"topic model\" method to analyse these data, one can characterise thematic relationships between citation contexts from citing and the cited paper content. However, to build relevant topic models and to compare them accurately for papers linked by citation relationships we have to know the semantic labels of PDF papers' layout such as section titles, paragraph boundaries, etc. Recent achievements in papers' conversion from a PDF form into a rich attributed JSON format allow us to develop new approaches for the logical labelling of the papers' layout. This paper presents a re-usable method and open source software for the logical labelling of PDF papers, which gave good quality of a layout element's recognition for a set of research papers. Using these semantic labels we made a precise comparison of topic models built for citing and cited papers and we found some level of similarity between them.","PeriodicalId":111629,"journal":{"name":"Int. J. Metadata Semant. Ontologies","volume":"72 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127596529","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Runumi Devi, D. Mehrotra, Hajer Baazaoui Zghal, Ghada Besbes
{"title":"SWRL reasoning on ontology-based clinical dengue knowledge base","authors":"Runumi Devi, D. Mehrotra, Hajer Baazaoui Zghal, Ghada Besbes","doi":"10.1504/ijmso.2020.10030005","DOIUrl":"https://doi.org/10.1504/ijmso.2020.10030005","url":null,"abstract":"Dengue is a widespread mosquito-borne viral illness that may lead to death if not treated timely and properly. The aim of this study is to propose a semantic rule-based modelling and reasoning approach directed towards formalising dengue disease definition in conjunction with operational definitions (semantics) that support clinical and diagnostic reasoning. The operational definitions are incorporated using Semantic Web Rule Language (SWRL) as logical rules that enhance the expressive capability of the knowledge base. A dengue knowledge base has been designed which is extended with International Classification of Diseases (ICD) ontology for associating dengue fever with ICD code. The knowledge base created can be reasoned upon for diagnostic classification that can discover dengue symptoms and predict the possibility of patients to suffer from the disease apart from offering interoperability. 153 real patient cases are classified successfully against the operational definitions incorporated by SWRL rules.","PeriodicalId":111629,"journal":{"name":"Int. J. Metadata Semant. Ontologies","volume":"201 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115697479","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Semantic architectures and dashboard creation processes within the data and analytics framework","authors":"Michele Petito, F. Fallucchi, E. W. D. Luca","doi":"10.1504/ijmso.2020.10030002","DOIUrl":"https://doi.org/10.1504/ijmso.2020.10030002","url":null,"abstract":"The open data tools currently on the market do not exploit the semantic web, or provide tools for data analysis and visualisation. Most of them are simple open data portals that display a data catalogue, often not even fulfilling the lowest level of the famous five-star model. The Data and Analytics Framework (DAF), a project run by the Italian government, is enabled to extract knowledge from the immense amount of data owned by the State. It favours the spread of Linked Open Data thanks to the integration of the network of controlled ontologies and vocabularies (OntoPiA). The research outlined in this paper illustrates some of the platform's competitive solutions and introduces the five-step process to create a DAF dashboard, as well as the related data story. The case study created by the authors concerns tourism in Sardinia and represents one of the few demonstrations of a real case being tested in DAF.","PeriodicalId":111629,"journal":{"name":"Int. J. Metadata Semant. Ontologies","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128494145","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Eleftherios Kalogeros, M. Gergatsoulis, M. Damigos
{"title":"Document-based RDF storage method for parallel evaluation of basic graph pattern queries","authors":"Eleftherios Kalogeros, M. Gergatsoulis, M. Damigos","doi":"10.1504/ijmso.2020.10030007","DOIUrl":"https://doi.org/10.1504/ijmso.2020.10030007","url":null,"abstract":"In this paper, we investigate the problem of efficiently evaluating (Basic Graph Pattern) BGP SPARQL queries over a large amount of RDF data. We propose an effective data model for storing RDF data in a document database using maximum replication factor of 2 (i.e., in the worst case scenario, the data graph will be doubled in storage size). The proposed storage model is utilised for efficiently evaluating SPARQL queries, in a distributed manner. Each query is decomposed into a set of generalised star queries, which are queries that allow both subject-object and object-subject edges from a specific node, called central node. The proposed data model ensures that no joining operations over multiple data sets are required to evaluate generalised star queries. The results of the evaluation of the generalised star sub-queries of a query Q are then combined properly, in order to compute the answers of the query Q posed over the RDF data. The proposed approach has been implemented using MongoDB and Apache Spark.","PeriodicalId":111629,"journal":{"name":"Int. J. Metadata Semant. Ontologies","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115388489","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
G. O. M. D. Silva, Paulo Roberto de Souza, F. Durão
{"title":"HSLD: a hybrid similarity measure for linked data resources","authors":"G. O. M. D. Silva, Paulo Roberto de Souza, F. Durão","doi":"10.1504/ijmso.2020.10030003","DOIUrl":"https://doi.org/10.1504/ijmso.2020.10030003","url":null,"abstract":"The web of data is a set of deeply linked resources that can be instantly read and understood by both humans and machines. A vast amount of RDF data has been published in freely accessible and interconnected data sets creating the so-called Linked Open Data cloud. Such a huge amount of data available along with the development of semantic web standards has opened up opportunities for the development of semantic applications. However, most of the semantic recommender systems use only the link structure between resources to calculate the similarity between resources. In this paper we propose HSLD, a hybrid similarity measure for Linked Data that exploits information present in RDF literals besides the links between resources. We evaluate the proposed approach in the context of a LOD-based Recommender System using data from DBpedia. Experiment results indicate that HSLD increases the precision of the recommendations in comparison to pure link-based baseline methods.","PeriodicalId":111629,"journal":{"name":"Int. J. Metadata Semant. Ontologies","volume":"17 14","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131747335","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}