PurposeThis work provides a generic review of the existing data mining ontologies (DMOs) and also provides a base platform for ontology developers and researchers for gauging the ontologies for satisfactory coverage and usage.Design/methodology/approachThe study uses a systematic literature review approach to identify 35 DMOs in the domain between the years 2003 and 2021. Various parameters, like purpose, design methodology, operations used, language representation, etc. are available in the literature to review ontologies. Accompanying the existing parameters, a few parameters, like semantic reasoner used, knowledge representation formalism was added and a list of 20 parameters was prepared. It was then segregated into two groups as generic parameters and core parameters to review DMOs.FindingsIt was observed that among the 35 papers under the study, 26 papers were published between the years 2006 and 2016. Larisa Soldatova, Saso Dzeroski and Pance Panov were the most productive authors of these DMO-related publications. The ontological review indicated that most of the DMOs were domain and task ontologies. Majority of ontologies were formal, modular and represented using web ontology language (OWL). The data revealed that Ontology development 101, METHONTOLOGY was the preferred design methodology, and application-based approaches were preferred for evaluation. It was also observed that around eight ontologies were accessible, and among them, three were available in ontology libraries as well. The most reused ontologies were OntoDM, BFO, OBO-RO, OBI, IAO, OntoDT, SWO and DMOP. The most preferred ontology editor was Protégé, whereas the most used semantic reasoner was Pellet. Even ontology metrics for 16 DMOs were also available.Originality/valueThis paper carries out a basic level review of DMOs employing a parametric approach, which makes this study the first of a kind for the review of DMOs.
In the original publication of the article the author name Ashaq Hussain Najar and the affiliation for authors Tariq Ahmad Shah and Ashaq Hussain Najar were incorrectly displayed. These have been correction with this Correction.Also, in the first line of the last para of the Conclusion section, the sentence, "Furthermore, the study was based on0020a…" should read as "Furthermore, the study was based on a…".The original article has been corrected.
Purpose:The Covid-19 pandemic has significantly impacted world healthcare, with ophthalmology being one of the most severely affected area. The study aims to perform a bibliometric analysis of global literature published on "Ophthalmic Manifestations of Covid-19" to explore the scientific productivity and trends in research in this field. Methods: Bibliometric methods have been used to analyze global literature on this topic using quantitatively and qualitatively indices from the Scopus database up to 20 th September 2021. The keywords related to "Covid-19" and "ophthalmology" are used in search strategy through the boolean operator. Primary data were exported in CSV and BibTxt file format for further analysis using different software. The literature on "Ophthalmic Manifestations of Covid-19" was assessed using a variety of metrics. Results: A total of 3453 publications were published on "Ophthalmic Manifestations of Covid-19" , which received 32935 citations, averaging 9.54 citations per paper. Of the total publications, 557 received external funding support and registered 10802 citations. The U.S.A. and India published the most significant number of papers among countries. The U.S.A. and U.K. occupied the top position in international collaborative publications. Medicine and Neurosciences were the most productive areas. The Indian Journal of Ophthalmology is the most productive source. A total of 46 high-cited papers have been identified on this topic, which are published in 35 journals, with the U.S.A. contributing the most papers. Conclusion: In this study, the bibliometric assessment presents a quantitative and qualitative matrix of research in the field "Ophthalmic Manifestations of Covid-19" . The study gives proof of the enhanced global collaboration that global researchers have created in order to combat the epidemic. The authors have used various bibliometric metrics and tools to present this study efficiently. This study will be helpful for the scholars who were researching in this field.
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