DC FieldValueLanguage
dc.contributor.authorPapadakis, Ioannis-
dc.contributor.authorChaleplioglou, Artemis-
dc.contributor.authorPapavlasopoulos, Sozon-
dc.date.accessioned2023-10-23T11:57:45Z-
dc.date.available2023-10-23T11:57:45Z-
dc.date.issued2019-02-25-
dc.identifiergoogle_scholar-SzSNM_QAAAAJ:LkGwnXOMwfcC-
dc.identifier.issn2241-1925-
dc.identifier.otherSzSNM_QAAAAJ:LkGwnXOMwfcC-
dc.identifier.urihttps://uniwacris.uniwa.gr/handle/3000/584-
dc.description.abstractThe advances in data management technologies lead to the transformation of biosciences into Big Data disciplines. Traditional and digital biomedical libraries utilize modern tools to support both teaching and learning of biosciences in all levels of education, from primary school to doctoral educational environment. Herein, we will describe the Semantic web technologies and services in the setting of biological and educational linked data. In particular, we will discuss the different types of open access web data and the challenges of volume, variability and complexity in their analyses. Currently, the use of distinct ontologies for biosciences and education represents a major problem in biomedical teaching. Their compilation and assembly is a priority for integrated functionality. The accessibility needs and preferences of biomedical students differ between traditional and e-learning contexts, while different existing and experimental virtual learning solutions have been proposed. From the Semantic web point of view the information should be organized and structured to produce curated metadata, linking different data sets into aggregated semantic LIS services. Such systems will facilitate the rapid retrieval and validation of biological data for educational purposes, building e-textbooks from open resources and shortening the information from multiple resources towards knowledge discovery, available for all teachers, students, doctoral fellows and residents. However, the developing Semantic web services need continuously evaluation and monitoring, since drawbacks arise in data retrieval and result errors because of information import from external datasets. To overcome the limitations of intelligent processing, we should focus in the accuracy and expressiveness of an integrated biomedical education ontology.en_US
dc.language.isoenen_US
dc.relation.ispartofQualitative and Quantitative Methods in Librariesen_US
dc.source10th Qualitative and Quantitative Methods in Libraries -International …, 2018-
dc.subjectSemantic weben_US
dc.subjectOntologiesen_US
dc.subjectLinked dataen_US
dc.subjectE-learningen_US
dc.titleNew LIS Technologies and Services in Biosciences Educationen_US
dc.typeConference Paperen_US
dc.relation.conference10th Qualitative and Quantitative Methods in Libraries (QQML), 22-25 May 2018, Chania, Greeceen_US
dc.relation.deptDepartment of Archival, Library and Information Studiesen_US
dc.relation.facultySchool of Administrative, Economics and Social Sciencesen_US
dc.relation.volume7en_US
dc.relation.issue2en_US
dc.identifier.spage233en_US
dc.identifier.epage243en_US
dc.linkhttp://qqml-journal.net/index.php/qqml/article/view/472en_US
dc.collaborationUniversity of West Attica (UNIWA)en_US
dc.subject.fieldSocial Sciencesen_US
dc.journalsOpen Accessen_US
dc.publicationPeer Revieweden_US
dc.countryGreeceen_US
item.cerifentitytypePublications-
item.languageiso639-1en-
item.openairetypeConference Paper-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.fulltextNo Fulltext-
item.grantfulltextnone-
crisitem.author.deptDepartment of Archival, Library and Information Studies-
crisitem.author.facultySchool of Administrative, Economics and Social Sciences-
crisitem.author.orcid0000-0002-6519-7428-
crisitem.author.parentorgSchool of Administrative, Economics and Social Sciences-
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