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1.
EOSC interoperability framework : Report from the EOSC Executive Board Working Groups FAIR and Architecture
Oscar Corcho, Magnus Eriksson, Krzysztof Kurowski, Milan Ojsteršek, Christine Choirat, Mark van de Sanden, Frederik Coppens, 2021, znanstvena monografija

Opis: This document has been developed by the Interoperability Task Force of the EOSC Executive Board FAIR Working Group, with participation from the Architecture WG. Achieving interoperability within EOSC is essential in order for the federation of services that will compose EOSC to provide added value for service users. In the context of the FAIR principles, interoperability is discussed in relation to the fact that “research data usually need to be integrated with other data; in addition, the data need to interoperate with applications or workflows for analysis, storage, and processing”. Our view on interoperability does not only consider data but also the many other research artefacts that may be used in the context of research activity, such as software code, scientific workflows, laboratory protocols, open hardware designs, etc. It also considers the need to make services and e-infrastructures as interoperable as possible. This document identifies the general principles that should drive the creation of the EOSC Interoperability Framework (EOSC IF), and organises them into the four layers that are commonly considered in other interoperability frameworks (e.g., the European Interoperability Framework - EIF): technical, semantic, organisational and legal interoperability. For each of these layers, a catalogue of problems and needs, as well as challenges and high-level recommendations have been proposed, which should be considered in the further development and implementation of the EOSC IF components. Such requirements and recommendations have been developed after an extensive review of related literature as well as by running interviews with stakeholders from ERICs (European Research Infrastructure Consortia), ESFRI (European Strategy Forum on Research Infrastructures) projects, service providers and research communities. Some examples of such requirements are: “every semantic artefact that is being maintained in EOSC must have sufficient associated documentation, with clear examples of usage and conceptual diagrams”, or “Coarse-grained and fine-grained dataset (and other research object) search tools need to be made available”, etc. The document finally contains a proposal for the management of FAIR Digital Objects in the context of EOSC and a reference architecture for the EOSC Interoperability Framework that is inspired by and extends the European Interoperability Reference Architecture (EIRA), identifying the main building blocks required.
Ključne besede: technical interoperability, semantic interoperability, organizational interoperability, legal interoperability, EOSC, metadata crosswalk, reference architecture
Objavljeno v DKUM: 21.09.2021; Ogledov: 455; Prenosov: 24
.pdf Celotno besedilo (1,06 MB)
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2.
Crosswalk of most used metadata schemes and guidelines for metadata interoperability (Version 1.0)
Milan Ojsteršek, 2021, zaključena znanstvena zbirka podatkov ali korpus

Opis: This resource provides crosswalks among the most commonly used metadata schemes and guidelines to describe digital objects in Open Science, including: - RDA metadata IG recommendation of the metadata element set, - EOSC Pilot - EDMI metadata set, - Dublin CORE Metadata Terms, - Datacite 4.3 metadata schema, - DCAT 2.0 metadata schema and DCAT 2.0 application profile, - EUDAT B2Find metadata recommendation, - OpenAIRE Guidelines for Data Archives, - OpenAire Guidelines for literature repositories 4.0, - OpenAIRE Guidelines for Other Research Products, - OpenAIRE Guidelines for Software Repository Managers, - OpenAIRE Guidelines for CRIS Managers, - Crossref 4.4.2 metadata XML schema, - Harvard Dataverse metadata schema, - DDI Codebook 2.5 metadata XML schema, - Europeana EDM metadata schema, - Schema.org, - Bioschemas, - The PROV Ontology.
Ključne besede: crosswalk, metadata, EDMI metadata set, Dublin CORE, Datacite 4.3 metadata schema, DCAT 2.0 metadata schema, UDAT B2Find metadata recommendation, OpenAIRE Guidelines for Data Archives, OpenAire Guidelines for literature repositories 4.0, OpenAIRE Guidelines for Other Research Products, OpenAIRE Guidelines for Software Repository Managers, OpenAIRE Guidelines for CRIS Managers, Crossref 4.4.2 metadata XML schema, Harvard Dataverse metadata schema, DDI Codebook 2.5 metadata XML schema, Europeana EDM metadata schema, Schema.org, Bioschemas, The PROV Ontology
Objavljeno v DKUM: 21.09.2021; Ogledov: 811; Prenosov: 37
.xlsx Raziskovalni podatki (169,58 KB)
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3.
Modular and branched structure of individualized intelligent e-learning materials for science and technology subject course
Kosta Dolenc, Igor Pesek, Boris Aberšek, 2013, izvirni znanstveni članek

Opis: E-learning and online education offers important opportunities for educators as well as for students. Traditional e-materials, as they are known today, do not allow the recognition of different parameters, such as: learning differences, prior knowledge, learning capabilities, learning environment, styles of learning, etc. Because e-materials are structured in such a way they cannot be successfully adapted for learners who consequently cannot control their own learning (Berge, 2002; Picciano, 2000; Saba, 2002). Such a result offers, among others, a highly anti-motivational effect. The preparation of modern e-materials therefore requires a thorough preparation in terms of content and design, which has to be (mostly) based on pedagogical and didactic theories. Modern e-materials, which can also be named educational e-materials, are usually accessible online (internet-based training (IBT), web-based training (WBT), online education, etc.), they enable and encourage self-learning, they are flexible, dynamic, interactive, use different types of media, individualized and adapted to the users needs. Mostly the latter characteristic will receive special attention in the following research.
Ključne besede: education, individualized e-learning, intelligent system, metadata
Objavljeno v DKUM: 15.12.2017; Ogledov: 1015; Prenosov: 85
.pdf Celotno besedilo (1,31 MB)
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