Methodology for Similarity Assessment of Relational Data Models and Semantic Ontologies

Zarembo, Imants; Teilāns, Artis; Barghorn, Knut; Merkuryev, Yuri; Berina, Gundega

doi:10.1109/sims.2016.21

Cited by 1 publication

(2 citation statements)

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“…Nowadays there are a number of digital tools available to bridge this gap and to create common understanding of Smart specialization matter. When time comes for a legacy relational database to migrate to semantic web or to be integrated with it, an important issue of determining similarity (compatibility) between two data models expressed in different ways arises [9].…”

Section: Resultsmentioning

confidence: 99%

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Smart Specialisation Concept Application in Universities: E-Business Online Studies Model Development

Andersons

Bushati

2019

ETR

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This paper discusses the Smart specialisation concept problems and challenges based on practice of Nordic and Baltic Higher Education Institutions. A particular focus of this research is devoted to the core understanding of the concept of Smart specialisation and its practical application for University level studies curriculum. EU Regional Cohesion Policy and other related EU policies play an important role to understand basic theoretical aspects for Smart specialisation. On the other hand, when specific case studies had been analysed in practice it is possible to see enormous variety of different misunderstandings of the matter. Even different study directions in the same University translate the Smart specialization terms mostly related to their individual study environments. As a result, it is possible to find in practice very different “Smart specialisation” concepts for technology, engineering, economics, IT and other study directions. As the research methodology/approach, the authors analyse the outcomes and challenges faced by different sets of case studies in Baltic and Nordic countries. Using EU, World Bank and other official national documents and publications, the authors explain the ways in which the Smart specialisation concept can be used in online learning environments. As an empirical research evidence there are analysed the outcomes from case studies - practical implementation of an online e-business study course jointly developed by 9 universities from Latvia, Finland, Iceland, Norway, Estonia, Lithuania, Sweden and Denmark supported by e-business field experts from Balkan area universities. Because of still existing gaps in Smart specialisation theoretical framework, the “grounded theory” approach have to be used more intensively when new and advanced theories have been created from practical outcomes of specific case studies. To solve a problem of Smart specialisation concept different translations and applications, authors of this paper propose to construct the teaching methodology of Smart specialisation concept into two consecutive levels - primary, as a core theory unique for all educators and secondary, as specific applied theories for each specific study direction.

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Section: Resultsmentioning

confidence: 99%

“…2) These domains of specialization should make use of existing strengths (smart) such as location, resources, or Science Technology and Innovation (STI) capabilities. Proposed key steps in the strategic process of selecting Smart specialisations [8], [9].…”

Section: B the Framework Development And Strategies Ofmentioning

confidence: 99%

Smart Specialisation Concept Application in Universities: E-Business Online Studies Model Development

Andersons

Bushati

2019

ETR

View full text Add to dashboard Cite

show abstract

Methodology for Similarity Assessment of Relational Data Models and Semantic Ontologies

Cited by 1 publication

References 7 publications

Smart Specialisation Concept Application in Universities: E-Business Online Studies Model Development

Smart Specialisation Concept Application in Universities: E-Business Online Studies Model Development

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