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Synthetic Method in Interdisciplinary Terminological Landscape Research of Digital Economy
- Source :
- SHS Web of Conferences, Vol 50, p 01082 (2018)
- Publication Year :
- 2018
- Publisher :
- EDP Sciences, 2018.
-
Abstract
- The science in the digital age focuses on interdisciplinary research as the main driver of the development. Modern studies of semantic and thematic contexts taken from the digital scientific resources are important for tasks of information technology use in science, education, management and business. As a rule, interdisciplinary research emerges in response to the trends in social and economic development. Socio-political and cultural environment has also a great influence on the introduction of new terminology into the scientific discourse. The delay of scientific discourse regarding the public discourse generates problems of both scientific and philosophical nature. Furthermore, those challenges influence the education system, making demands for new curricula and courses, which, among other things, reflect the categorical and conceptual basis of the new subject areas. The actual objective is to reveal the trends in the terminological landscape of developing interdisciplinary research directions. The present study offers the Synthetic Method, which combines various approaches and tools of Digital Humanities. This Method allows using context query for the search for information resources; the context knowledge explication and clarification of the terminological landscape of interdisciplinary scientific direction “Digital Economy: e-governance and smart technology”.
- Subjects :
- business.industry
05 social sciences
Information technology
Context (language use)
02 engineering and technology
Data science
Terminology
lcsh:Social Sciences
lcsh:H
Explication
Digital humanities
0202 electrical engineering, electronic engineering, information engineering
020201 artificial intelligence & image processing
Sociology
Digital economy
0509 other social sciences
050904 information & library sciences
business
Curriculum
Categorical variable
Subjects
Details
- Language :
- English
- ISSN :
- 22612424
- Volume :
- 50
- Database :
- OpenAIRE
- Journal :
- SHS Web of Conferences
- Accession number :
- edsair.doi.dedup.....69c13d747ff7e50fb7f0420a63d31fa6