scholarly journals EVOLUTION OF OPEN SCIENCE TOOLS AND TECHNOLOGIES

2021 ◽  
pp. 293-298
Author(s):  
Yuliia Nosenko
Keyword(s):  
Open Access ◽  
Data Exchange ◽  
Innovation Policy ◽  
Knowledge Society ◽  
Open Science ◽  
Knowledge Flows ◽  
Research And Innovation ◽  
Grant Support ◽  
Registration Number ◽  
Research And Innovation Policy

Building a global information space and Knowledge Society, the European community is developing a priority area for research and innovation policy – the Open Science, which, among other things, provides open access to publications and research results. When developing this direction in Ukraine, it is expedient to take into account the experience of successful countries, global transformations and trends, digital progress, and historical lessons. The article’s purpose is to substantiate the periodization and determine the stages of evolution of open science tools and technologies in the world. The article presents some results of the research within the project «Cloud-oriented systems of open science in teaching and professional development of teachers» (registration number 2020.02/0310) implemented with grant support from the National Research Fund of Ukraine. Theoretical methods are used: historical-pedagogical method, generalization of scientific and scientific-methodical sources, analysis and systematization of concepts, works of Ukrainian and foreign scientists, experts in the field of digitalization of education and science. The periodization of the evolution of open science tools and technologies has been developed. The first stage was characterized by a sharp increase in data and knowledge flows, the emergence of the first initiatives to ensure the availability of scientific and cultural achievements of humankind. The second stage was characterized by the intensification of the process of transition of journals and scientific repositories to the open format, the development and dissemination of software to support open access, the development of cloud computing and Web 2.0 technology. The result of the third period was the intensive development of scientific-educational environments, due to the processes of digitization, increasing trends: open access, archiving of articles, data exchange.

scholarly journals Empowering civil society through educating about responsible research and innovation

2018 ◽  
Vol 48 ◽  
pp. 01045
Author(s):  
Marta Majorek ◽  
Marta du Vall
Keyword(s):  
Innovation Policy ◽  
Third Sector ◽  
Knowledge And Skills ◽  
Social Actors ◽  
Research And Innovation ◽  
Number Of Factors ◽  
Engagement Process ◽  
Understanding Of Science ◽  
Research And Innovation Policy ◽  
Lack Of Knowledge

Number of factors may be indicated that can negatively affect the willingness of third sector actors and citizens to get involved with research and innovation policy. It is worth referring to these factors as barriers to societal engagement. Six key barriers can be identified: lack of knowledge and skills, lack of relevance, lack of impact, lack of trust and critical views of others, lack of time and finances, and lack of legitimacy. The main purpose of this article is to present some policies and practice options that can help to overcome these barriers. The main focus will be on solving the lack of knowledge and skills of social actors. In this context, the fact that citizens and third sector actors may perceive an engagement process as not relevant to their own interests, concerns, and goals may be indicated as the main cause for their non-involvement. Citizens and third sector actors may refrain from engagement when they fear they lack the necessary knowledge and skills to engage in research or in research and innovation policy. They may also be reluctant to participate when they do not have the basic understanding of science and scientific working methods. The article will propose an overview of policies and activities that can effectively overcome the indicated barriers to engagement.

scholarly journals Corporate R&D intensity decomposition: different data, different results?

2020 ◽  
Author(s):  
Pietro Moncada-Paternò-Castello ◽  
Sara Amoroso ◽  
Michele Cincera
Keyword(s):  
Research And Development ◽  
Analytical Methods ◽  
Innovation Policy ◽  
International Comparisons ◽  
Policy Implications ◽  
Data Sources ◽  
Empirical Results ◽  
Research And Innovation ◽  
Research And Innovation Policy ◽  
First Time

Abstract Research and Development (R&D) indicators are used to facilitate international comparisons and as targets for research and innovation policy. An example of such an indicator is R&D intensity. The decomposition of the aggregate corporate R&D intensity is able to explain the differences in R&D intensity between countries by determining whether is the result of firms’ underinvestment in R&D or of the differences across sectors. Despite its importance, the literature of corporate R&D intensity decomposition has been developed only recently. This article reviews for the first time the different methodological frameworks of corporate R&D intensity decomposition and how they are used in practice, shedding light on why sometimes empirical results seem to be contradictory. It inspects how the use of different data sources and analytical methods affect R&D intensity decomposition results, and what the analytical and policy implications are. The article also provides methodological and analytical guidance to analysts and policymakers.

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