Data Sharing and Developing Countries
Data sharing and what motivates individuals towards the dissemination of their research must thus also be considered a personal activity. It is therefore important to consider that data sharing on an individual level is informed by a plethora of influences, including:
This project thus asks three questions:
1. How do scientists in low/middle-income countries interact with data during the course of their daily research?
2. Do these practices differ from those employed in high-income countries? If so, what elements of the research environment cause these variations?
3. How might the characteristics of data use and dissemination in low/middle-income countries be better represented in the paradigm of Open Science?
Data sharing and what motivates individuals towards the dissemination of their research must thus also be considered a personal activity. It is therefore important to consider that data sharing on an individual level is informed by a plethora of influences, including:
- Bureaucratic and regulatory demands – including whether these demands conflict or offer unequal benefits.
- Social responsibilities – that scientists perceive towards society, and the response that data sharing garners from society.
- Physical structures – whether the research infrastructure facilitates sharing and accessing the benefits of sharing.
- Scientific commitments – whether sharing is part of the contextual scientific culture, whether scientists perceive it as their obligation to the international scientific community, and how they understand the rewards and responsibilities of their research.
- Understanding of data and sharing – how scientists perceive value in data worth sharing, and how they go about doing it.
This project thus asks three questions:
1. How do scientists in low/middle-income countries interact with data during the course of their daily research?
2. Do these practices differ from those employed in high-income countries? If so, what elements of the research environment cause these variations?
3. How might the characteristics of data use and dissemination in low/middle-income countries be better represented in the paradigm of Open Science?