From Open Data to Open Science

The open science movement continues to gain momentum, attention, and discussion. However, there are a number of different interpretations, viewpoints, and perspectives as to what the term open science means. In this study, we define open science as a collaborative culture enabled by technology that empowers the open sharing of data, information, and knowledge within the scientific community and the wider public to accelerate scientific research and understanding. As science has become increasingly data driven, data programs now play a critical role in enabling and accelerating open science. In this study, we describe specific actions that data programs can take to make the open science paradigm shift a reality. These actions range from implementing open data and software policies to reimaging data systems that move data out of organizational silos and into cyberinfrastructures that enable efficient research processes and accelerate knowledge dissemination. There are still a number of obstacles to be overcome by data programs which range from mitigating the risk of open data misuse to overcoming the inertia of legacy systems. Data programs need to support open science through the thoughtful development of open policies, systematic investment in innovative and collaborative infrastructures, and the promotion of cultural change. On the other hand, individual researchers play an equally important role by serving as advocates for open science principles and by adopting a number of best practices outlined in this study. By working together, a new and more open age of scientific research can be achieved to benefit science and society.

Automated summary

Open science is defined as a collaborative culture enabled by technology that facilitates the sharing of data, information, and knowledge to accelerate scientific research and understanding. Data programs are crucial in enabling and accelerating open science, and actions such as implementing policies and reimagining data systems can help realize the shift towards open science. Overcoming obstacles like the risk of data misuse and legacy system inertia is necessary for data programs to support open science through policy development, investment in infrastructure, and cultural change. Researchers also play a significant role in advocating for open science principles and adopting best practices to achieve a more open age of scientific research for the benefit of science and society.