The FireOak team keeps an eye out for and shares the most interesting articles, reports, and case studies related to managing, sharing, and securing information, data, and knowledge. Here are some snippets from what we’re reading right now. This week’s pick is a slide deck by Dr. Heila Piennar evaluating data openness, or when data should be closed, shared, or open.
Evaluating Data Openness
The world of research data: when should data be closed, shared, or open, discusses the following two questions:
- What are the (real) reasons for ‘forcing’ scientists to open their data, even if they are not ready to do so?
- What right have non-scientists (and scientists) to push indiscriminately for the sharing of data without taking the nuances of research into consideration?
The author talks about general physical characteristics of research data before delving into the modes by which data are often shared. It is important that researchers are informed that opening or sharing their data isn’t a one method only approach. For instance, data can be shared on closed networks, to researchers working on similar topics, published with closed licenses, published openly after permission is granted, or published with an open license.
As with most things, evaluating data openness shows that there are advantages and disadvantages to sharing research data.
Advantages of sharing research data:
- Maximizing the impact of data
- Using common databases allows scientists to test data against others and promote scientific progress
- Data sharing informs collaboration
Disadvantages of sharing research data:
- Once data is published, there is no way to know how the data may be used
- Ethical implications could lead to identification of individuals despite a call for anonymity
- Participants may only want their data used in a certain way
Dr. Piennar points to Daniel Barron’s blog post, How freely should scientists share their data?, as a case study exemplifying “public humiliation in the name of Open Science.” This case study describes an escalating dispute regarding how quickly data should be shared.
In short, data sharing is highly subjective and dependent on the type of research, data, ethical implications, funder requirements, and many more factors. Making data open is not a decision to take lightly and needs to be implemented with great care to uphold ethical responsibilities.
Citation: Piennar, H. (2018). The world of research data: when should data be closed, shared or open [SlideShare slides]. Retrieved from https://www.slideshare.net/heila1/the-world-of-research-data-when-should-data-be-closed-shared-or-open