Myths and Fears of Scientific Data Sharing

May 28, 2021 Ver este post en Español

Science is moving towards a more open and collaborative future. There is an array of options for how to share data, which we will briefly mention. Although this is happening globally, there are still many challenges that scientists, researchers, and data sharers alike face. We will talk about these in more detail.

There are institutions of high importance such as the US National Academies of Science, Engineering, and Medicine and the European Commission who are making a call for action for science to become more open. Not only that, but they endorsed a set of data-management standards known as the FAIR (findable, accessible, interoperable, and reusable) principles. Many journals are also encouraging or requiring authors to make data available. Scientists have also been publicly criticized for not sharing data, given the plethora of Open Access repositories available to host data from almost all fields.

As we briefly mentioned, there are many challenges associated with data sharing. Concerns surrounding this topic are typically related to the scientists who have gathered or generated the data; some are related to businesses or other organizations that have paid for collecting the data, while others are more practical issues having to do with the administration of the data.

Although we encounter challenges, there are also solutions to many of them. Below are some common myths we have heard, followed by the truth for each:

Myth: Data sharing is not an activity in my field.

Truth: Data sharing mandates are becoming more common across different national, funder, and organizational levels. Thus, regardless of the discipline you are a part of, numerous Open Access repositories accept and host a wide range of data types from almost all fields.

Myth: Data sharing is hard.

Truth: There is support available for research data management, so data sharing does not have to be hard. Data stewards or data librarians can also help with a management plan.

Myth: It does not hurt my research career if this data is not shared.

Truth: Data sharing has the potential to introduce new collaborations and increase citations for a researcher. Data sharing also contributes to higher quality science, better value for money, and most importantly, faster progress in improving health. Therefore, by not sharing data, it can lead to severe repercussions. Scientists are publicly criticized when they do not share data, as we mentioned earlier.

Now that we have debunked some myths let us look at the fears associated with data sharing.

While each of the below fears is a legitimate fear that researchers and scientists have, there is reassurance that there may be a solution to every fear, and there is ultimately nothing to be fearful of.

Data is too sensitive to share. It may be possible to share datasets if appropriate anonymization is followed or by using controlled access. Also, if you still are not able to share your data, you can share your metadata. This provides essential information about how the data can be accessed and cited and will help others to discover your data.
The data will be misinterpreted. As long as there is sufficient contextual information to allow others to understand your data fully, this should not be a problem. A data dictionary can help in this case. A data dictionary supports reuse and reproducibility, therefore, helps avoid misrepresentation.
The data will be misused. Rich metadata must back up your data in this case. Metadata describes both the purpose and the restraints of the data. Wherever there is sensitive data involved, data use agreements are put in place to make the terms in which the data can be used clear.
There are concerns with research being scooped if data is shared. This is a widespread fear among researchers, especially ones in their early careers. Fortunately, there is no evidence to back up this fear. Instead of fearing to scoop, a researcher is encouraged to embrace the possibility of credit. The FAIR policies mentioned above have a role in this as well. They may also find new collaborations as a result.
This data is not useful to anyone else. Quite the contrary - research has a more significant impact than one may think. Beyond researchers, research data is consumed by a multitude of people from different fields, including policymakers and educators.

There are many options and helpful sources in combating any fears that a researcher may have when thinking about sharing data.

Inevitably, there will be some issues that researchers and scientists run into.

There is tension between the researchers who collect the data and those interested only in discrediting the data. Sometimes advocates who are not interested in advancing knowledge look to undermine a study. Believing that these advocates are looking for weaknesses in the data, which may potentially discredit the researchers, they are hesitant to make the data public. Finding ways to ease this tension will also reduce some of the problems related to data sharing.

To make researchers comfortable with sharing sensitive data with others, for example, they must have ways to ensure that the confidentiality of the individuals in that particular data set can be preserved when the data is shared. One way to do this is by sharing the data through data use agreements. This provides any new investigators access to the underlying data, but they must protect any personal information.

Regardless of the many concerns surrounding data sharing, there are many benefits to take into account. Not only can it catalyze new collaborations, but it can increase confidence in findings and generate goodwill among researchers.

Additionally, data sets are becoming easier to cite. This citability allows researchers to receive credit where credit is due. They are also able to use their data sets for job, tenure, and promotion applications. Not to mention the less tangible satisfaction of contributing to the scientific community and giving something of value back to the taxpayers who support basic research.

Read our article about What is OpenAIRE and find out about the many benefits of publishing your data to a research information platform. Platforms such as OpenAIRE aim to institute an open and sustainable scholarly communication infrastructure. Through these types of platforms, Open Science is propulsed into an area of accepted data sharing and exchange.

Conclusion

Although the challenges data sharing highlights are plenty, it really gives us a better look at the current state of science. It is partly open, partly closed, with unclear and inconsistent expectations and policies on data sharing that are still unpredictable.

Even though this is the case, there are many institutions (the US National Academies of Science, Engineering, and Medicine and the European Commission) and people (researchers, scientists, educators, OpenAIRE institutions, and Open Science experts) that are taking the steps necessary to implement changes so data sharing can have a more shared and collaborative approach.

No one is saying that data sharing should be or is easy. But what data sharing can do is far more important than the myths and fears that some researchers or scientists may have. To read more about our role towards a more collaborative future, make sure to take a look at our platform. Also, you can read about how Orvium collaborates with OpenAIRE and find out how researchers are affected.

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