The Deceptive Practice of Openwashing with Open Access Data

You’ve probably heard the term greenwashing before. A company might say that their new “green” items are recyclable when the truth is more complicated. It’s tricky wordplay—being dishonest with the public but phrasing it so that it is technically true. Those who advocate for green policies are frustrated by these deceptive greenwashing practices. The same applies for advocates who want companies and governments to be more transparent about the data they collect. Openwashing is similar to greenwashing, in which groups like organizations and governments claim they are disclosing information, but in reality, it’s not entirely the case. What does it mean for an organization or government to provide open access and just how truly open are they?

Defining what open access (OA) means in this context is easier said than done, as “literature on openness has produced multiple understandings and conceptual ambiguity as to what is meant by openness” (Dahlander & Gann, 2010). However, for simplicity’s sake, OA content (data, books, movies, reports, etc.) should have these elements: 

• Free. Not free as in Free for a Limited Time, Restricted “Freemium” Access, or Free but I’m Selling Your Personal Data in Exchange. Completely Free. Full Stop. 
• Accessible. Accessing the content should be relatively quick and shouldn’t require a waiting period or a sign-in. People should be to able access it whenever they want—especially electronic materials. 
• Unlimited control. The public can use, copy, or distribute the content indefinitely, provided that they give credit to the original author. 

The concept of OA is not new. Academic institutions have been openly sharing scientific research and publications since the 1660s (Schlagwein et al., 2017). However, in the past decade, the pressure on governments and organizations to be even more transparent with their data and content has created a vast expansion of OA materials. Morrison (2020) notes “while many aspects of our lives and activities have slowed down during the COVID pandemic, this has not been the case with open access!” For example, as of this writing, the Directory of Open Access Journals has over 20,000 open journals and over 9 million open access articles. This number is only going to grow, and all of it is completely free to the public. 

Despite this amazing growth of open access, there are still many organizations that are reluctant to be truly open. As Heimstädt (2017) notes, when organizations are “forced to make the information they control accessible to the public and the other members of the organizations, individuals loose [sic] this power and thereby descend on the informal hierarchy.” At the same time, there is pressure from the public to be open, so the compromised result is “providing selective information without having an environment where citizens can freely use that data” (Brandusescu, 2016). According to Heimstädt, there are generally three ways to provide selective information to the public: 

• Selecting. Parts of the data are shared, but not in its entirety. Organizations may remove sensitive or profane information that they do not want the public to see. 
• Bending. Similar to selecting, the data is released, but it is organized in a way in which the full picture is not truly revealed. 
• Orchestrating. Data is released, but rather presented in its raw form, it is crafted in a certain way for the public to see. 

Granted, there are times in which these practices may seem justifiable. For example, orchestrating very complex data may be good to avoid confusing the general public. Also, certain parts of data may contain sensitive information that could be exploited by others, thus it is beneficial to be selective about what is released. However, despite some of these justifications, if released data is not truly open, why are they calling it so? 

Take the Covid-19 pandemic and openness for example. In 2021, the European Centre for Disease Prevention and Control was accused of not being transparent enough with its open data being released to the public—possibly relying on incomplete datasets. In California, the state released only select information to the public despite claiming it would provide maximum transparency. While there is an argument for these organizations to withhold some information, when open doesn’t mean fully transparent, it is difficult to ascertain just how reliable it is. 

This is the main problem and also the solution to openwashing. As previously mentioned, the definition of the word open is incredibly vague and is often contested. It also doesn’t help that the word open means something entirely different to many people. The solution is to have a clear and legally binding definition of what open means to research. Using open license models like Creative Commons (CC) is helpful when it comes to what one can legally do with that data once it is released. However, open license models are not as effective when it comes to the type of data released. For example, a resource could have a CC license, but 25% of its content could be redacted—making it partially open. If governments and organizations claim they are being open and transparent with their data, they need to demonstrate that it is truly open and be held accountable if they are not. 

The meteoric rise of OA materials is vital for the growth of science and economic development. However, just like being “green”, being “open” must be truthful—otherwise, the word means nothing. 

Picture credit: Image adapted from 愚木混株 Cdd20 from Pixabay

References

Agbo, L. (2021). COVID-19: EU health agency lacks data, transparency, says ombudsman. Allnews. https://allnews.ng/news/covid-19-eu-health-agency-lacks-data-transparency-says-ombudsman

Associated Press. (2021, Jan 22). Despite promises of transparency, California keeps key virus data from public. KTLA5. https://ktla.com/news/california/despite-promises-of-transparency-california-keeps-key-virus-data-from-public/

Brandusescu, A. (2016). #openwashing…anyone? Web Foundation. https://webfoundation.org/2016/10/openwashing-anyone/

The Canadian Press. (2022, January 7). Keurig Canada fined $3 million for misleading claims over coffee pod recycling. CBC News. https://www.cbc.ca/news/business/keurig-fined-3-million-fine-1.6307150

Dahlander, L., & Gann, D. M. (2010). How open is innovation? Research Policy, 39(6), 699–709. https://doi.org/10.1016/j.respol.2010.01.013

European Ombudsman. (2021). Ombudsman calls on ECDC to be more open about its work as vaccine rollout begins. https://www.ombudsman.europa.eu/en/press-release/en/137880

Heimstädt, M. (2017). Openwashing: A decoupling perspective on organizational transparency. Technological Forecasting & Social Change, 125, 77–86. https://doi.org/10.1016/j.techfore.2017.03.037

Morrison, H. (2020). Dramatic growth of Open Access September 30, 2020. The Imaginary Journal of Poetic Economics. https://poeticeconomics.blogspot.com/2020/10/dramatic-growth-of-open-access.html

Schlagwein, D., Conboy, K., Feller, J., Leimeister, J. M., & Morgan, L. (2017). “Openness” with and without information technology: A framework and a brief history. Journal of Information Technology, 32(4), 297–305. https://doi.org/10.1057/s41265-017-0049-3