Update on the #DontLeaveItToGoogle campaign

A few months ago, I started the #DontLeaveItToGoogle campaign on Twitter to protest Google Dataset Search and to urge funders to provide the means for creating open alternatives. The original tweet has since been retweeted and liked hundreds of times and reached 50K impressions. As I had hoped, it also started a widespread discussion about open infrastructures in research.

Since then, I have been interviewed for the Elephant in the Lab to clarify the issues behind the initial tweet. I also wrote a piece for GenR where I laid out the specific problems in the discovery space.

And last week, I gave a keynote at the Open Science Conference in Berlin that contrasted the approach of proprietary vendors such as Google with the open infrastructure. In this talk that I co-created with Maxi Schramm, I argued that there is a serious crisis of discoverability in research. Scientific knowledge is growing at an unprecedented rate, but we do not have the tools to keep up with this growth. As a result, we see the emergence of dark knowledge, i.e. knowledge that cannot be discovered and reused.


Proprietary discovery tools from companies such as Google, Elsevier, and Digital Science are one of the main reasons for this problem. Their tools have outdated user interfaces and they do not allow for reuse of their data and software. What cannot be found within their systems is invisible to researchers and practitioners, essentially creating a wall of dark knowledge. We therefore cannot leave it to these large commercial entities to solve the discoverability crisis.


Instead we have to invest in the open discovery infrastructure. In the open infrastructure, reuse reigns supreme. We can all build on top of each other’s work, creating a cycle of continuous innovation. No one tool has the monopoly over which content researchers and practitioners get to see, tearing down the wall of dark knowledge.


Going forward, it will be especially important to fund user interfaces and user-facing services. Otherwise, we will give up all control over how users interact with open science. We also lose governance over user data and algorithms, and we miss out on a large chunk of innovation potential in that area.


You can find the slides from the talk here. I’d be very interested in your feedback on these ideas and arguments. Add your voice on social media using the #DontLeaveItToGoogle hashtag, or respond in the comments below.




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