CKEditor is an authority on rich-text editing and real-time collaborative writing. We pride ourselves on our growing reputation for finding solutions for firms in a multitude of fields. Modern science is one of them; a rich-text solution to reconciling data and code is in need, and CKEditor is in the position to help save the day.
# The data reproducibility crisis
The 2010s brought a scourge upon the sciences in what has been coined the data reproducibility crisis. As such, scientists have been unable to reproduce previously published results in many cases. Some researchers have even admitted to falsifying their studies or knowing someone who had. If this sounds worrying, it should. The ability to reproduce results (or, well, not) has ramifications for scientific and business developments alike.
The data reproducibility crisis has three related aspects: weak correlations made in research results, an oppressive pressure to publish in academic culture, and the fevered desire to please stakeholders in the academic and business worlds alike. Simply put, the “publish-or-perish” mindset that has had young researchers scrambling to make an impact in their chosen field, be prolific in their work, and continuously build their reputation, has led to mistakes (at best) and falsifications (at worst). Members of the academic community put intense pressure on each other to produce, and therefore the time needed for proper analysis and reproductions of initial results is not taken. The crisis may also hinder attempts to apply that science; bad results can lead R&D teams to create proofs of concept on shaky grounds.
# A rich-text editor’s role in open science
One approach to remedying the crisis is to take the emphasis off of publishing finished work by encouraging collaboration on raw data found during the research process. A so-called “open science” framework could be the elixir that the sciences need. Possible practices of open science, according to The Conversation, include open peer-review and open notebook science. Further, they report that there are already platforms being developed to support these approaches.
We can confirm that there are. The possibility for disparate parts of the scientific community to collaborate on crunching data is an opportunity to develop the right tools to support it. Leave it to the Swiss Data Science Center (SDSC) to stand at the front of the open science approach, creating a platform like Renku that works as a collaborative knowledge base in which to analyze data and code – a GitHub for data scientists, if you will. To mitigate the data reproducibility crisis, transparency in data analysis is paramount. With that in mind, the SDSC is counting on CKEditor 5 to help lead the open science charge.
Rich-text editors help researchers analyze and confirm data and code by giving them a vast array of options to format, style, and cleanly present it. Renku’s creators, however, believe they can use CKEditor 5 beyond stemming the crisis. When we spoke with SDSC senior computer scientist Chandrasekhar Ramakrishnan, he talked about the potential for Renku to advance science. “We’re about making a platform that makes it easy for researchers to describe what they’ve done so others can carry it out, whether exactly or in variations through different experiments on the data.”
Rich text editors help researchers confirm data by giving them a vast array of options to format, style, and cleanly present it.
# A science tool with its eye on the business world
Naturally, that translates to business. With Renku, the Swiss Data Science Center not only has an open-source tool to fight the data reproducibility crisis, but also a business model for public as well as private use. “Data science is becoming more important to business, becoming an embedded part of companies,” Ramakrishnan continued. “It involves collaboration of multiple parties – data scientists, statisticians, programmers, business minds, project managers, and those who identify metrics. We see Renku as well positioned to address those kinds of developments between industry and data scientists.”
While exciting, we must remember that old habits die hard. The publish-or-perish mindset, stemming from the drive for career advancement, is firmly rooted in ego. The fiercely competitive nature of careers in research indicates resistance toward a collaborative concept such as open science. It takes a community, however, to use science for the greater good. In the end, altruism stands a good chance of winning out. And as it does, CKEditor will provide the engine for initiatives like Renku as they enable scientific discovery.