Springer Nature Case Study
Springer Nature is one of the largest academic publishers in the world, with its origins based from back in 1842. Given that most papers are given accreditation through peer review, there are a lot of academics that are involved in the system that need to collaborate in order to get their work published.
Springer Nature, amongst the other large publishers, realised the main problem that their peer review systems are facing is a lack of transparency and was interested to explore a blockchain based solution.
There are many steps and stakeholders involved to publish research all needing to be able to fluently collaborate, yet restricted by the use of each other’s systems. Hence, there are limitations in regards to the availability of and access to crucial data about the peer review process of respective papers. This causes an inefficiency in the process, delays work being published and lacks transparency.
Moreover, publishers value their data very highly and want to keep a lot of it confidential. Sharing exclusive peer review data confidentially and privately is difficult to execute, especially with numerous systems in use.
Springer Nature was in search of a solution that could make crucial peer review data available and be easily integrated with fellow publishers, while instilling trust among everyone.
Katalysis designed a solution that makes this data available across a shared platform, enabling confidentiality and privacy for publishers. This is made possible as no single entity controls or owns the data on the platform.
There is a certain amount of data that is real-time and accessible to all, such as what status the review is at and the confirmation of who is reviewing whose paper. This data is what publishers are comfortable with sharing, as they can establish their relationship by accepting that data can be retrieved from one another beforehand.
The data that publishers want to keep confidential is kept safely behind the publisher firewall. This includes the content of the manuscript, identities of reviewers, and their review comments.