SoG Scientific Governance in Action

The success criteria must make SoG not only scientifically sound, but also practically operable. To satisfy these two potentially contentious criteria, we need to inclusively consider competing scientific methodologies, identify the converging ideas and rules and compile them into shared knowledge bases (PKCs) as symmetrical data content. It is also necessary to identify diverging ideas and rules, and make sure different opinions can easily branch out to isolated knowledge bases to avoid unnecessary entanglement of operational data. This is often known as the practice of version control, but the adequate adoption of version control data in different application domains can be costly and requires a lot of Information Technology support in an organization. That is why a general purpose data management platform that is not designed to maximize commercial interest is a precondition of data ownership/data sovereignty. Most of the organizations are still debating their internal differences using traditional means of verbal interactions. In many cases, a well-managed set of historical records, such as a transparent, accountable action log will resolve a lot of managerial issues. In other words, Scientific Governance requires a scientific instrument, and that instrument is PKC.

As mentioned earlier, data becomes more trustworthy if the ordering sequences of potentially interactive events do not violate the temporal logic in the physical world. It is time and pre/post conditions that helps organizations to filter operational data to an actionable body of knowledge. That is why the Science of Governance can only be exercised operationally with a symmetrical format represented in Hoare Triples.