Figure 1: Managing all the different ideas simultaneously is the only way to find an optimum

To streamline this, a standardised three-step procedure is employed. Firstly, scientists input their ideas through a user-friendly interface, where they can either draw new structures or modify existing ones. Next, the data is translated and enriched to fit a structured format that facilitates management and connection with other information. Finally, this processed data is stored in a centralised system.

A key feature of this system is its ability to automatically update and refine stored information. When a scientist submits a new idea, the system checks if it already exists in the database. If not, it creates a new entry and establishes the necessary relationships. Additionally, the system includes mechanisms for further data enrichment. Scientists can provide additional metadata, such as reaction conditions and success probabilities, which is then incorporated into the system. This added detail enhances the value of the information, making it more useful for future research and development.

Moreover, the system is designed to integrate data from various sources, including literature and existing databases. This capability broadens the scope of the knowledge base, ensuring that all relevant information is considered and that scientists have access to the most comprehensive dataset possible. Once validated for accuracy and integrity, the data is made available to other researchers. This centralised repository allows scientists to view and build upon each other’s work, fostering a collaborative environment where new ideas can quickly evolve and improve.