Combined summary - Should there be a "Network Data" category?
In the realm of protocol design and implementation, there's a recognition of the importance of performance benchmarks and their role in decision-making.
While such benchmarks are commonly associated with specific implementations on platforms like GitHub, there is a proposal to broaden this scope. A suggestion has been made to create a new category—potentially named "Measurements" or "Observations"—that would encompass performance analysis not directly tied to an implementation. The rationale is that insights into network behavior through detailed benchmarks, such as those analyzing IBD sync or secp256k1 signing processes, would contribute significantly to the improvement of protocol design.
The debate hinges on whether to place this data analysis alongside implementation discussions or in a new, dedicated category that focuses on a wider range of measurements. It is argued that knowledge about network behavior can inform and enhance protocol design; therefore, it might fit well within the "Protocol Design" category. Nevertheless, the idea of a separate "Measurements" category has been floated as a more appropriate home for such discussions.
A pragmatic approach has also been suggested: start by sharing this type of content in a single post and, if interest grows, consider establishing a standalone category. This approach is supported by the availability of extensive data, such as 11 years worth of network propagation information, which includes transaction and block hash details along with corresponding timestamps. This dataset could provide valuable insight into historical orphan rates and mempool reconstruction.
There is a consensus that creating a space for centralized discussion and processing of Bitcoin-related data would be beneficial. Such a category would facilitate the sharing and requesting of both raw and processed data, including graphs pertinent to Bitcoin development. Examples of potential discussions include the examination of the percentage of fees within block rewards over the years and comparisons of transaction volume over time. By consolidating these conversations, multiple contributors could engage more effectively, leveraging visual aids and collaborative discussion to advance understanding and innovation in the field.