Complexity of market data is the new opacity of financial markets. Modern algorithmic financial markets process and produce vast amounts of data. The transition from human trust-based to algorithmic data-driven financial markets led regulators to put in place new market data sharing initiatives to collect, compile, and reconstruct market data from the financial system. Sharing market data is caring about the level-playing field between market participants. But sharing data is also scaring market participants because different datasets, statistical models, and parameter choices can lead to diverging results and cause regulatory uncertainty. Regulation of algorithmic financial markets therefore requires manufacturing consent on the interpretation of market data. The consent is manufactured through the use of consultations, communication channels between market participants and regulators, data sharing between regulators, but also through private regulatory initiatives.