Most persons are primarily interested in using data to make their point. Why persons seek truth non-instrumentally is a mystery from an evolutionary perspective. That mystery need not serve as the basis for true enlightenment. A better basis for true enlightenment is a norm of credibility through data accessibility: if you use data to make a point, you must make sufficient, high-quality data freely available to analyze that point and related points. If you don’t, your use of data should be considered pointless.
Open data platforms often have only superficial institutional support and face continual funding battles. Vertical disintegration in data production, dissemination, analysis, and claim-making reduces upstream data-production incentives. High-quality data can support a wide variety of insights and values. Particular interests in it are relatively small.
Data ethics in academic scholarship are slowly developing. While a small number of scholars do hugely important work in collecting, curating, and disseminating data, their work is greatly undervalued academically. Data is likely to continue to be greatly undervalued in academic status competition. A more propitious development is scholarly norms of data disclosure. Providing data access is slowly becoming a requirement for taking scholarly claims seriously.
Most statistics quoted in general public discussion are uninterpretable or misinterpreted. Much scholarly work follows disciplinary conventions that support objectively meaningless work. But if such rhetoric and scholarship helps to generate high-quality data, its net effect on public discussion will be positive.