Data Science: Research directions

Combining datasets requires consistent descriptions of what was measured and how it may be used. Machine-readable metadata can help, but incompatible concepts and incomplete documentation still create work. Better discoverability must be accompanied by provenance and justified interpretation.

Uncertainty methods can communicate more than a single predicted value. Their assumptions must remain visible when an analysis is reused or conditions change. A numerical interval should explain what it covers rather than becoming a general seal of certainty.