Museum 'dark data' show variable impacts on deep-time biogeographic and evolutionary history

Area of Science:

• Paleontology
• Macroevolution
• Museum Collections

Background:

• Digitally accessible datasets have transformed paleontology.
• Vast amounts of 'dark data' exist in museum collections, potentially altering evolutionary understanding.
• This 'dark data' remains largely inaccessible and underutilized.

Purpose of the Study:

• To assess the impact of museum-exclusive data on macroevolutionary understanding.
• To investigate how 'dark data' influences biogeographic patterns and diversity drivers.
• To determine the necessity of museum data for comprehensive deep-time analyses.

Main Methods:

• Utilized a dataset of Palaeozoic echinoids, incorporating the majority of museum occurrences.
• Compared the composition of museum 'dark data' with published literature data.
• Analyzed the effects of incorporating museum-only data on biogeographic ranges, diversity drivers, and temporal ranges.

Main Results:

• Museum 'dark data' differs significantly in composition from published data.
• Inclusion of museum data increased average taxon geographic range size by 35%.
• Global diversity driver assessments were significantly impacted by museum-only data.

Conclusions:

• Unpublished museum data are crucial for a complete understanding of deep-time macroevolutionary patterns.
• Digitization and curation of 'dark data' are vital in the era of 'Big Data' in paleobiology.
• Museum collections represent an essential, yet often overlooked, resource for paleontological research.