To increase trust, change the social design behind aggregated biodiversity data

Area of Science:

• Biodiversity informatics
• Data science
• Systematic biology

Background:

• Growing concerns about aggregated biodiversity data quality erode trust in large-scale data networks.
• Current strategies focus on correcting errors at the source, which are insufficient for full diagnosis.

Purpose of the Study:

• To investigate the root causes of distrust in biodiversity data aggregators.
• To analyze the role of social design and power dynamics in data aggregation.
• To evaluate the impact of data standards on taxonomic coherence and accountability.

Main Methods:

• Qualitative analysis of trust dynamics in data aggregation.
• Examination of the social design of aggregation processes and power balances.
• Assessment of the Darwin Core standard's role in data coherence.

Main Results:

• Distrust stems not only from data quality but also from the social design of aggregation and power imbalances.
• Aggregators create an accountability gap by downplaying the significance of taxonomic hierarchies ('backbones').
• The Darwin Core standard lacks structure to preserve taxonomic coherence, leading to unsupported inferences.

Conclusions:

• Effective data aggregation requires accommodating taxonomic plurality and addressing unsettled systematic research.
• New technical and social mechanisms are needed for expert validation of taxonomically coherent data packages.
• Enhancing trust necessitates a more accountable and inclusive biodiversity data aggregation process.