Unified and pluralistic ideals for data sharing and reuse in biodiversity

Abstract

How should billions of species observations worldwide be shared and made reusable? Many biodiversity scientists assume the ideal solution is to standardize all datasets according to a single, universal classification and aggregate them into a centralized, global repository. This ideal has known practical and theoretical limitations, however, which justifies investigating alternatives. To support better community deliberation and normative evaluation, we develop a novel conceptual framework showing how different organizational models, regulative ideals and heuristic strategies are combined to form shared infrastructures supporting data reuse. The framework is anchored in a general definition of data pooling as an activity of making a taxonomically standardized body of information available for community reuse via digital infrastructure. We describe and illustrate unified and pluralistic ideals for biodiversity data pooling and show how communities may advance toward these ideals using different heuristic strategies. We present evidence for the strengths and limitations of the unification and pluralistic ideals based on systemic relationships of power, responsibility and benefit they establish among stakeholders, and we conclude the pluralistic ideal is better suited for biodiversity data.

Figure 1.

A typology for suitable management approaches to resources, modified from Ostrom et al. (62).

Figure 2.

Five epistemic-organizational models for data pooling: data aggregators, search index portals, research contractors, peer data commons and custom databases. The properties of these models are illustrated by analogous approaches to how businesses or social groups make food for broader consumption. The models rely on data standardization and preprocessing to an increasing degree from left to right.

Figure 3.

Four possible heuristics (A–D) for data pooling and their relationship to the unified and pluralistic ideals. See main text for discussion of A-D. White boxes represent distinct data portals, and colored symbols within the box represent data standardized to a local, potentially unique taxonomic classification that is not deliberately harmonized with other taxonomies. The vertical overlap in white boxes indicates where portals overlap in the scope of data they include.

Figure 4.

Two heuristic approaches to unified data pooling. (A) Image from Bisby (28), illustrating his envisioned unified hierarchy of classificatory theories for taxonomic domains. The hierarchy would enable a centralized aggregator or modular system of data pools. (B) Image from Gallagher et al. (52), illustrating a modular hub-and-spoke system for integrating trait data about species by taxonomic domains. Black circles at the edges of the network show primary data publishers or sources. Intermediate nodes show projects harmonizing data and developing standards. The central, largest node represents a trait dataset registry that functions as a basic search index portal across domains.

Figure 5.

Selected examples of North American and global biodiversity data pooling projects illustrate the current partially coordinated flow of biodiversity data (uni- or bi-directional arrows). Projects are distinguished by the geographic scale (y-axis) and type of domain used to characterize their scope (colors by column on the x-axis). The aggregator column represents some important biodiversity data pooling projects whose scopes cut across the other domain categories.