Biodiversity Information Science and Standards : Conference Abstract
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Corresponding author: Nico Franz (nico.franz@asu.edu)
Received: 28 Jun 2019 | Published: 02 Jul 2019
© 2019 Nico Franz, Edward Gilbert, Beckett Sterner
This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Citation: Franz N, Gilbert E, Sterner B (2019) Distributed, but Global in Reach: Outline of a de-centralized paradigm for biodiversity data intelligence. Biodiversity Information Science and Standards 3: e37749. https://doi.org/10.3897/biss.3.37749
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We provide an overview and update on initiatives and approaches to add taxonomic data intelligence to distributed biodiversity knowledge networks. "Taxonomic intelligence" for biodiversity data is defined here as the ability to identify and renconcile source-contextualized taxonomic name-to-meaning relationships (
We predict that the success of this project will ultimately rest on our ability to up-value the roles and recognition of systematic expertise and experts in large, aggregated data environments. We will argue that these environments will need to adhere to criteria for responsible data science and interests of coherent communities of practice (
We will demonstrate in principle and through concrete use cases, how to de-centralize systematic knowledge while maintaining alignments between congruent or concflicting taxonomic concept labels (
Having established an intellectual opportunity, as well as a technical solution pathway, we turn to the issue of developing an implementation and adoption strategy. Which biodiversity data environments are currently the most taxonomically intelligent, and why? How is this level of taxonomic data intelligence created, maintained, and propagated outward? How are taxonomic data intelligence services motivated or incentivized, both at the level of individuals and organizations? Which "concerned entities" within the greater biodiversity data publication enterprise are best positioned to promote such services? Are the most valuable lessons for biodiversity data science "hidden" in successful social media applications? What are good, feasible, incremental steps towards improving taxonomic data intelligence for a diversity of data publishers?
alignment, biodiversity data, conflict, coordination, de-centralization, Region Connection Calculus, taxonomic concepts, systematics
Nico M. Franz
Biodiversity_Next 2019