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Nico Franz [3]Nico M. Franz [2]
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Nico Franz
University of Puerto Rico
  1. Taxonomy for Humans or Computers? Cognitive Pragmatics for Big Data.Beckett Sterner & Nico M. Franz - 2017 - Biological Theory 12 (2):99-111.
    Criticism of big data has focused on showing that more is not necessarily better, in the sense that data may lose their value when taken out of context and aggregated together. The next step is to incorporate an awareness of pitfalls for aggregation into the design of data infrastructure and institutions. A common strategy minimizes aggregation errors by increasing the precision of our conventions for identifying and classifying data. As a counterpoint, we argue that there are pragmatic trade-offs between precision (...)
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  2. Outline of an Explanatory Account of Cladistic Practice.Nico M. Franz - 2005 - Biology and Philosophy 20 (2-3):489-515.
    A naturalistic account of the strengths and limitations of cladistic practice is offered. The success of cladistics is claimed to be largely rooted in the parsimony-implementing congruence test. Cladists may use the congruence test to iteratively refine assessments of homology, and thereby increase the odds of reliable phylogenetic inference under parsimony. This explanation challenges alternative views which tend to ignore the effects of parsimony on the process of character individuation in systematics. In a related theme, the concept of homeostatic property (...)
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    Coordination Instead of Consensus Classification: Insights From Systematics for Bio-Ontologies.Beckett Sterner, Joeri Witteveen & Nico Franz - forthcoming - History and Philosophy of the Life Sciences.
    Big data is opening new angles on old questions about scientific progress. Is scientific knowledge cumulative? If yes, how does it make progress? In the life sciences, what we call the Consensus Principle has dominated the design of data discovery and integration tools: the design of a formal classificatory system for expressing a body of data should be grounded in consensus. Based on current approaches in biomedicine and systematic biology, we formulate and compare three types of the Consensus Principle: realist, (...)
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    Bats, Objectivity, and Viral Spillover Risk.Beckett Sterner, Steve Elliott, Nate Upham & Nico Franz - 2021 - History and Philosophy of the Life Sciences 43 (1):1-5.
    What should the best practices be for modeling zoonotic disease risks, e.g. to anticipate the next pandemic, when background assumptions are unsettled or evolving rapidly? This challenge runs deeper than one might expect, all the way into how we model the robustness of contemporary phylogenetic inference and taxonomic classifications. Different and legitimate taxonomic assumptions can destabilize the putative objectivity of zoonotic risk assessments, thus potentially supporting inconsistent and overconfident policy decisions.
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    Coordinating Dissent as an Alternative to Consensus Classification: Insights From Systematics for Bio-Ontologies.Beckett Sterner, Joeri Witteveen & Nico Franz - 2020 - History and Philosophy of the Life Sciences 42 (1):1-25.
    The collection and classification of data into meaningful categories is a key step in the process of knowledge making. In the life sciences, the design of data discovery and integration tools has relied on the premise that a formal classificatory system for expressing a body of data should be grounded in consensus definitions for classifications. On this approach, exemplified by the realist program of the Open Biomedical Ontologies Foundry, progress is maximized by grounding the representation and aggregation of data on (...)
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