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Citizen SciencePublic Participation in Environmental Research$
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Janis L. Dickinson and Rick Bonney

Print publication date: 2012

Print ISBN-13: 9780801449116

Published to Cornell Scholarship Online: August 2016

DOI: 10.7591/cornell/9780801449116.001.0001

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Using Data Mining to Discover Biological Patterns in Citizen Science Observations

Using Data Mining to Discover Biological Patterns in Citizen Science Observations

Chapter:
(p.125) 8 Using Data Mining to Discover Biological Patterns in Citizen Science Observations
Source:
Citizen Science
Author(s):

Daniel Fink

Wesley M. Hochachka

Publisher:
Cornell University Press
DOI:10.7591/cornell/9780801449116.003.0009

This chapter focuses on the use of data mining to discover biological patterns in citizen science observations. In particular, it describes a set of statistical tools designed to take advantage of access to massive quantities of data with a strong emphasis on pattern discovery. The chapter begins with an overview of how data mining can be used to explore and learn about species distribution, along with the insights that can be gained by applying these methods to broad-scale citizen science data. Using data from bird monitoring projects eBird and Project FeederWatch, it demonstrates an exploratory strategy in which the focus of investigations moves from general phenomena to the processes responsible for the phenomena. It then considers distinction between exploratory and confirmatory analysis and the important practical issues that should be taken into account when planning an exploratory analysis with citizen science data.

Keywords:   data mining, biological patterns, citizen science, statistical tools, citizen science data, bird monitoring, eBird, Project FeederWatch, confirmatory analysis, exploratory analysis

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