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    Remote sensing data processing – NEON airborne data
    Concepts of remote sensing and data logistics, and NEON remote sensing data are introduced. Students learn how to apply spatial data processing and visualization skills using R coding program to...
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    NEON Data in the Classroom: Quantifying Spatial Patterns
    Students build on fundamental concepts of spatial patterns and combine this knowledge with the open-data from the National Ecological Observatory Network to quantify spatial autocorrelation and...
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    Data management and introduction to QGIS and RStudio for spatial analysis
    Students learn about the importance of good data management and begin to explore QGIS and RStudio for spatial analysis purposes. Students will explore National Land Cover Database raster data and...
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    Remote Sensing of Plants and Topography in R (Project EDDIE)
    Students will explore different possible abiotic drivers of plant growth, defined as greenness and height. In the final step, students will analyze data from around the United States and consider...
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    Comparative Landscape Ecology Project using RStudio Cloud (Project EDDIE)
    This modified version incorporates the use of RStudio Cloud for easier remote instruction, and culminates in an exploratory project comparing the influence of patch metrics on vegetation health for...
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    Northern Processing
    Using photoshop and illustrator from tif file to make a figure
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    Teaching Data Viz and Communication as an Undergraduate Biology Course: Assignments and Projects
    Teaching materials co-developed for a new upper-level undergraduate biology course to teach data exploration and communication without requiring previous coding experience.
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    Teaching Data Viz and Communication as an Undergraduate Biology Course: Syllabus and Resources
    Teaching materials co-developed for a new upper-level undergraduate biology course to teach data exploration and communication without requiring previous coding experience.
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    RNA-seq Analysis
    In this computer lab module, students learn how to process an RNA-seq data set to identify differentially expressed genes (DEGs). The samples for this data set were collected from yeast cells...
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    Biological Diversity in Wetlands: Applying the Scientific Method
    An introduction to the Scientific Method for Introductory Biology students using plant and animal richness and environmental data from ephemeral ponds and permanent wetlands.
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    DataONE Module 02: Data Sharing
    Data sharing in the context of the data life cycle, the value of sharing data, concerns about sharing data, and methods and best practices for sharing data.
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    Chapter 3: Visualizing data
    Biostatistics Using R: A Laboratory Manual was created with the goals of providing biological content to lab sessions by using authentic research data and introducing R programming language....
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    REMNet Tutorial, Excel Part 1: Accessing Your Microbiome Data 5.3.19
    Video on accessing microbiome data from the Research Experiences in Microbiomes Network
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    Data is the New Science - Modified and combined with Following the Data Module
    In this module, students will be introduced to some emerging biodiversity data resources. They will be asked to think critically about the strengths and utility of these data resources and apply...
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    What is Data Science - Introduction to Data Science
    Data Science is the technology that goes behind handling and working with data in the 21st century. Data Science concepts have proved to be the pinnacle in the last couple of years with the onset...
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    BIO 439/539: Big Data Analysis
    Course materials for BIO 439/539: Big Data Analysis
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    More In Depth Spreadsheet Management Adaptation of Data Management using NEON Small Mammal Data
    This adaptation consists of three exercises that introduce students to 1) format spreadsheet data tables, 2) carry out spreadsheet quality control, and 3) count/sort/filter data of interest in...
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    NEON_PDSI
    Users access and manipulate drought data and visualize these data to learn about historical drought patterns.
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    DataONE Module 01: Why Data Management?
    Trends in data collection, storage and loss, the importance and benefits of data management, and an introduction to the data life cycle.
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    Data Ethics
    Data ethics and the use of digital data
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