Elfinwood Data Science

Data Science for Everyone

Elfinwood is a term used to describe stunted forests characteristic of most subalpine and alpine regions world-wide. Also referred to as krummholtz, these miniature forests occur at the upper altitudinal limits of trees.

The objective of this blog is to help improve data management in general, with examples given from the biological and environmental sciences. To this end, I’ll present an introduction to data management and a database schema model with the intent of moving us towards a more integrated approach to data management. The materials presented will be equivalent to that of a graduate level course in data management.

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Learning Data Science

Introduction In the previous post I covered branches and basic merging in Git. In this post I’ll introduce readers to a GitHub repository that we’ll be using for this and future posts to facilitate learning, and then you’ll fork the repository and clone the forked repository to your computer. Since data analysis and management areContinue reading “Learning Data Science”

Version Control: An Overview

Introduction In the last post I provided an overview of databases and data management systems. This post is the first in a 5 part series on version control. The objective of this post is to provide an overview of version control for managing code. This is in preparation for using version control in future postsContinue reading “Version Control: An Overview”

Databases and Data Management Systems

Introduction In the last post I provided an overview of data management plans: Data Management Plans. In this post I’ll be presenting on databases and data management systems (DBMS), including a discussion about what constitutes a database, the basics of relational databases, and an overview of several popular DMBS software options. What is a Database?Continue reading “Databases and Data Management Systems”

Data Management Plans

“By failing to prepare, you are preparing to fail.” Benjamin Franklin Introduction In the last post I provided an overview of the final stage in the data pipeline: Metadata and Archiving. The first stage in the data pipeline is planning, and I provided an overview of this stage in my third post “The Data Pipeline:Continue reading “Data Management Plans”


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