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  • The Barbara K. Ostrom (1978) Bioinformatics and Computing Facility
  • Computing Resources
    • Active Data Storage
    • Archive Data Storage
    • Luria Cluster
      • FAQs
    • Other Resources
  • Bioinformatics Topics
    • Tools - A Basic Bioinformatics Toolkit
      • Getting more out of Microsoft Excel
      • Bioinformatics Applications of Unix
        • Unix commands applied to bioinformatics
        • Manipulate NGS files using UNIX commands
        • Manipulate alignment files using UNIX commands
      • Alignments and Mappers
      • Relational databases
        • Running Joins on Galaxy
      • Spotfire
    • Tasks - Bioinformatics Methods
      • UCSC Genome Bioinformatics
        • Interacting with the UCSC Genome Browser
        • Obtaining DNA sequence from the UCSC Database
        • Obtaining genomic data from the UCSC database using table browser queries
        • Filtering table browser queries
        • Performing a BLAT search
        • Creating Custom Tracks
        • UCSC Intersection Queries
        • Viewing cross-species alignments
        • Galaxy
          • Intro to Galaxy
          • Galaxy NGS Illumina QC
          • Galaxy NGS Illumina SE Mapping
          • Galaxy SNP Interval Data
        • Editing and annotation gene structures with Argo
      • GeneGO MetaCore
        • GeneGo Introduction
        • Loading Data Into GeneGO
        • Data Management in GeneGO
        • Setting Thresholds and Background Sets
        • Search And Browse Content Tab
        • Workflows and Reports Tab
        • One-click Analysis Tab
        • Building Network for Your Experimental Data
      • Functional Annotation of Gene Lists
      • Multiple Sequence Alignment
        • Clustalw2
      • Phylogenetic analysis
        • Neighbor Joining method in Phylip
      • Microarray data processing with R/Bioconductor
    • Running Jupyter notebooks on luria cluster nodes
  • Data Management
    • Globus
  • Mini Courses
    • Schedule
      • Previous Teaching
    • Introduction to Unix and KI Computational Resources
      • Basic Unix
        • Why Unix?
        • The Unix Tree
        • The Unix Terminal and Shell
        • Anatomy of a Unix Command
        • Basic Unix Commands
        • Output Redirection and Piping
        • Manual Pages
        • Access Rights
        • Unix Text Editors
          • nano
          • vi / vim
          • emacs
        • Shell Scripts
      • Software Installation
        • Module
        • Conda Environment
      • Slurm
    • Introduction to Unix
      • Why Unix?
      • The Unix Filesystem
        • The Unix Tree
        • Network Filesystems
      • The Unix Shell
        • About the Unix Shell
        • Unix Shell Manual Pages
        • Using the Unix Shell
          • Viewing the Unix Tree
          • Traversing the Unix Tree
          • Editing the Unix Tree
          • Searching the Unix Tree
      • Files
        • Viewing File Contents
        • Creating and Editing Files
        • Manipulating Files
        • Symbolic Links
        • File Ownership
          • How Unix File Ownership Works
          • Change File Ownership and Permissions
        • File Transfer (in-progress)
        • File Storage and Compression
      • Getting System Information
      • Writing Scripts
      • Schedule Scripts Using Crontab
    • Advanced Utilization of IGB Computational Resources
      • High Performance Computing Clusters
      • Slurm
        • Checking the Status of Computing Nodes
        • Submitting Jobs / Slurm Scripts
        • Interactive Sessions
      • Package Management
        • The System Package Manager
        • Environment Modules
        • Conda Environments
      • SSH Port Forwarding
        • SSH Port Forwarding Jupyter Notebooks
      • Containerization
        • Docker
          • Docker Installation
          • Running Docker Images
          • Building Docker Images
        • Singularity
          • Differences from Docker
          • Running Images in Singularity
      • Running Nextflow / nf-core Pipelines
    • Python
      • Introduction to Python for Biologists
        • Interactive Python
        • Types
          • Strings
          • Lists
          • Tuples
          • Dictionaries
        • Control Flow
        • Loops
          • For Loops
          • While Loops
        • Control Flows and Loops
        • Storing Programs for Re-use
        • Reading and Writing Files
        • Functions
      • Biopython
        • About Biopython
        • Quick Start
          • Basic Sequence Analyses
          • SeqRecord
          • Sequence IO
          • Exploration of Entrez Databases
        • Example Projects
          • Coronavirus Exploration
          • Translating a eukaryotic FASTA file of CDS entries
        • Further Resources
      • Machine Learning with Python
        • About Machine Learning
        • Hands-On
          • Project Introduction
          • Supervised Approaches
            • The Logistic Regression Model
            • K-Nearest Neighbors
          • Unsupervised Approaches
            • K-Means Clustering
          • Further Resources
      • Data Processing with Python
        • Pandas
          • About Pandas
          • Making DataFrames
          • Inspecting DataFrames
          • Slicing DataFrames
          • Selecting from DataFrames
          • Editing DataFrames
        • Matplotlib
          • About Matplotlib
          • Basic Plotting
          • Advanced Plotting
        • Seaborn
          • About Seaborn
          • Basic Plotting
          • Visualizing Statistics
          • Visualizing Proteomics Data
          • Visualizing RNAseq Data
    • R
      • Intro to R
        • Before We Start
        • Getting to Know R
        • Variables in R
        • Functions in R
        • Data Manipulation
        • Simple Statistics in R
        • Basic Plotting in R
        • Advanced Plotting in R
        • Writing Figures to a File
        • Further Resources
    • Version Control with Git
      • About Version Control
      • Setting up Git
      • Creating a Repository
      • Tracking Changes
        • Exercises
      • Exploring History
        • Exercises
      • Ignoring Things
      • Remotes in Github
      • Collaborating
      • Conflicts
      • Open Science
      • Licensing
      • Citation
      • Hosting
      • Supplemental
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  1. Mini Courses
  2. Version Control with Git

Licensing

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Last updated 1 year ago

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About Licensing

When a repository with source code, a manuscript or other creative works becomes public, it should include a file LICENSE or LICENSE.txt in the base directory of the repository that clearly states under which license the content is being made available. This is because creative works are automatically eligible for intellectual property (and thus copyright) protection. Reusing creative works without a license is dangerous, because the copyright holders could sue you for copyright infringement.

A license solves this problem by granting rights to others (the licensees) that they would otherwise not have. What rights are being granted under which conditions differs, often only slightly, from one license to another. In practice, a few licenses are by far the most popular, and will help you find a common license that suits your needs. Important considerations include:

  • Whether you want to address patent rights.

  • Whether you require people distributing derivative works to also distribute their source code.

  • Whether the content you are licensing is source code.

  • Whether you want to license the code at all.

Choosing a license that is in common use makes life easier for contributors and users, because they are more likely to already be familiar with the license and don’t have to wade through a bunch of jargon to decide if they’re ok with it. The and both maintain lists of licenses which are good choices.

provides an excellent overview of licensing and licensing options from the perspective of scientists who also write code.

At the end of the day what matters is that there is a clear statement as to what the license is. Also, the license is best chosen from the get-go, even if for a repository that is not public. Pushing off the decision only makes it more complicated later, because each time a new collaborator starts contributing, they, too, hold copyright and will thus need to be asked for approval once a license is chosen.

  • Can I Use Open License?

Find out whether you are allowed to apply an open license to your software. Can you do this unilaterally, or do you need permission from someone in your institution? If so, who?

  • What licenses have I already accepted?

Many of the software tools we use on a daily basis (including in this workshop) are released as open-source software. Pick a project on GitHub from the list below, or one of your own choosing. Find its license (usually in a file called LICENSE or COPYING) and talk about how it restricts your use of the software. Is it one of the licenses discussed in this session? How is it different?

  • , the source-code management tool

  • , the standard implementation of the Python language

  • , the project behind the web-based Python notebooks we’ll be using

  • , a real-time collaborative editor

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Open Source Initiative
Free Software Foundation
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Git
CPython
Jupyter
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