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CHANGELOG.md

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Changelog

All notable changes to this project between releases will be documented in this file.

v0.13 (XX. XX. 2020) -- Towards a tetralogy!

Handbook release matching the release of DataLad v0.13.0 With contributions from Dorian Pustina, Sarah Oliveira, Tristan Glatard, Hamzah Hamid Baagil, Giulia Ippoliti, Yaroslav Halchenko, Alex Waite, and Michael Hanke -- thank you!

Refactoring or deletions

  • RF: Replace datalad publish with datalad push (#412)
  • RF: The Basics part was split into a Basics and Advanced part (#450). The chapters "Advanced Options" and "Go big or go home" have been moved/added there.
  • Installation instructions for Windows subsystem for linux have been removed (#397)

Additions

Introduction

  • Installation instructions for rpm-based Linux distributions were added (#435)
  • A "user-type" overview now serves as a guide through the handbook (#403)

Basics

  • A stand-alone section on datalad push summarizes all previous publishing-related information (#417)
  • A section for collecting gists (nifty code snippets for various tasks) is added to the chapter on help(#445)
  • datalad drop is introduced in the first chapter (#463)
  • Gin's new feature of anonymous read-only access to datasets is now mentioned in the chapter on using third party infrastructure(#456)
  • The section on getting help started to collect and explain common warnings and error messages (#418)

Advanced

Usecases

Miscellaneous additions

  • Introduction of a system to improve intersphinx linkage between the handbook and the technical docs & docstrings of DataLad (#377)
  • Various improvements to the PDF version of the handbook (#367)
  • Major toctree restructuring: Chapter-wise toctrees (#367), robustified URLs (#457)
  • Addition of short, README-ready explanations of DataLad datasets for published projects (#370)
  • Redirections are now possible, using a ?<label> element after handbook.datalad.org/r.html (#518)
  • (Almost) complete correspondence between HTML and PDF part, chapter, and section labeling (#500)

v0.12 (Jan. 11 2020) -- A good weekend read

Beta stage release matching the release of datalad v0.12.0.

Refactoring or deletions

  • RF: Replace datalad install with datalad clone (#326)

Additions

Introduction

  • High-level, one page description "What you really need to know" about DataLad (#295)

Basics

  • The DataLad Cheatsheet (#157)

  • Chapter "One step further" with content on advanced dataset nesting (#226) and computational reproducibility with the datalad-containers extension (#242)

  • Chapter "Further options" with content on DataLad's result hooks (#304), an overview on DataLad's extensions (#242), and how to keep clean datasets despite untracked contents (#84)

  • Chapter "Third party infrastructure" on how to use various hosting services to share DataLad datasets, with concrete demonstrations/step-by-step instructions of sharing via Dropbox and GIN (#111)

  • Section "Frequently Asked Questions" (#239)

  • Section "Back and forth in time" on interacting with dataset history with Git tools/commands (#106)

  • Section "YODA-compliant data analysis project" with an example data science project (including Python API) (#226)

  • Include datalad download-url in first chapter to emphasize provenance capture abilities of DataLad (#294)

Usecases

  • Use case "An automatically reproducible analysis of public neuroimaging data" (#205)

  • Use case "Building a scalable data storage for scientific computing" (#223)

Miscellaneous additions

  • Adjust contents to autorunrecord update to record a flexible set of code snippets in "casts" for live demonstrations. Add cast associations for existing contents with speakernotes (#219)

  • Additional book segment "Code lists from chapters" with code lists used for workshops (#273

  • Illustrations from undraw.co (starting in #329)

  • Tagged "showroom" repositories with branches reflecting dataset states at different book sections (#341)

v0.1 (Oct. 10 2019) -- A lazy afternoon read

Alpha stage release with handbook content covering most of the core commands.

Additions

Basics

  • Chapter "DataLad datasets" on local version control (create, save, status, install)

  • Chapter "DataLad, Run!" on reproducible execution with datalad run and datalad rerun

  • Chapter "Under the hood: git-annex" on the dataset annex and the text2git procedure

  • Chapter "Collaboration" on sharing datasets (on the same computational infrastructure), siblings, and updating.

  • Chapter "Tuning datasets to your needs" on various configurations

  • Chapter "Help yourself" on common file system operations and on help.

  • Chapter "Make the most out of datasets" about the YODA principles

Usecases

  • Use case "A typical collaborative data management workflow"

  • Use case "Basic provenance tracking"

  • Use case "Basic provenance tracking"

  • Use case "Student supervision in a research project"