All notable changes to this project between releases will be documented in this file.
A handbook release matching (delayed) the release of DataLad v0.18.0. This release contains notable changes resulting from a Handbook hackathon in December 2022. It also increases the required version of DataLad to 0.17
All over the handbook, version notes or information relating to datalad versions lower than 0.17 were removed (#905)
- A new standalone chapter about datalad extensions was added, and sections on datalad-catalog (#917), datalad-metalad (#930), and datalad-gooey were included.
- A new standalone chapter about datalad extensions was added, and sections on datalad-catalog (#917), datalad-metalad (#930), and datalad-gooey were included.
- The Cheatsheet was updated with modern commands (#912)
- A new use case about encrypted workflows is now part of the handbook (#895)
- The Makefile in the source repository received a more intuitive and fine-grained structure (#901)
- The handbook has gained an Appveyor configuration that allows building the entire Basis and Beyond Basics parts from scratch, and allows an export of generated code snippets. This makes builds on local machines obsolete for contributors that don't want to go through this trouble (#908)
- the handbook now has a tool to report readthedocs metrics for authenticated and authorized users (#902)
Handbook release matching the release of DataLad v0.17.0, which was for the most part only an internal change to a different testing framework (pytest instead of nose)
It includes contributions the new contributors @Arshitha, @ajveltri22, @complexbrains, @jkosciessa, @candleindark, and @asmacdo, as well as contributions from established contributors @mslw, @sappelhoff, @kimsin98, @adswa, @yarikoptic.
- A new walkthrough for the neurohackademy was added (#852)
- The installation instructions were updated for Windows (#872)(#868), conda (#869), and Mac (#875)(#859)(#846)
- The midterm project scripts was improved and made functional again (#854), (#853)
- The GitLFS section now mentions a publication dependency for automation (#842)
- The
alias
parameter ofcreate-sibling-ria
is now mentioned ([#855][])
- The JS-based redirection of the handbook now works around an unintentional prefix-redirection glitch of readthedocs (#880)
- The GitHub repository gained a codespell workflow (#892)
Handbook release matching the release of DataLad v0.16.0.
This release contains a number of updates for respective changes in DataLad 0.16
's API, including the overhaul of existing commands, reimplementations of commands, and additional commands.
It includes contributions the new contributors @eort, @mslw, @tguiot, @jhpb7 and @eltociear, as well as contributions from established contributors @jsheunis, @mih, @adswa, @yarikoptic, and @Remi-Gau.
- Installation instructions on Windows now recommend git-annex'es filter-process configuration for performance improvements ([#791][])
- The chapter on publishing datasets was overhauled and now includes a general overview of publishing routines and hosting service differences. ([#762][])
- Content on
datalad run
now mentions its superglob abilities ([#692][]) and how to glob across directories hierarchies with earlier datalad versions ([#785][]) - A few fixes and improvements to the section on publishing datasets to Gin ([#793][])
- The enki walkthrough links the FAIRly big paper and tutorial as an improved alternative ([#783][])
- A new chapter contains a section on contributing to DataLad and DataLad's design docs ([#782][])
- A new section guides through the process of creating your own extensions ([#812][])
- The section on configuring additional data providers now includes content on DataLad 0.16's credential integration with Git ([#814][])
- A new general section on how to create interoperable file names was added ([#796][])
- The GitHub project of the handbook now uses templates for easier issue generation. ([#768][])
- A number of CSS improvements fix the rendering of bullet points ([#770][])
- The ML use case was minified to speed up builds ([#790][])
- A new code list for the DGPA workshop was added ([#820][])
Handbook release matching the release of DataLad v0.15.0. This release contains major improvements of the handbook's LaTeX backbone.
With thanks to the new contributors @oesteban, @AKSoo, and @jsheunis, and established contributors @eknahm, @kyleam, @RemiGau, @bpoldrack, @yarikoptic, @effigies @sappelhof, @lilikapa, @arokem
- The deprecated --no-storage-sibling parameter was removed from the RIA store chapter (#641)
- The installation instructions were updated for Python (#651) and Mac (#675), and overall improved (#682)
- The help section was extended with a note on asyncio-related errors in Jupyter (#646) and information on line-endings and and autocrfl true configurations for windows users (#723)
- The section on publishing with Gin was amended with content on using Gin as an autoenabled special remote (#707)
- The chapter on run now mentions its
--assume-ready
and ``--dry-runparameter ([#699][])
, (#724) - There now is a FAQ on how to fix GitHub displaying the git-annex branch as the default (#722)
- A new chapter on Publishing to S3 walks through publishing to a public S3 bucket (#721)
- A wide range of improvements in the LaTeX rendering of the handbook (#647), (#648), (#650), (#655), (#656), (#657), (#658), (#658), (#660), (#661), (#662), (#663), (#665), (#666), (#679), (#684), (#685), (#694), (#759)
- A number of textual changes to improve the PDF rendering of the handbook ([#48][]), (#669), (#670), (#671), (#678), (#680), (#691), (#704)
- New artwork (#667), (#672),
- A new code list for a Repronim Workshop in Yale (#693)
- Continuous integration was migrated to GitHub actions (#703)
- The Zenodo record now resolves to the latest version (#717)
- The code blocks now have copy-buttons (#615)
- A monthly linkchecker was implemented to better catch unresolving URLs (#743)
Handbook release matching the release of DataLad v0.14.0. Like the software release, this handbook release improves the situation on/for Windows systems starkly from what we had before. With contributions from Tristan Glatard, Ariel Rokem, Remi Gau, Surya Teja Togaru, Judith Bomba, Konrad Hinsen, Wu Jianxiao, Małgorzata Wierzba, Stefan Appelhoff, and Michael Joseph -- thank you!
- Overhaul Windows installation instructions (#588)
- Adjustments for GitHub's user-password deprecation (#626), (#592)
- git-annex installations with custom built git-annex with MagicMime support (#603)
- A quick-start guide for OpenNeuro (#585)
- Disambiguation on configurations (#627) with thanks to John Lee for the issue at datalad
- A new section on how to debug and troubleshoot problems - with thanks to Tristan Glatard for the idea and contributions ([#538][])
- A chapter on large-scale fair processing with parallel datalad-run calls (#591)
- A new section on configuring subdataset clone candidates and their priority (#548)
- A new chapter/section that compares the tool DVC to DataLad (#569)
- Addition of a machine-learning application with DataLad (#581)
- Addition on Human Connectome Project (HCP) AWS credentials (thanks to Michael Joseph) (#622)
- Addition of a hands-on tutorial for reproducible papers (#608), with thanks to Małgorzata Wierzba for feedback and contributions
- A variety of code lists and introductions (#630), (#613)
- A few new permalinks: git-lfs (#624), MPIB intro (#614)
- A new expandable section "Windows workaround" for Windows-specific notes and explanations(#532)
- Large amount of Windows adjustments in the Basics (#588)
- FAQs on copying locked files out of datasets, and on caveats with the BIDS validator - with thanks to Remi Gau (#570), (#562)
- The handbook's GitHub repository received a welcome bot (with thanks to The Turing Way project for CC-BY illustrations), and a "Discussions" Forum
- The handbook's frontpage links to the cheat sheet with a nice illustration (#578)
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!
- RF: Replace
datalad publish
withdatalad 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)
- Installation instructions for rpm-based Linux distributions were added (#435)
- A "user-type" overview now serves as a guide through the handbook (#403)
- 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)
- A new chapter on scaling up with DataLad was added (#414)
- A section on configuring custom data access was added to the chapter "Advanced Options"(#440)
- The extension overview has been updated to a complete overview (#477)
- A new Usecase Scaling Up: Managing 80TB and 15 Million files from the HCP release was added (#225)
- Giulia Ippoliti contributed the Usecase Using Globus as a data store for the Canadian Open Neuroscience Portal (opened in #421, merged as #479)
- 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 afterhandbook.datalad.org/r.html
(#518) - (Almost) complete correspondence between HTML and PDF part, chapter, and section labeling (#500)
Beta stage release matching the release of datalad v0.12.0.
- RF: Replace
datalad install
withdatalad clone
(#326)
- High-level, one page description "What you really need to know" about DataLad (#295)
-
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)
-
Use case "An automatically reproducible analysis of public neuroimaging data" (#205)
-
Use case "Building a scalable data storage for scientific computing" (#223)
-
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
-
Tagged "showroom" repositories with branches reflecting dataset states at different book sections (#341)
Alpha stage release with handbook content covering most of the core commands.
-
Chapter "DataLad datasets" on local version control (create, save, status, install)
-
Chapter "DataLad, Run!" on reproducible execution with
datalad run
anddatalad 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
-
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"