Home Fundamentals Research Data Management FAIR Data Principles Metadata Ontologies Data Sharing Data Publications Data Management Plan Version Control & Git Public Data Repositories Persistent Identifiers Electronic Lab Notebooks (ELN) DataPLANT Implementations Annotated Research Context User Journey ARC specification ARC Commander QuickStart QuickStart (Experts) Swate QuickStart Walk-through Best Practices For Data Annotation DataHUB DataPLAN Ontology Service Landscape ARC Commander Manual Setup Git Installation ARC Commander Installation Windows MacOS Linux ARC Commander DataHUB Access Before we start Central Functions Initialize Clone Connect Synchronize Configure Branch ISA Metadata Functions ISA Metadata Investigation Study Assay Update Export ARCitect Manual Installation - Windows Installation - macOS Installation - Linux QuickStart Swate Manual Swate Installation Excel Browser Excel Desktop Windows – installer Windows – manually macOS – manually Organization-wide Core Features Annotation tables Building blocks Building Block Types Adding a Building Block Using Units with Building Blocks Filling cells with ontology terms Advanced Term Search Templates File Picker Expert Features Contribute Templates ISA-JSON DataHUB Manual Overview User Settings Generate a Personal Access Token (PAT) Projects Panel ARC Panel Forks Working with files ARC Settings ARC Wiki Groups Panel Create a new user group Data publications Passing Continuous Quality Control Submitting ARCs with ARChigator Track publication status Use your DOIs Guides ARC User Journey Create your ARC ARC Commander QuickStart ARC Commander QuickStart (Experts) ARCitect QuickStart Annotate Data in your ARC Annotation Principles ISA File Types Best Practices For Data Annotation Swate QuickStart Swate Walk-through Share your ARC Register at the DataHUB Invite collaborators to your ARC Recommended ARC practices Syncing recommendation Keep files from syncing to the DataHUB Working with large data files Adding external data to the ARC ARCs in Enabling Platforms Publication to ARC Contribute Swate Templates Knowledge Base Teaching Materials Slides DataPLANT Annotated Research Context Videos Start Your ARC Series Events 2023 Nov: CEPLAS PhD Module Oct: CSCS CEPLAS Start Your ARC Sept: MibiNet CEPLAS Start Your ARC July: RPTU Summer School on RDM July: Data Steward Circle May: CEPLAS Start Your ARC Series Frequently Asked Questions

Working with large data files

last updated at 2023-06-28 About this guide

In this guide we show you how you can actively handle large data files in your ARC.

UserAdvanced ModeTutorial

⚠️ This guide presents an interim solution. We are working on a more user-friendly implementation.

Before we can start

☑️ You have created an ARC before using the ARC Commander
☑️ The latest version of the ARC Commander is installed on your computer
☑️ You have a DataPLANT account
☑️ Your computer is linked to the DataHUB via personal access token

Large File Storage (LFS)

ARCs and the DataHUB come with a mechanism to sync and store large files called Large File Storage (LFS). LFS is an efficient way to store your large data files. These files are called "LFS objects". Rather than checking every file during every arc sync, the ARC Commander first checks wether there was a change at all. And only if this is the case, it scans what was changed. This way it saves time and computing power compared to always scanning all large files for possible changes.

By default, the ARC Commander tracks the following files via LFS:

  1. All files stored in an assay's dataset folder, and
  2. All files with a size larger than 150 MB.

The threshold of 150 MB can easily be adjusted using the ARC Commander. For instance, if you want to increase it to 250 MB (i.e. 250000000 bytes), run

arc config set -g -n "general.gitlfsbytethreshold" -v "250000000"

💡 The LFS system is also the reason why git LFS needs to be installed prior to using the ARC Commander.

Track files via LFS

In addition to the defaults, you can also actively choose, which files to track via LFS.

  1. Update your local ARC via arc sync
  2. Add large files or folders by copying or moving them to your ARC
  3. Track files via
git lfs track "<path/to/FolderWithLargeFiles/**>" git add .gitattributes
  1. Sync your ARC to the DataHUB via arc sync
  2. Open your ARC in the DataHUB and navigate to the folder with LFS objects and see them flagged as "LFS".
Downloading an ARC without large data files

Sometimes you may want to download your ARC to a smaller computer, where you do not need a full copy of your ARC including all its large data files. For instance, you just want to work with smaller derived data sets or want to update ISA metadata. In this case, you can add the -n or --nolfs flag to your arc get command:

arc get --nolfs -r https://git.nfdi4plants.org/<YourUser>/<YourARC>

For example, have a look at the example ARC https://git.nfdi4plants.org/brilator/Facultative-CAM-in-Talinum. In the DataHUB this ARC has a storage volume of ~11GB, a lot of which comes from the large RNASeq data files flagged as "LFS".

You can download this ARC without the LFS objects via

arc get --nolfs -r https://git.nfdi4plants.org/brilator/Facultative-CAM-in-Talinum

⚠️ Even without LFS objects this ARC still takes ~1GB of space.

Keep LFS objects from syncing

To make sure that also during an upcoming arc sync, LFS objects are not downloaded, you need to change the LFS option on that particular machine for this ARC. Navigate to your ARC (Facultative-CAM-in-Talinum) and execute the following two commands:

git config --local filter.lfs.smudge "git-lfs smudge --skip -- %f" git config --local filter.lfs.process "git-lfs filter-process --skip" Selectively download large files

If at some point you wish to selectively download one or more of the LFS objects of your ARC to that machine, you can do so via git lfs pull --include "<path/to/fileOrFolder>"

For example, the following command will download one of the large RNASeq data files.

git lfs pull --include "assays/Talinum_RNASeq_minimal/dataset/DB_097_CAMMD_CAGATC_L001_R1_001.fastq.gz"

DataPLANT Support

Besides these technical solutions, DataPLANT supports you with community-engaged data stewardship. For further assistance, feel free to reach out via our helpdesk or by contacting us directly .
Contribution Guide 📖
✏️ Edit this page