Data organization

Supported source data structures

Out of the box, BIDScoin requires that the source data repository is organized according to a subject/[session]/data structure (the session subfolder is always optional). The data folder(s) can be structured in various ways (depending on the plugin and/or dataformat), as illustrated by the following examples:

1. A DICOM Series layout

The data folder is organized in multiple series subfolders, each of which that contains a single data type that is typically acquired in a single run – a.k.a ‘Series’ in DICOM speak. This is how users receive their data from the (Siemens) scanners at the DCCN:

sourcedata
|-- sub-001
|   |-- ses-mri01
|   |   |-- 001-localizer
|   |   |   |-- 00001_1.3.12.2.1107.5.2.19.45416.2017121914582956872274162.IMA
|   |   |   |-- 00002_1.3.12.2.1107.5.2.19.45416.2017121914583757650874172.IMA
|   |   |   `-- 00003_1.3.12.2.1107.5.2.19.45416.2017121914583358068374167.IMA
|   |   |
|   |   |-- 002-t1_mprage_sag_p2_iso_1.0
|   |   |   |-- 00002_1.3.12.2.1107.5.2.19.45416.2017121915051526005675150.IMA
|   |   |   |-- 00003_1.3.12.2.1107.5.2.19.45416.2017121915051520026075138.IMA
|   |   |   |-- 00004_1.3.12.2.1107.5.2.19.45416.2017121915051515689275130.IMA
|   |   |   [..]
|   |   [..]
|   |
|   `-- ses-mri02
|       |-- 001-localizer
|       |   |-- 00001_1.3.12.2.1107.5.2.19.45416.2017121914582956872274162.IMA
|       |   |-- 00002_1.3.12.2.1107.5.2.19.45416.2017121914583757650874172.IMA
|       |   `-- 00003_1.3.12.2.1107.5.2.19.45416.2017121914583358068374167.IMA
|       [..]
|
|-- sub-002
|   `-- ses-mri01
|       |-- 001-localizer
|       |   |-- 00001_1.3.12.2.1107.5.2.19.45416.2017121914582956872274162.IMA
|       |   |-- 00002_1.3.12.2.1107.5.2.19.45416.2017121914583757650874172.IMA
|       |   `-- 00003_1.3.12.2.1107.5.2.19.45416.2017121914583358068374167.IMA
|       [..]
[..]

2. A DICOMDIR layout

The data folder contains a DICOMDIR file and multiple subfolders. A DICOMDIR is dictionary-file that indicates the various places where the DICOM files are stored. DICOMDIRs are often used in clinical settings and may look like this (example is without the optional session subfolders):

  sourcedata
  |-- sub-001
  |   |-- DICOM
  |   |   `-- 00001EE9
  |   |       `-- AAFC99B8
  |   |           `-- AA547EAB
  |   |               |-- 00000025
  |   |               |   |-- EE008C45
  |   |               |   |-- EE027F55
  |   |               |   |-- EE03D17C
  |   |               |   [..]
  |   |               |
  |   |               |-- 000000B4
  |   |               |   |-- EE07CCDA
  |   |               |   |-- EE0E0701
  |   |               |   |-- EE0E200A
  |   |               |   [..]
  |   |               [..]
  |   `-- DICOMDIR
  |
  |-- sub-002
  |   [..]
  [..]

The above organization of one DICOMDIR file per subject or session is supported out of the box by the bidscoiner and bidsmapper. If you have a single multi-subject DICOMDIR file for your entire repository you can reorganize your data by running the `dicomsort <./utilities.html#dicomsort>`__ utility beforehand.

3. A flat DICOM layout

In a flat DICOM layout the data folder contains all the DICOM files of all the different Series without any subfolders. This layout is sometimes used when exporting data in clinical settings (NB: in this example, non-default ‘pat^’ and ‘ses^’ subject/session prefixes are used):

sourcedata
|-- pat^001
|   `-- ses^01
|       |-- IM_0001.dcm
|       |-- IM_0002.dcm
|       |-- IM_0003.dcm
|       [..]
|
|-- pat^002
|   `-- ses^01
|       |-- IM_0001.dcm
|       |-- IM_0002.dcm
|       |-- IM_0003.dcm
|       [..]
[..]

4. A (S)PAR/REC layout

All SPAR(XML)/PAR/REC files of all the different Series are contained in the data folder (without subfolders). This layout is how users often export their data from Philips scanners in research settings (optional json sidecar files were added in this example to complement the (S)PAR-files):

sourcedata
|-- sub-001
|   `-- ses-mri01
|       |-- TCHC_066_1_WIP_Hanneke_Block_2_SENSE_4_1.PAR
|       |-- TCHC_066_1_WIP_Hanneke_Block_2_SENSE_4_1.REC
|       |-- TCHC_066_1_WIP_Hanneke_Block_2_SENSE_4_1.json
|       |-- TCHC_066_1_WIP_IDED_SENSE_6_1.PAR
|       |-- TCHC_066_1_WIP_IDED_SENSE_6_1.REC
|       |-- TCHC_066_1_WIP_IDED_SENSE_6_1.json
|       [..]
|
|-- sub-002
|   `-- ses-mri01
|       |-- TCHC_066_1_WIP_Hanneke_Block_2_SENSE_4_1.PAR
|       |-- TCHC_066_1_WIP_Hanneke_Block_2_SENSE_4_1.REC
|       |-- TCHC_066_1_WIP_Hanneke_Block_2_SENSE_4_1.json
|       |-- TCHC_066_1_WIP_IDED_SENSE_6_1.PAR
|       |-- TCHC_066_1_WIP_IDED_SENSE_6_1.REC
|       |-- TCHC_066_1_WIP_IDED_SENSE_6_1.json
|       [..]
[..]

5. Miscellaneous layouts

The above layouts are supported by the (default) dcm2niix2bids plugin. The other pre-installed plugins search the data folder recursively for source files. For instance, the nested mix of NIfTI and MRS source data in the example below can be converted to BIDS using the nibabel2bids plugin in combination with the spec2nii2bids plugin (NB: example is with a non-default ‘’ (empty) subject prefix):

sourcedata
|-- 001
|   |-- anat
|   |   `-- 35-365_t1_structural_20150418_03.nii
|   |   `-- 35-365_t1_structural_20150418_03.json
|   |-- met
|   |   |-- 35-365_MRS_ACC_supressed_20150418_04.SDAT
|   |   `-- 35-365_MRS_ACC_supressed_20150418_04.SPAR
|   `-- water
|       |-- 35-365_MRS_ACC_20150418_05.SDAT
|       `-- 35-365_MRS_ACC_20150418_05.SPAR
|
|-- 002
|   `-- 35-365.tar.gz
|
|-- 003
|   |-- TCHC_066_1_WIP_Hanneke_Block_2_SENSE_4_1.nii.gz
|   |-- TCHC_066_1_WIP_Hanneke_Block_2_SENSE_4_1.json
|   [..]
[..]

Note

You can store your session data in any of the above data layouts as zipped (.zip) or tarzipped (e.g. .tar.gz) archive files. BIDScoin workflow tools will automatically unpack/unzip those archive files in a temporary folder and then process your session data from there. For flat/DICOMDIR data, BIDScoin tools (i.e. the bidsmapper and the bidscoiner) will automatically run dicomsort in a temporary folder to sort them in seriesfolders. Depending on the data and file system, repeatedly unzipping data in the workflow may come with a significant processing speed penalty.

Tip

BIDScoin plugins will typically skip (Linux-style hidden) files and folders of which the name starts with a . (dot) character. You can use this feature to flexibly omit subjects, sessions or runs from your bids repository, for instance when you restarted an MRI scan because something went wrong with the stimulus presentation and you don’t want that data to be converted and enumerated as run-1, run-2.

Recommended data acquisition conventions

BIDScoin can automatically recognize source datatypes on the basis of it’s properties and attributes. Typically, in the DCCN users name their MR scan protocols in a meaningful way, which is therefore used as a basis for intelligent source datatype identification. For instance, if a functional fmri protocol is named “StopTask” or “fMRI_Stroop”, the default bidsmap_dccn template will yield a positive ‘func/bold’ match, as it has the “task” and “fMRI” keywords in it’s run-item regular expression: {ProtocolName: (?i).*(f.?MRI|task|BOLD|func|rest|RSN|CMRR.*_TR).*}. Similarly, anatomical scans that have T1w or MPRAGE in their protocol name are identified as anat/T1w items, and field maps that have fmap, fieldmap or B0map in their protocol name are identified as field maps. On the other hand, if a functional scan is just named Stop, the datatype cannot be correctly identified (at least not by the default template) and needs to be manually changed in the bidseditor from extra_data to func. A robust way to acquire and convert your data is hence to use (BIDS-like) descriptive names for your protocols, or for any other attribute or property (such as filenames) that you may use to manage your data. For more details and keywords, see e.g. the DCCN template bidsmap.