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ID: 229764 : Preprocessed Image Data
ID: 229767 : Structural MRI
ID: 229794 : This package is the recommended starting point for structural analyses and contains files precisely aligned across subjects using the MSMAll multi-modal surface registration, plus a session report file that provides an overview of the usable imaging data collected during the participant's visit. It contains outputs of the HCP Structural Preprocessing pipeline, which is the result of applying PreFreeSurferPipeline, FreeSurferPipeline, PostFreeSurferPipeline and MSMAllPipeline.
ID: 229795 : This package contains structural files coarsely aligned across subjects using the MSMSulc folding surface registration, plus a session report file that provides an overview of the usable imaging data collected during the participant's visit. It contains outputs of the HCP Structural Preprocessing pipeline, which is the result of applying PreFreeSurferPipeline, FreeSurferPipeline, and PostFreeSurferPipeline.
ID: 229796 : This package contains the actual outputs from the FreeSurferPipeline stage of the HCP Structural Preprocessing, in FreeSurfer's native file formats and directory structure
ID: 229797 : This package contains additional files related to QC on structural preprocessing outputs and other extra files that may be useful to select users. It contains outputs of the HCP Structural Preprocessing pipeline, which is the result of applying PreFreeSurferPipeline, FreeSurferPipeline, PostFreeSurferPipeline and MSMAllPipeline.
ID: 229768 : Resting State fMRI
ID: 229798 : This package is the recommended starting point for rfMRI analyses and contains cleaned files precisely aligned across subjects using the MSMAll multi-modal surface registration. It contains outputs of HCP Functional Preprocessing for resting state scans, which is the result of applying GenericfMRIVolumeProcessingPipeline, GenericfMRISurfaceProcessingPipeline, hcp_fix_multi_run, and MSMAllPipeline.
ID: 229799 : This package contains cleaned files coarsely aligned across subjects using the MSMSulc folding surface registration. It contains outputs of HCP Functional Preprocessing for resting state scans, which is the result of applying GenericfMRIVolumeProcessingPipeline, GenericfMRISurfaceProcessingPipeline, and hcp_fix_multi_run.
ID: 229800 : This package contains cleaned rfMRI files poorly aligned across subjects using nonlinear volume registration. It contains outputs of HCP Functional Preprocessing for resting state scans, which is the result of applying GenericfMRIVolumeProcessingPipeline and hcp_fix_multi_run.
ID: 229801 : This package contains uncleaned resting state data of all registration types for use in testing alternative data cleanup strategies. It contains outputs of HCP Functional Preprocessing for resting state scans, which is the result of applying GenericfMRIVolumeProcessingPipeline, GenericfMRISurfaceProcessingPipeline, and MSMAllPipeline.
ID: 229802 : This package contains additional files related to rfMRI data cleanup and other extra files that may be useful to select users. It contains outputs of HCP Functional Preprocessing for resting state scans, which is the result of applying GenericfMRIVolumeProcessingPipeline, GenericfMRISurfaceProcessingPipeline, hcp_fix_multi_run, and MSMAllPipeline.
ID: 229769 : Task fMRI
ID: 229803 : This package is the recommended starting point for CARIT tfMRI analyses and contains cleaned files precisely aligned across subjects using the MSMAll multi-modal surface registration. It contains outputs of HCP Functional Preprocessing for the CARIT (Go/NoGo Conditioned Approach Response Inhibition Task, with no reward history component) tfMRI scan, which is the result of applying GenericfMRIVolumeProcessingPipeline, GenericfMRISurfaceProcessingPipeline, hcp_fix_multi_run, and MSMAllPipeline.
ID: 229804 : This package contains cleaned CARIT tfMRI files coarsely aligned across subjects using the MSMSulc folding surface registration. It contains outputs of HCP Functional Preprocessing for the CARIT (Go/NoGo Conditioned Approach Response Inhibition Task, with no reward history component) tfMRI scan, which is the result of applying GenericfMRIVolumeProcessingPipeline, GenericfMRISurfaceProcessingPipeline, and hcp_fix_multi_run.
ID: 229805 : This package contains cleaned CARIT tfMRI files poorly aligned across subjects using nonlinear volume registration. It contains outputs of HCP Functional Preprocessing for the CARIT (Go/NoGo Conditioned Approach Response Inhibition Task, with no reward history component) tfMRI scan, which is the result of applying the GenericfMRIVolumeProcessingPipeline and hcp_fix_multi_run.
ID: 229806 : This package contains uncleaned tfMRI CARIT data of all registration types for use in testing alternative data cleanup strategies. It contains outputs of HCP Functional Preprocessing for the CARIT (Go/NoGo Conditioned Approach Response Inhibition Task, with no reward history component) tfMRI scan, which is the result of applying GenericFMRIVolumeProcessingPipeline, GenericfMRISurfaceProcessingPipeline, and MSMAllPipeline
ID: 229807 : This package contains additional CARIT tfMRI files related to data cleanup and other extra files that may be useful to select users. It contains outputs of HCP Functional Preprocessing for the CARIT (Go/NoGo Conditioned Approach Response Inhibition Task, with no reward history component) tfMRI scan, which is the result of applying GenericfMRIVolumeProcessingPipeline, GenericfMRISurfaceProcessingPipeline, hcp_fix_multi_run, and MSMAllPipeline.
ID: 229808 : This package is the recommended starting point for FACENAME tfMRI analyses and contains cleaned files precisely aligned across subjects using the MSMAll multi-modal surface registration. It contains outputs of HCP Functional Preprocessing for the FACENAME (paired-associative memory task) tfMRI scan, which is the result of applying GenericfMRIVolumeProcessingPipeline, GenericfMRISurfaceProcessingPipeline, hcp_fix_multi_run, and MSMAllPipeline.
ID: 229809 : This package contains cleaned FACENAME tfMRI files coarsely aligned across subjects using the MSMSulc folding surface registration. It contains outputs of HCP Functional Preprocessing for the FACENAME (paired-associative memory task) tfMRI scan, which is the result of applying GenericfMRIVolumeProcessingPipeline, GenericfMRISurfaceProcessingPipeline, and hcp_fix_multi_run.
ID: 229810 : This package contains cleaned FACENAME tfMRI files poorly aligned across subjects using nonlinear volume registration. It contains outputs of HCP Functional Preprocessing for the FACENAME (paired-associative memory task) tfMRI scan, which is the result of applying the GenericfMRIVolumeProcessingPipeline and hcp_fix_multi_run.
ID: 229811 : This package contains uncleaned tfMRI FACENAME data of all registration types for use in testing alternative data cleanup strategies. It contains outputs of HCP Functional Preprocessing for the FACENAME (paired-associative memory task) tfMRI scan, which is the result of applying GenericfMRIVolumeProcessingPipeline, GenericfMRISurfaceProcessingPipeline, and MSMAllPipeline.
ID: 229812 : This package contains additional FACENAME tfMRI files related to data cleanup and other extra files that may be useful to select users. It contains outputs of HCP Functional Preprocessing for the FACENAME (paired-associative memory task) tfMRI scan, which is the result of applying GenericfMRIVolumeProcessingPipeline, GenericfMRISurfaceProcessingPipeline, hcp_fix_multi_run, and MSMAllPipeline.
ID: 229813 : This package is the recommended starting point for VISMOTOR tfMRI analyses and contains cleaned files precisely aligned across subjects using the MSMAll multi-modal surface registration. It contains outputs of HCP Functional Preprocessing for the VISMOTOR (simultaneous motor and visual activation task) task scan, which is the result of applying GenericfMRIVolumeProcessingPipeline, GenericfMRISurfaceProcessingPipeline, hcp_fix_multi_run, and MSMAllPipeline.
ID: 229814 : This package contains cleaned VISMOTOR tfMRI files coarsely aligned across subjects using the MSMSulc folding surface registration. It contains outputs of HCP Functional Preprocessing for the VISMOTOR (simultaneous motor and visual activation task) task scan, which is the result of applying GenericfMRIVolumeProcessingPipeline, GenericfMRISurfaceProcessingPipeline, and hcp_fix_multi_run.
ID: 229815 : This package contains cleaned VISMOTOR tfMRI files poorly aligned across subjects using nonlinear volume registration. It contains outputs of HCP Functional Preprocessing for the VISMOTOR (simultaneous motor and visual activation task) task scan, which is the result of applying the GenericfMRIVolumeProcessingPipeline and hcp_fix_multi_run.
ID: 229816 : This package contains uncleaned tfMRI VISMOTOR data of all registration types for use in testing alternative data cleanup strategies. It contains outputs of HCP Functional Preprocessing for the VISMOTOR (simultaneous motor and visual activation task) task scan, which is the result of applying GenericfMRIVolumeProcessingPipeline, GenericfMRISurfaceProcessingPipeline, and MSMAllPipeline.
ID: 229817 : This package contains additional VISMOTOR tfMRI files related to data cleanup and other extra files that may be useful to select users. It contains outputs of HCP Functional Preprocessing for the VISMOTOR (simultaneous motor and visual activation task) task scan, which is the result of applying GenericfMRIVolumeProcessingPipeline, GenericfMRISurfaceProcessingPipeline, hcp_fix_multi_run, and MSMAllPipeline.
ID: 229765 : Unprocessed Image Data
ID: 229774 : This package contains multi-echo MPRAGE (T1 weighted) and T2-SPACE (T2 weighted) scans (in NIFTI format). The T1w image reconstruction of the mean of the first two echoes of the multi-echo T1w scan and the T2w image, both acquired with volumetric navigators (vNav) for real-time motion correction, but collected without Siemen's 'Prescan Normalize' feature, are recommended and were used as the starting point for Structural preprocessing. It also includes the associated navigators for each scan, reconstructions of each of the four separate echoes from the multi-echo T1w scan, reconstructions of the RMS of the four T1w echoes, and a session report file that provides an overview of the usable imaging data collected during the participant's visit.
ID: 229775 : This package contains the dMRI scans (in NIFTI format), bval, and bvec files for the two sets of diffusion sensitizing directions ('dir98' and 'dir99'), each acquired with AP/PA phase encoding, plus SpinEchoFieldMaps and SBRefs.
ID: 229776 : This package contains both pairs of resting state fMRI scans (in NIFTI format), acquired with AP/PA phase encoding, plus SpinEchoFieldMaps, SBRefs, and PsychoPy event timing, Physio files containing pulse oximetry and respiratory traces, and participant eye videos for each run.
ID: 229777 : This package contains the fMRI scan for the CARIT task (in NIFTI format; Go/NoGo Conditioned Approach Response Inhibition Task, with no reward history component), acquired with PA phase encoding, plus SpinEchoFieldMaps, SBRefs, PsychoPy event timing and task modeling files, and Physio files containing pulse oximetry and respiratory traces.
ID: 229778 : This package contains the fMRI scan for the FACENAME task (in NIFTI format; paired-associative memory task), acquired with PA phase encoding, plus SpinEchoFieldMaps, SBRef, PsychoPy event timing and task modeling files, and a Physio file containing pulse oximetry and respiratory traces.
ID: 229779 : This package contains the fMRI scan for the VISMOTOR task (in NIFTI format; simultaneous motor and visual activation task), acquired with PA phase encoding, plus SpinEchoFieldMaps, SBRefs, PsychoPy event timing and task modeling files, and a Physio file containing pulse oximetry and respiratory traces.
ID: 229780 : This package contains the mbPCASLhr scan (in NIFTI format; multiband 2D EPI pseudo-continuous arterial spin labeling with high spatial resolution), plus SpinEchoFieldMaps, PsychoPy event timing and participant eye video for the run.
ID: 229781 : This package contains the turbo-spin-echo high spatial resolution hippocampal structural scan (in NIFTI format), reconstructed both without and with Siemen's 'Prescan Normalize', plus SpinEchoFieldMaps.
ID: 229766 : This package contains contains non-imaging demographic, physical health, clinical, cognitive, and behavioral data for participant’s first study visit (V1). See the Lifespan HCP 2.0 Data Release Reference Manual for details on included measures.
ID: 229782 : Preprocessed Image Data
ID: 229785 : Structural MRI
ID: 229818 : This package is the recommended starting point for structural analyses and contains files precisely aligned across subjects using the MSMAll multi-modal surface registration, plus a session report file that provides an overview of the usable imaging data collected during the participant's visit. It contains outputs of the HCP Structural Preprocessing pipeline, which is the result of applying PreFreeSurferPipeline, FreeSurferPipeline, PostFreeSurferPipeline and MSMAllPipeline.
ID: 229819 : This package contains structural files coarsely aligned across subjects using the MSMSulc folding surface registration, plus a session report file that provides an overview of the usable imaging data collected during the participant's visit. It contains outputs of the HCP Structural Preprocessing pipeline, which is the result of applying PreFreeSurferPipeline, FreeSurferPipeline, and PostFreeSurferPipeline.
ID: 229820 : This package contains the actual outputs from the FreeSurferPipeline stage of the HCP Structural Preprocessing, in FreeSurfer's native file formats and directory structure
ID: 229821 : This package contains additional files related to QC on structural preprocessing outputs and other extra files that may be useful to select users. It contains outputs of the HCP Structural Preprocessing pipeline, which is the result of applying PreFreeSurferPipeline, FreeSurferPipeline, PostFreeSurferPipeline and MSMAllPipeline.
ID: 229786 : Resting State fMRI
ID: 229822 : This package is the recommended starting point for rfMRI analyses and contains cleaned files precisely aligned across subjects using the MSMAll multi-modal surface registration. It contains outputs of HCP Functional Preprocessing for resting state scans, which is the result of applying GenericfMRIVolumeProcessingPipeline, GenericfMRISurfaceProcessingPipeline, hcp_fix_multi_run, and MSMAllPipeline.
ID: 229823 : This package contains cleaned files coarsely aligned across subjects using the MSMSulc folding surface registration. It contains outputs of HCP Functional Preprocessing for resting state scans, which is the result of applying GenericfMRIVolumeProcessingPipeline, GenericfMRISurfaceProcessingPipeline, and hcp_fix_multi_run.
ID: 229824 : This package contains cleaned rfMRI files poorly aligned across subjects using nonlinear volume registration. It contains outputs of HCP Functional Preprocessing for resting state scans, which is the result of applying GenericfMRIVolumeProcessingPipeline and hcp_fix_multi_run.
ID: 229825 : This package contains uncleaned resting state data of all registration types for use in testing alternative data cleanup strategies. It contains outputs of HCP Functional Preprocessing for resting state scans, which is the result of applying GenericfMRIVolumeProcessingPipeline, GenericfMRISurfaceProcessingPipeline, and MSMAllPipeline.
ID: 229826 : This package contains additional files related to rfMRI data cleanup and other extra files that may be useful to select users. It contains outputs of HCP Functional Preprocessing for resting state scans, which is the result of applying GenericfMRIVolumeProcessingPipeline, GenericfMRISurfaceProcessingPipeline, hcp_fix_multi_run, and MSMAllPipeline.
ID: 229787 : Task fMRI
ID: 229827 : This package is the recommended starting point for CARIT tfMRI analyses and contains cleaned files precisely aligned across subjects using the MSMAll multi-modal surface registration. It contains outputs of HCP Functional Preprocessing for CARIT (Go/NoGo Conditioned Approach Response Inhibition Task, with a reward history component from the GUESSING task) tfMRI scans, which is the result of applying GenericfMRIVolumeProcessingPipeline, GenericfMRISurfaceProcessingPipeline, hcp_fix_multi_run, and MSMAllPipeline.
ID: 229828 : This package contains cleaned CARIT tfMRI files coarsely aligned across subjects using the MSMSulc folding surface registration. It contains outputs of HCP Functional Preprocessing for CARIT (Go/NoGo Conditioned Approach Response Inhibition Task, with a reward history component from the GUESSING task) tfMRI scans, which is the result of applying GenericfMRIVolumeProcessingPipeline, GenericfMRISurfaceProcessingPipeline, and hcp_fix_multi_run.
ID: 229829 : This package contains cleaned CARIT tfMRI files poorly aligned across subjects using nonlinear volume registration. It contains outputs of HCP Functional Preprocessing for CARIT (Go/NoGo Conditioned Approach Response Inhibition Task, with a reward history component from the GUESSING task) tfMRI scans, which is the result of applying the GenericfMRIVolumeProcessingPipeline and hcp_fix_multi_run.
ID: 229830 : This package contains uncleaned tfMRI CARIT data of all registration types for use in testing alternative data cleanup strategies. It contains outputs of HCP Functional Preprocessing for CARIT (Go/NoGo Conditioned Approach Response Inhibition Task, with a reward history component from the GUESSING task) tfMRI scans, which is the result of applying GenericFMRIVolumeProcessingPipeline, GenericfMRISurfaceProcessingPipeline, and MSMAllPipeline.
ID: 229831 : This package contains additional CARIT tfMRI files related to data cleanup and other extra files that may be useful to select users. It contains outputs of HCP Functional Preprocessing for CARIT (Go/NoGo Conditioned Approach Response Inhibition Task, with a reward history component from the GUESSING task) tfMRI scans, which is the result of applying GenericfMRIVolumeProcessingPipeline, GenericfMRISurfaceProcessingPipeline, hcp_fix_multi_run, and MSMAllPipeline.
ID: 229841 : This package is the recommended starting point for EMOTION tfMRI analyses and contains cleaned files precisely aligned across subjects using the MSMAll multi-modal surface registration. It contains outputs of HCP Functional Preprocessing for the EMOTION (emotion and face-processing task) tfMRI scan, which is the result of applying GenericfMRIVolumeProcessingPipeline, GenericfMRISurfaceProcessingPipeline, hcp_fix_multi_run, and MSMAllPipeline.
ID: 229832 : This package contains cleaned EMOTION tfMRI files coarsely aligned across subjects using the MSMSulc folding surface registration. It contains outputs of HCP Functional Preprocessing for the EMOTION (emotion and face-processing task) tfMRI scan, which is the result of applying GenericfMRIVolumeProcessingPipeline, GenericfMRISurfaceProcessingPipeline, and hcp_fix_multi_run.
ID: 229833 : This package contains cleaned EMOTION tfMRI files poorly aligned across subjects using nonlinear volume registration. It contains outputs of HCP Functional Preprocessing for the EMOTION (emotion and face-processing task) tfMRI scan, which is the result of applying the GenericfMRIVolumeProcessingPipeline and hcp_fix_multi_run.
ID: 229834 : This package contains uncleaned tfMRI EMOTION data of all registration types for use in testing alternative data cleanup strategies. It contains outputs of HCP Functional Preprocessing for the EMOTION (emotion and face-processing task) tfMRI scan, which is the result of applying GenericfMRIVolumeProcessingPipeline, GenericfMRISurfaceProcessingPipeline, and MSMAllPipeline.
ID: 229835 : This package contains additional EMOTION tfMRI files related to data cleanup and other extra files that may be useful to select users. It contains outputs of HCP Functional Preprocessing for the EMOTION (emotion and face-processing task) tfMRI scan, which is the result of applying GenericfMRIVolumeProcessingPipeline, GenericfMRISurfaceProcessingPipeline, hcp_fix_multi_run, and MSMAllPipeline.
ID: 229836 : This package is the recommended starting point for GUESSING tfMRI analyses and contains cleaned files precisely aligned across subjects using the MSMAll multi-modal surface registration. It contains outputs of HCP Functional Preprocessing for GUESSING (reward, punishment, anticipatory reactivity task) tfMRI scans, which is the result of applying GenericfMRIVolumeProcessingPipeline, GenericfMRISurfaceProcessingPipeline, hcp_fix_multi_run, and MSMAllPipeline.
ID: 229837 : This package contains cleaned GUESSING tfMRI files coarsely aligned across subjects using the MSMSulc folding surface registration. It contains outputs of HCP Functional Preprocessing for GUESSING (reward, punishment, anticipatory reactivity task) tfMRI scans, which is the result of applying GenericfMRIVolumeProcessingPipeline, GenericfMRISurfaceProcessingPipeline, and hcp_fix_multi_run.
ID: 229838 : This package contains cleaned GUESSING tfMRI files poorly aligned across subjects using nonlinear volume registration. It contains outputs of HCP Functional Preprocessing for GUESSING (reward, punishment, anticipatory reactivity task) tfMRI scans, which is the result of applying the GenericfMRIVolumeProcessingPipeline and hcp_fix_multi_run.
ID: 229839 : This package contains uncleaned tfMRI GUESSING data of all registration types for use in testing alternative data cleanup strategies. It contains outputs of HCP Functional Preprocessing for GUESSING (reward, punishment, anticipatory reactivity task) tfMRI scans, which is the result of applying GenericfMRIVolumeProcessingPipeline, GenericfMRISurfaceProcessingPipeline, and MSMAllPipeline.
ID: 229840 : This package contains additional GUESSING tfMRI files related to data cleanup and other extra files that may be useful to select users. It contains outputs of HCP Functional Preprocessing for GUESSING (reward, punishment, anticipatory reactivity task) tfMRI scans, which is the result of applying GenericfMRIVolumeProcessingPipeline, GenericfMRISurfaceProcessingPipeline, hcp_fix_multi_run, and MSMAllPipeline
ID: 229783 : Unprocessed Image Data
ID: 229788 : This package contains multi-echo MPRAGE (T1 weighted) and T2-SPACE (T2 weighted) scans (in NIFTI format). The T1w image reconstruction of the mean of the first two echoes of the multi-echo T1w scan and the T2w image, both acquired with volumetric navigators (vNav) for real-time motion correction, but collected without Siemen's 'Prescan Normalize' feature, are recommended and were used as the starting point for Structural preprocessing. It also includes the associated navigators for each scan, reconstructions of each of the four separate echoes from the multi-echo T1w scan, reconstructions of the RMS of the four T1w echoes, and a session report file that provides an overview of the usable imaging data collected during the participant's visit.
ID: 229789 : This package contains the dMRI scans (in NIFTI format), bval, and bvec files for the two sets of diffusion sensitizing directions ('dir98' and 'dir99'), each acquired with AP/PA phase encoding, plus SpinEchoFieldMaps and SBRefs.
ID: 229790 : This package contains both pairs of resting state fMRI scans (in NIFTI format), acquired with AP/PA phase encoding, plus SpinEchoFieldMaps, SBRefs, and PsychoPy event timing, Physio files containing pulse oximetry and respiratory traces, and participant eye videos for each run.
ID: 229791 : This package contains the fMRI scan for the CARIT task (in NIFTI format; Go/NoGo Conditioned Approach Response Inhibition Task, with no reward history component), acquired with PA phase encoding, plus SpinEchoFieldMaps, SBRefs, PsychoPy event timing and task modeling files, and Physio files containing pulse oximetry and respiratory traces.
ID: 229792 : This package contains the fMRI scans for the GUESSING task (in NIFTI format; reward, punishment, anticipatory reactivity task), acquired with AP/PA phase encoding, plus SpinEchoFieldMaps, SBRefs, PsychoPy event timing and task modeling files, and a Physio file containing pulse oximetry and respiratory traces for each run.
ID: 229793 : This package contains the mbPCASLhr scan (in NIFTI format; multiband 2D EPI pseudo-continuous arterial spin labeling with high spatial resolution), plus SpinEchoFieldMaps, PsychoPy event timing and participant eye video for the run.
ID: 229842 : This package contains the fMRI scan for the EMOTION task (in NIFTI format; emotion and face-processing task), acquired with PA phase encoding, plus SpinEchoFieldMaps, SBRef, PsychoPy event timing and task modeling files, and a Physio file containing pulse oximetry and respiratory traces.
ID: 229784 : his package contains contains non-imaging demographic, physical health, clinical, cognitive, and behavioral data for participant’s first study visit (V1). See the Lifespan HCP 2.0 Data Release Reference Manual for details on included measures.
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helpcenter.filter-cart
NDA Help Center
Filter Cart
Viewable at the top right of NDA pages, the Filter Cart is a temporary holder for filters and data they
select. Filters are added to the Workspace first, before being submitted to The Filter Cart. Data selected
by filters in the Filter Cart can be added to a Data Package or an NDA Study from the Data Packaging Page,
by clicking the 'Create Data Package / Add Data to Study' button.
The filter cart supports combining multiple filters together, and depending on filter type will use "AND"
or "OR" when combining filters.
Multiple selections from the same filter type will result in those selections being applied with an ‘OR’
condition. For example, if you add an NDA Collection Filter with selections for both collections 2112 and
2563 to an empty Workspace, the subjects from NDA Collection 2112 ‘OR’ NDA Collection 2563 will be added
to your Workspace even if a subject is in both NDA Collections. You can then add other NDA Collections to
your Workspace which further extends the ‘OR’ condition.
If a different filter type is added to your Workspace, or a filter has already been submitted to the
Filter Cart, the operation then performs a logical ‘AND’ operation. This means that given the subjects
returned from the first filter, only those subjects that matched the first filter are returned by the
second filter (i.e., subjects that satisfied both filters).
When combining other filters with the GUID filter, please note the GUID filter should be added last.
Otherwise, preselected data may be lost. For example, a predefined filter from Featured Datasets
may select a subset of data available for a subject. When combined with a GUID filter for the same subject,
the filter cart will contain all data available from that subject, data structure, and dataset; this may be
more data than was selected in the predefined filter for that subject. Again, you should add the GUID
Filter as the last filter to your cart. This ensures 'AND' logic between filters and will limit results to
the subjects, data structures, and datasets already included in your filter cart.
Note that only the subjects specific to your filter will be added to your Filter Cart and only on data
shared with the research community. Other data for those same subjects may exist (i.e., within another NDA
Collection, associated with a data structure that was not requested in the query, etc.). So, users should
select ‘Find all Subjects Data’ to identify all data for those specific subjects.
Additional Tips:
You may query the data without an account, but to gain access you will need to create an NDA user
account and apply for access. Most data access requires that you or your lab are sponsored by an NIH
recognized institution with Federal Wide Assurance (FWA). Without access, you will not be able to
obtain individual-level data.
Once you have selected data of interest you can:
Create a data package - This allows you to specify format for access/download
Assign to Study Cohort - Associate the data to an NDA Study allowing for a DOI to be generated and the
data to be linked directly to a finding, publication, or data release.
Find All Subject Data - Depending on filter types being used, not all data associated with a subject
will be selected. Data may be restricted by data structure, NDA Collection, or outcome variables
(e.g., NDA Study). ‘Find All Data’ expands the filter criteria by replacing all filters in your
Filter Cart with a single Query by GUID filter for all subjects selected by those filters.
Please Note:
When running a query, it may take a moment to populate the Filter Cart. Queries happen in the
background so you can define other queries during this time.
When you add your first filter, all data associated with your query will be added to the Filter Cart
(e.g., a Concept, an NDA Collection, a Data Structure/Element, etc.). As you add additional filters,
they will also display in the Filter Cart. Only the name of filter will be shown in the Filter Cart,
not the underlying structures.
Information about the contents of the Filter Cart can be seen by clicking "Edit”.
Once your results appear in the Filter Cart, you can create a data package or assign subjects to a
study by selecting the 'Package/Assign to Study' option. You can also 'Edit' or 'Clear' filters.
Frequently Asked Questions
What is a Filter Cart?
Viewable at the top right of NDA pages, the Filter Cart is a temporary holder of data identified by the user,
through querying or browsing, as being of some potential interest. The Filter Cart is where you send the data
from your Workspace after it has been filtered.
What do I do after filters are added to the Filter Cart?
After filters are added to the Filter Cart, users have options to ‘Create a Package’ for download, ‘Associate
to Study Cohort’, or ‘Find All Subject Data’. Selecting ‘Find All Subject Data’ identifies and pulls all data
for the subjects into the Filter Cart. Choosing ‘Create a Package’ allows users to package and name their query
information for download. Choosing ‘Associate to Study Cohort’ gives users the opportunity to choose the Study
Cohort they wish to associate this data.
Are there limitations on the amount of data a user can download?
NDA limits the rate at which individual users can transfer data out of Amazon Web Services (AWS) S3 Object
storage to non-AWS internet addresses. All users have a download limit of 20 Terabytes. This limit applies
to the volume of data an individual user can transfer within a 30-day window. Only downloads to non-AWS
internet addresses will be counted against the limit.
How does Filter Cart Boolean logic work?
The Filter Cart currently employs basic AND/OR Boolean logic. A single filter may contain multiple
selections for that filter type, e.g., a single NDA Study filter might contain NDA Study 1 and NDA Study
2. A subject that is in EITHER 1 OR 2 will be returned. Adding multiple filters to the cart, regardless
of type, will AND the result of each filter. If NDA Study 1 and NDA Study 2 are added as individual
filters, data for a subject will only be selected if the subject is included in BOTH 1 AND 2.
When combining other filters with the GUID filter, please note the GUID filter should be added last.
Otherwise, preselected data may be lost. For example, a predefined filter from Featured Datasets
may select a subset of data available for a subject. When combined with a GUID filter for the same subject,
the filter cart will contain all data available from that subject, data structure, and dataset; this may be
more data than was selected in the predefined filter for that subject. Again, you should add the GUID Filter
as the last filter to your cart. This ensures 'AND' logic between filters and will limit results to the
subjects, data structures, and datasets already included in your filter cart.
Glossary
Workspace
The Workspace within the General Query Tool is a holding area where you can review your pending filters prior
to adding them to Filter Cart. Therefore, the first step in accessing data is to select one or more items and
move it into the Workspace.
Filter Cart
Viewable at the top right of NDA pages, the Filter Cart is a temporary holder of data identified by the user
through querying or browsing as being of some potential interest. The Filter Cart adds data using an AND
condition. The opportunity to further refine data to determine what will be downloaded or sent to a miNDAR is
available on the Data Packaging Page, the next step after the Filter Cart. Subsequent access to data is
restricted by User Permission or Privilege; however Filter Cart use is not.
The NDA Query Tool provides a powerful interface to identify and access data. It enables users to select
one or many types of queries, typically following a keyword search. Then, users add these selections to
their Workspace.
The Workspace is the intermediate place for selecting and reviewing filters before submitting them to the
Filter Cart. Once queries have been added to the Workspace and verified, the next step is to submit them
to the Filter Cart.
Multiple selections from the same filter type will result in those selections being applied with an ‘OR’
condition. For example, if you add a Data from Labs Filter with selections for NDA Collections 2112 and
2563 to an empty Workspace, the subjects from NDA Collection 2112 ‘OR’ NDA Collection 2563 will be added
to your Workspace even if a subject is in both NDA Collections. You can then add other Data from Labs
filter to your Workspace which further extends the ‘OR’ condition.
When combining other filters with the GUID filter, please note the GUID filter should be added last.
Otherwise, preselected data may be lost. For example, a predefined filter from Featured Datasets
may select a subset of data available for a subject. When combined with a GUID filter for the same subject,
the filter cart will contain all data available from that subject, data structure, and dataset; this may be
more data than was selected in the predefined filter for that subject. Again, you should add the GUID
Filter as the last filter to your cart. This ensures 'AND' logic between filters and will limit results to
the subjects, data structures, and datasets already included in your filter cart.
If a different filter type is added to your Workspace, or a filter has already been submitted to the Filter
Cart, the operation then performs a logical ‘AND’ operation. This means that given the subjects returned
from the first filter, only those subjects that matched the first filter are returned by the second filter
(i.e., subjects that satisfied both filters). Note that only the subjects specific to your filter will be
added to your Filter Cart and only on data shared with the research community. Other data for those same
subjects may exist (i.e., within another NDA Collection, associated with a data structure that was not
requested in the query, etc.).
Additional Tips:
You may add filters without an account, but to create a data package or add data to a study you will
need to create an NDA user account and apply for access. Most data access requires that you or your lab
are sponsored by an NIH recognized institution with Federal Wide Assurance (FWA). Without access, you
will not be able to obtain individual-level data.
Once you have selected data of interest you can click the 'Create data package / Add data to Study
button' on the Filter Cart, this will take you the Data Packaging Page where you can:
Create a data package - This allows you to specify format for access/download
Add data to a Study - Add the selected data to an NDA Study allowing for a DOI to be generated
and the data to be linked directly to a finding, publication, or data release.
Find All Subject Data - Depending on filter types being used, not all data associated with a
subject will be selected. Data may be restricted by data structure, NDA Collection, or outcome
variables (e.g., NDA Study). ‘Find All Data’ expands the filter criteria by replacing all
filters in your Filter Cart with a single Query by GUID filter for all subjects selected by
those filters.
Frequently Asked Questions
What is a Filter Cart?
Viewable at the top right of NDA pages, the Filter Cart is a temporary holder of data identified by the user,
through querying or browsing, as being of some potential interest. The Filter Cart is where you send the data
from your Workspace after it has been filtered.
How are selections from different tabs represented in the Workspace?
Selections that have been added from different tabs are shown in the Workspace by the filter name they were
created under. For example, when users add data to the Workspace from the ‘Data Dictionary’ tab, queries
show up under a heading Filter: Data Dictionary. When users add to the Workspace from ‘Data from Labs’,
queries display as Filter: Data from Labs. This allows you to review all the queries by differentiated tabs
prior to putting the data from your Workspace into your Filter Cart.
What do I do after filters are added to the Filter Cart?
After filters are added to the Filter Cart, users have options to ‘Create a Package’ for download,
‘Associate to Study Cohort’, or ‘Find All Subject Data’. Selecting ‘Find All Subject Data’ identifies and
pulls all data for the subjects into the Filter Cart. Choosing ‘Create a Package’ allows users to package
and name their query information for download. Choosing ‘Associate to Study Cohort’ gives users the
opportunity to choose the Study Cohort they wish to associate this data.
How do I see all data associated with the subjects in my Filter Cart?
Only pertinent data to the type of filter added is seen in the Filter Cart. For example, if a data structure
is selected and added to the Workspace and then the Filter Cart, only those data within that specific structure
are seen. To see all data for a set of subjects across structures, NDA Collections, or other containers, use
the ‘Query by GUID’ option for the subjects of interest, or select ‘Find All Subjects’ from within the Filter
Cart. After adding another type of filter, all subjects currently in the cart are captured and return all data
associated with them. NOTE: ‘Query by GUID’ and ‘Find all Subject Data’ require that you are authenticated and
have access to at least one of the NDA data repositories or NDA Collections.
How does Filter Cart Boolean logic work?
The Filter Cart currently employs basic AND/OR Boolean logic. A single filter may contain multiple
selections for that filter type, e.g., a single NDA Study filter might contain NDA Study 1 and NDA Study
2. A subject that is in EITHER 1 OR 2 will be returned. Adding multiple filters to the cart, regardless
of type, will AND the result of each filter. If NDA Study 1 and NDA Study 2 are added as individual
filters, data for a subject will only be selected if the subject is included in BOTH 1 AND 2.
When combining other filters with the GUID filter, please note the GUID filter should be added last.
Otherwise, preselected data may be lost. For example, a predefined filter from Featured Datasets
may select a subset of data available for a subject. When combined with a GUID filter for the same subject,
the filter cart will contain all data available from that subject, data structure, and dataset; this may be
more data than was selected in the predefined filter for that subject. Again, you should add the GUID Filter
as the last filter to your cart. This ensures 'AND' logic between filters and will limit results to the
subjects, data structures, and datasets already included in your filter cart.
How do I create a data package?
Once one or more query tools add data to the Filter Cart for download, data can be viewed and edited in the
cart panel located in the upper right-hand corner of the page. Clicking ‘Create Data Package/Add to Study’ takes
you to the Data Packaging Page. On the Data Packaging Page, data returned by the query is viewable. The panel
to the left displays the source NDA Collections of all the data, and the panel to the right displays a list of
all the Data Structures included. Users can check or uncheck NDA Collections and Data Structures to remove or
include in each newly created package. Individual subjects must be in both a checked NDA Collection and a
checked Data Structure to be included.
Glossary
Add to Filter Cart
Once queries are added to the Workspace and verified, the next step is to submit them to the Filter Cart.
Clear Selections
The Clear Selections button allows you to remove selections that you made prior to adding them to your
Workspace. It does not clear your Workspace, Filter Cart, or search results.
