NIMH Data Archive - Data Dictionary: Data Structure

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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.

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ABCD Youth Delay Discounting Sum Scores

11,368 Shared Subjects

Description Discounting and valuation of proximal and distal rewards

Data type Clinical Assessments

Categories

Task Based

Date created 01/10/2019

Short name abcd_yddss01

Most Recent Update 10/27/2020
View Change History

Version 01

Downloads

Definition

Submission Template

Query	Element Name	Data Type	Size	Required	Description	Value Range	Notes	Aliases
	subjectkey	GUID		Required	The NDAR Global Unique Identifier (GUID) for research subject	NDAR*
	src_subject_id	String	20	Required	Subject ID how it's defined in lab/project
	interview_date	Date		Required	Date on which the interview/genetic test/sampling/imaging/biospecimen was completed. MM/DD/YYYY
	interview_age	Integer		Required	Age in months at the time of the interview/test/sampling/imaging.	0 :: 1260	Age is rounded to chronological month. If the research participant is 15-days-old at time of interview, the appropriate value would be 0 months. If the participant is 16-days-old, the value would be 1 month.
	sex	String	20	Required	Sex of subject at birth	M;F; O; NR	M = Male; F = Female; O=Other; NR = Not reported	gender
	eventname	String	60	Required	The event name for which the data was collected
	ddis_scr_script_startdte	Date		Recommended	Date script was run
	ddis_scr_script_starttme	String	30	Recommended	Time script was started
	ddis_scr_subjectid	String	100	Recommended	Subject id number
Query	ddis_scr_session	Float		Recommended	session
Query	ddis_scr_script_elaptme	Float		Recommended	Time it took to run script (in ms)
	ddis_scr_computer_platform	String	30	Recommended	The platform the script was run on
Query	ddis_scr_values_completed	Float		Recommended	0 = script was not completed (prematurely aborted); 1 = script was completed (all conditions run)
Query	ddis_scr_param_delayrewamt	Float		Recommended	The delayed amount in $ (here: 100)
	ddis_scr_val_testdelays	String	120	Recommended	A string variable that stores all tested
Query	ddis_scr_val_immedcho	Float		Recommended	values.immediateChoiceValidity. (Added in June 2018) Tally of immediate choices in the three validity questions presented after the "3months", "1year", and "5years" delay blocks (e.g. "get $100 NOW" vs. "get $100 in 5 years"). Values < 3 indicate some inattentive (or at least irrational) behavior by the participant
Query	ddis_scr_val_indif_point_6h	Float		Recommended	6-hour delay "indifference point"; The proportion of the maximum ($100) reward that, if presented immediately, was equal in subjective value to the maximum ($100) reward if the subject had to wait 6 h to receive the maximum.
Query	ddis_scr_val_indif_pnt_1da	Float		Recommended	1-day delay "indifference point"; The proportion of the maximum ($100) reward that, if presented immediately, was equal in subjective value to the maximum ($100) reward if the subject had to wait one day to receive the maximum.
Query	ddis_scr_val_indif_pnt_1week	Float		Recommended	1-week delay "indifference point"; The proportion of the maximum ($100) reward that, if presented immediately, was equal in subjective value to the maximum ($100) reward if the subject had to wait 1 week to receive the maximum.
Query	ddis_scr_val_indif_pnt_1mth	Float		Recommended	1 month delay "indifference point"; The proportion of the maximum ($100) reward that, if presented immediately, was equal in subjective value to the maximum ($100) reward if the subject had to wait one month to receive the maximum.
Query	ddis_scr_val_indif_pnt_3mth	Float		Recommended	3 month delay "indifference point"; The proportion of the maximum ($100) reward that, if presented immediately, was equal in subjective value to the maximum ($100) reward if the subject had to wait three months to receive the maximum.
Query	ddis_scr_val_indif_pnt_1yr	Float		Recommended	1 year delay "indifference point"; The proportion of the maximum ($100) reward that, if presented immediately, was equal in subjective value to the maximum ($100) reward if the subject had to wait one year to receive the maximum.
Query	ddis_scr_val_indif_pnt_5yr	Float		Recommended	5-year delay "indifference point"; The proportion of the maximum ($100) reward that, if presented immediately, was equal in subjective value to the maximum ($100) reward if the subject had to wait five years to receive the maximum.
Query	ddis_scr_expr_mnrt_allcho	Float		Recommended	expressions.meanRT_allChoices: mean latency (in ms) of all choices
Query	ddis_scr_expr_medrt_allcho	Float		Recommended	medianRT_allChoices: median latency (in ms) of all choices
Query	ddis_scr_expr_mnrt_immcho	Float		Recommended	meanRT_immedChoices: mean latency (in ms) of 'immediate' choices
Query	ddis_scr_expr_medrt_immedcho	Float		Recommended	medianRT_immedChoices: median latency (in ms) of 'immediate' choices
Query	ddis_scr_expr_mnrt_delaycho	Float		Recommended	meanRT_delayedChoices: mean latency (in ms) of 'delayed' choices
Query	ddis_scr_expr_medrt_delaycho	Float		Recommended	medianRT_delayedChoices: median latency (in ms) of 'delayed' choices

Data Structure

This page displays the data structure defined for the measure identified in the title and structure short name. The table below displays a list of data elements in this structure (also called variables) and the following information:

Element Name: This is the standard element name
Data Type: Which type of data this element is, e.g. String, Float, File location.
Size: If applicable, the character limit of this element
Required: This column displays whether the element is Required for valid submissions, Recommended for valid submissions, Conditional on other elements, or Optional
Description: A basic description
Value Range: Which values can appear validly in this element (case sensitive for strings)
Notes: Expanded description or notes on coding of values
Aliases: A list of currently supported Aliases (alternate element names)
For valid elements with shared data, on the far left is a Filter button you can use to view a summary of shared data for that element and apply a query filter to your Cart based on selected value ranges

At the top of this page you can also:

Use the search bar to filter the elements displayed. This will not filter on the Size of Required columns
Download a copy of this definition in CSV format
Download a blank CSV submission template prepopulated with the correct structure header rows ready to fill with subject records and upload

Please email the The NDA Help Desk with any questions.