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Filter Cart

The Filter Cart provides a powerful way to query and access data for which you may be interested.  

A few points related to the filter cart are important to understand with the NDA Query/Filter implementation: 

First, the filter cart is populated asyncronously.  So, when you run a query, it may take a moment to populate but this will happen in the background so you can define other queries during this time.  

When you are adding your first filter, all data associated with your query will be added to the filter cart (whether it be a collection, a concept, a study, a data structure/elment or subjects). Not all data structures or collections will necessarily be displayed.  For example, if you select the NDA imaging structure image03, and further restrict that query to scan_type fMRI, only fMRI images will appear and only the image03 structure will be shown.  To see other data structures, select "Find All Subject Data" which will query all data for those subjects. When a secord or third filter is applied, an AND condition is used.  A subject must exist in all filters.  If the subject does not appear in any one filter, that subjects data will not be included in your filter cart. If that happens, clear your filter cart, and start over.  

It is best to package more data than you need and access those data using other tools, independent of the NDA (e.g. miNDAR snapshot), to limit the data selected.  If you have any questions on data access, are interested in using avaialble web services, or need help accessing data, please contact us for assistance.  

Frequently Asked Questions

Glossary

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NDA provides a single access to de-identified autism research data. For permission to download data, you will need an NDA account with approved access to NDA or a connected repository (AGRE, IAN, or the ATP). For NDA access, you need to be a research investigator sponsored by an NIH recognized institution with federal wide assurance. See Request Access for more information.

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Data Structures with shared data
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Hedonic Taste Pleasantness Scale (HTPS)

fmri_pleas

01

Download Definition as
Download Submission Template as
Element NameData TypeSizeRequiredDescriptionValue RangeNotesAliases
subjectkeyGUIDRequiredThe NDAR Global Unique Identifier (GUID) for research subjectNDAR*
src_subject_idString20RequiredSubject ID how it's defined in lab/project
interview_dateDateRequiredDate on which the interview/genetic test/sampling/imaging/biospecimen was completed. MM/DD/YYYYRequired field
interview_ageIntegerRequiredAge in months at the time of the interview/test/sampling/imaging.0 :: 1260Age 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.
sexString20RequiredSex of the subjectM;FM = Male; F = Femalegender
sol1_pcFloatRecommendedSolution 1 %sol1_pc_scan1, sol1_pc_scan2
sol1_pleasIntegerRecommendedSolution 1 pleasantness1::91=dislike extremely; 9 = like extremelysol1_pleas_scan1, sol1_pleas_scan2
sol1_sweetIntegerRecommendedSolution 1 sweetnes1::91=absent; 9=extremesol1_sweet_scan1, sol1_sweet_scan2
sol2_pcFloatRecommendedSolution 2 %sol2_pc_scan1, sol2_pc_scan2
sol2_pleasIntegerRecommendedSolution 2 pleasantness1::91=dislike extremely; 9 = like extremelysol2_pleas_scan1, sol2_pleas_scan2
sol2_sweetIntegerRecommendedSolution 2 sweetnes1::91=absent; 9=extremesol2_sweet_scan1, sol2_sweet_scan2
sol3_pcFloatRecommendedSolution 3 %sol3_pc_scan1, sol3_pc_scan2
sol3_pleasIntegerRecommendedSolution 3 pleasantness1::91=dislike extremely; 9 = like extremelysol3_pleas_scan1, sol3_pleas_scan2
sol3_sweetIntegerRecommendedSolution 3 sweetnes1::91=absent; 9=extremesol3_sweet_scan1, sol3_sweet_scan2
sol4_pcFloatRecommendedSolution 4 %sol4_pc_scan1, sol4_pc_scan2
sol4_pleasIntegerRecommendedSolution 4 pleasantness1::91=dislike extremely; 9 = like extremelysol4_pleas_scan1, sol4_pleas_scan2
sol4_sweetIntegerRecommendedSolution 4 sweetnes1::91=absent; 9=extremesol4_sweet_scan1, sol4_sweet_scan2
sol5_pcFloatRecommendedSolution 5 %sol5_pc_scan1, sol5_pc_scan2
sol5_pleasIntegerRecommendedSolution 5 pleasantness1::91=dislike extremely; 9 = like extremelysol5_pleas_scan1, sol5_pleas_scan2
sol5_sweetIntegerRecommendedSolution 5 sweetnes1::91=absent; 9=extremesol5_sweet_scan1, sol5_sweet_scan2
sol6_pcFloatRecommendedSolution 6 %sol6_pc_scan1, sol6_pc_scan2
sol6_pleasIntegerRecommendedSolution 6 pleasantness1::91=dislike extremely; 9 = like extremelysol6_pleas_scan1, sol6_pleas_scan2
sol6_sweetIntegerRecommendedSolution 6 sweetnes1::91=absent; 9=extremesol6_sweet_scan1, sol6_sweet_scan2
sol7_pcFloatRecommendedSolution 7 %sol7_pc_scan1, sol7_pc_scan2
sol7_pleasIntegerRecommendedSolution 7 pleasantness1::91=dislike extremely; 9 = like extremelysol7_pleas_scan1, sol7_pleas_scan2
sol7_sweetIntegerRecommendedSolution 7 sweetnes1::91=absent; 9=extremesol7_sweet_scan1, sol7_sweet_scan2
solsugar_pleasIntegerRecommendedSolution sugar pleasantness1::91=dislike extremely; 9 = like extremelysolsugar_pleas_scan1, solsugar_pleas_scan2
solsugar_sweetIntegerRecommendedSolution sugar sweetnes1::91=absent; 9=extremesolsugar_sweet_scan1, solsugar_sweet_scan2
solsalty_pleasIntegerRecommendedSolution salty pleasantness1::91=dislike extremely; 9 = like extremelysolsalty_pleas_scan1, solsalty_pleas_scan2
solsalty_sweetIntegerRecommendedSolution salty sweetnes1::91=absent; 9=extremesolsalty_sweet_scan1, solsalty_sweet_scan2
trialIntegerRecommendedTrial number0::400; -777; -9991 = first; 2= second; 3=third; 4=fourth; 5=fifth; 6=sixth; etc; -777=NA, -999=missing
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.

Distribution for DataStructure: fmri_pleas01 and Element:
Chart Help

Filters enable researchers to view the data shared in NDA before applying for access or for selecting specific data for download or NDA Study assignment. For those with access to NDA shared data, you may select specific values to be included by selecting an individual bar chart item or by selecting a range of values (e.g. interview_age) using the "Add Range" button. Note that not all elements have appropriately distinct values like comments and subjectkey and are not available for filtering. Additionally, item level detail is not always provided by the research community as indicated by the number of null values given.

Filters for multiple data elements within a structure are supported. Selections across multiple data structures will be supported in a future version of NDA.