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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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Legal History

legal

01

Download Definition as
Download Submission Template as
Element NameData TypeSizeRequiredDescriptionValue RangeNotesAliases
subjectkeyGUIDRequiredThe NDAR Global Unique Identifier (GUID) for research subjectNDAR*pseudo_guids
src_subject_idString20RequiredSubject ID how it's defined in lab/projectid
interview_dateDateRequiredDate on which the interview/genetic test/sampling/imaging/biospecimen was completed. MM/DD/YYYYRequired fieldinterview_dt_t2, interview_dt_t3, interview_dt_t4
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.age_t2_mos, age_t3_mos, age_t4_mos
sexString20RequiredSex of the subject
M;F
M = Male; F = Femalegender, gender_t1, gender_t2, gender_t3, gender_t4
paroleIntegerRecommendedAre you currently on probation or parole?0;10 = No; 1 = Yeslegal1_t2, legal1_t3, legal1_t4
legal2a_t2IntegerRecommendedAre you presently awaiting charges, trial, or sentence?0;10= No; 1= Yeslegal2a_t3, legal2a_t4
legal2b_t2String200RecommendedIf yes, what are the charges?legal2b_t3, legal2b_t4
legal3_t2IntegerRecommendedHave you ever been arrested and charged with a crime?0;10= No; 1= Yeslegal3_t3, legal3_t4
legal4a_t2IntegerRecommendedArrested and charged with a crime BEFORE your first OEF/OIF/OND deployment?0;10= No; 1= Yeslegal4a_t3, legal4a_t4
legal4b_t2IntegerRecommendedCrime before deployment: Shoplifting/vandalism: number of times16= More than 15 timeslegal4b_t3, legal4b_t4
legal4c_t2IntegerRecommendedCrime before deployment: Parole/probation violations: number of times16= More than 15 timeslegal4c_t3, legal4c_t4
legal4d_t2IntegerRecommendedCrime before deployment: Drug charges: number of times16= More than 15 timeslegal4d_t3, legal4d_t4
legal4e_t2IntegerRecommendedCrime before deployment: Forgery: number of times16= More than 15 timeslegal4e_t3, legal4e_t4
legal4f_t2IntegerRecommendedCrime before deployment: Weapons offense: number of times16= More than 15 timeslegal4f_t3, legal4f_t4
legal4g_t2IntegerRecommendedCrime before deployment: Burglary, larceny, breaking and entering: number of times16= More than 15 timeslegal4g_t3, legal4g_t4
legal4h_t2IntegerRecommendedCrime before deployment: Robbery: number of times16= More than 15 timeslegal4h_t3, legal4h_t4
legal4i_t2IntegerRecommendedCrime before deployment: Assault: number of times16= More than 15 timeslegal4i_t3, legal4i_t4
legal4j_t2IntegerRecommendedCrime before deployment: Arson: number of times16= More than 15 timeslegal4j_t3, legal4j_t4
legal4k_t2IntegerRecommendedCrime before deployment: Rape: number of times16= More than 15 timeslegal4k_t3, legal4k_t4
legal4l_t2IntegerRecommendedCrime before deployment: Homicide, manslaughter: number of times16= More than 15 timeslegal4l_t3, legal4l_t4
legal4m_t2IntegerRecommendedCrime before deployment: Prostitution: number of times16= More than 15 timeslegal4m_t3, legal4m_t4
legal4n_t2IntegerRecommendedCrime before deployment: Contempt of court: number of times16= More than 15 timeslegal4n_t3, legal4n_t4
legal4o_t2IntegerRecommendedCrime before deployment: Disorderly conduct, vagrancy, public intoxication : number of times16= More than 15 timeslegal4o_t3, legal4o_t4
legal4p_t2IntegerRecommendedCrime before deployment: Driving while intoxicated: number of times16= More than 15 timeslegal4p_t3, legal4p_t4
legal4q_t2IntegerRecommendedCrime before deployment: Major driving violations (reckless driving, speeding, no license, etc.): number of times16= More than 15 timeslegal4q_t3, legal4q_t4
legal4r_t2IntegerRecommendedCrime before deployment: Other (yes/no)0;10= No; 1= Yeslegal4r_t3, legal4r_t4
legal4s_t2String200RecommendedCrime before deployment: Other (written out)legal4s_t3, legal4s_t4
legal4t_t2IntegerRecommendedCrime before deployment: Other (number of times)16= More than 15 timeslegal4t_t3, legal4t_t4
legal4u_t2IntegerRecommendedHow many of the charges from BEFORE your first OEF/OIF/OND deployment resulted in convictions?0::30legal4u_t3, legal4u_t4
legal5a_t2IntegerRecommendedArrested and charged with a crime AFTER your first OEF/OIF/OND deployment?0;10= No; 1= Yeslegal5a_t3, legal5a_t4
legal5b_t2IntegerRecommendedCrime after deployment: Shoplifting/vandalism: number of times16= More than 15 timeslegal5b_t3, legal5b_t4
legal5c_t2IntegerRecommendedCrime after deployment: Parole/probation violations: number of times16= More than 15 timeslegal5c_t3, legal5c_t4
legal5d_t2IntegerRecommendedCrime after deployment: Drug charges: number of times16= More than 15 timeslegal5d_t3, legal5d_t4
legal5e_t2IntegerRecommendedCrime after deployment: Forgery: number of times16= More than 15 timeslegal5e_t3, legal5e_t4
legal5f_t2IntegerRecommendedCrime after deployment: Weapons offense: number of times16= More than 15 timeslegal5f_t3, legal5f_t4
legal5g_t2IntegerRecommendedCrime after deployment: Burglary, larceny, breaking and entering: number of times16= More than 15 timeslegal5g_t3, legal5g_t4
legal5h_t2IntegerRecommendedCrime after deployment: Robbery: number of times16= More than 15 timeslegal5h_t3, legal5h_t4
legal5i_t2IntegerRecommendedCrime after deployment: Assault: number of times16= More than 15 timeslegal5i_t3, legal5i_t4
legal5j_t2IntegerRecommendedCrime after deployment: Arson: number of times16= More than 15 timeslegal5j_t3, legal5j_t4
legal5k_t2IntegerRecommendedCrime after deployment: Rape: number of times16= More than 15 timeslegal5k_t3, legal5k_t4
legal5l_t2IntegerRecommendedCrime after deployment: Homicide, manslaughter: number of times16= More than 15 timeslegal5l_t3, legal5l_t4
legal5m_t2IntegerRecommendedCrime after deployment: Prostitution: number of times16= More than 15 timeslegal5m_t3, legal5m_t4
legal5n_t2IntegerRecommendedCrime after deployment: Contempt of court: number of times16= More than 15 timeslegal5n_t3, legal5n_t4
legal5o_t2IntegerRecommendedCrime after deployment: Disorderly conduct, vagrancy, public intoxication : number of times16= More than 15 timeslegal5o_t3, legal5o_t4
legal5p_t2IntegerRecommendedCrime after deployment: Driving while intoxicated: number of times16= More than 15 timeslegal5p_t3, legal5p_t4
legal5q_t2IntegerRecommendedCrime after deployment: Major driving violations (reckless driving, speeding, no license, etc.): number of times16= More than 15 timeslegal5q_t3, legal5q_t4
legal5r_t2IntegerRecommendedCrime after deployment: Other (yes/no)0;10= No; 1= Yeslegal5r_t3, legal5r_t4
legal5s_t2String200RecommendedCrime after deployment: Other (written out)legal5s_t3, legal5s_t4
legal5t_t2IntegerRecommendedCrime after deployment: Other (number of times)16= More than 15 timeslegal5t_t3, legal5t_t4
legal5u_t2IntegerRecommendedHow many of the charges from AFTER your first OEF/OIF/OND deployment resulted in convictions?0::30legal5u_t3, legal5u_t4
legal6_t2IntegerRecommendedHave you ever been detained or incarcerated in your life?0;10= No; 1= Yeslegal6_t3, legal6_t4
legal7a_t2IntegerRecommendedWere you incarcerated BEFORE your first OEF/OIF/OND deployment?0;10= No; 1= Yeslegal7a_t3, legal7a_t4
legal7b_t2IntegerRecommendedBefore your first OEF/OIF/OND deployment, how many years in total were you incarcerated?1::61 = Less than a year to less than 3 years; 2= 3 years to less than 6 years; 3= 6 years to less than 9 years; 4= 9 years to less than 12 years; 5= 12 years to less than 15 years; 6= 15 years or morelegal7b_t3, legal7b_t4
legal7c_t2IntegerRecommendedHow many total months were you incarcerated BEFORE deployment?: less than three years0::3636= Briefly detained, 1 day or lesslegal7c_t3, legal7c_t4
legal7d_t2IntegerRecommendedHow many total months were you incarcerated BEFORE deployment?: three to six years36::71legal7d_t3, legal7d_t4
legal7e_t2IntegerRecommendedHow many total months were you incarcerated BEFORE deployment?: six to nine years72::107legal7e_t3, legal7e_t4
legal7f_t2IntegerRecommendedHow many total months were you incarcerated BEFORE deployment?: nine to twelve years108::143legal7f_t3, legal7f_t4
legal7g_t2IntegerRecommendedHow many total months were you incarcerated BEFORE deployment?: twelve to fifteen years144::179legal7g_t3, legal7g_t4
legal8a_t2IntegerRecommendedWere you incarcerated AFTER your first OEF/OIF/OND deployment?0;10= No; 1= Yeslegal8a_t3, legal8a_t4
legal8b_t2IntegerRecommendedStarting AFTER your first OEF/OIF/OND deployment, how many years in total have you been incarcerated?1::61 = Less than a year to less than 3 years; 2= 3 years to less than 6 years; 3= 6 years to less than 9 years; 4= 9 years to less than 12 years; 5= 12 years to less than 15 years; 6= 15 years or morelegal8b_t3, legal8b_t4
legal8c_t2IntegerRecommendedHow many total months were you incarcerated AFTER deployment?: less than three years0::3636= Briefly detained, 1 day or lesslegal8c_t3, legal8c_t4
legal8d_t2IntegerRecommendedHow many total months were you incarcerated AFTER deployment?: three to six years36::71legal8d_t3, legal8d_t4
legal8e_t2IntegerRecommendedHow many total months were you incarcerated AFTER deployment?: six to nine years72::107legal8e_t3, legal8e_t4
legal8f_t2IntegerRecommendedHow many total months were you incarcerated AFTER deployment?: nine to twelve years108::143legal8f_t3, legal8f_t4
legal8g_t2IntegerRecommendedHow many total months were you incarcerated AFTER deployment?: twelve to fifteen years144::179legal8g_t3, legal8g_t4
legal9_t2IntegerRecommendedHow many days in the past 30 days were you detained or incarcerated?0::30legal9_t3, legal9_t4
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: legal01 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.