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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 fliter 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

  • 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.

  • 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.

  • 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.

Glossary

  • Once your filter cart contains the subjects of interest, select Create Data Package/Assign to Data Study which will provide options for accessing item level data and/or assigning to a study.  

  • Once queries have been added to your workspace, the next step is to Submit the Filters in the workspace to the Filter Cart.  This process runs the queries selected, saving the results within a filter cart attached to your account.  

  • 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. 

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Data Structures with shared data
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Framingham Stroke Risk Profile

224 Shared Subjects

N/A
Clinical Assessments
Diagnostic
11/29/2016
frs01
11/29/2016
View Change History
01
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
Query site String 101 Recommended Site Study Site
Query vital_sysbp Float Recommended Blood Pressure (sitting for 3 minutes)mmHg (systolic) 0::500; 999 999=NK/missing
Query vital_diabp Integer Recommended Blood Pressure (sitting for 3 minutes)mmHg (diastolic) 0::500
Query q21_7d Integer Recommended Antihypertensives for high blood pressure 0; 1; 999 0=No; 1=Yes; 999=Missing/NA/NK
Query cr2 Integer Recommended Diabetes Mellitus 0;1 0 = No current diabetes or random BS < 220;1 = Diagnosis of diabetes or random BS >220
Query fsr5 Integer Recommended Has the subject been smoking tobacco in the past 6 months? 0;1 0 = No; 1 = Yes
Query fsr6 Integer Recommended Does subject have history of intermittent claudication (pain in the legs when walking due to vascular disease) or heart failure, myocardial infarction (heart attack), heart/chest pain from the heart, or heart disease? 0;1 0 = No; 1 = Yes
Query fsr7 Integer Recommended Does subject have history of irregular heart beats? 0;1 0 = No; 1 = Yes
Query fsr7a Integer Recommended (If yes, ask what kind - controlled or uncontrolled?) 0;1 subject may be on blood thinners or beta blockers; 0 = Controlled, 1 = Uncontrolled
Query cr6 Integer Recommended Left Ventricular Hypertrophy (by EKG criteria)? 0;1 0 = no;1 = yes
Query visit String 60 Recommended Visit name
Query days_baseline Integer Recommended Days since baseline
Query visnum Float Recommended Numeric Visit Number -1.5 = Pre-Screening; -1 = Screening; 0 = Baseline; ## = Visit ## (from 1 to 10); Whole numbers = standard monthly visits; #.001 - #.009 = Unscheduled; #.1 = End of Phase 1; #.2 = End of Phase 2; #.3 = End of Phase 3; #.4 = End of Open Choice Phase; #.5 = End of Study; #.6 = Genetic Analysis; 1000=all visits
Query me2 Integer Recommended Status 0;1 0 = Past [Inactive]; 1 = Active
Query fram1 Integer Recommended Framingham weighted: 1. Age in Years 2::10
Query fram2 Integer Recommended Framingham weighted: 2. Systolic Blood Pressure, mm Hg 0::10
Query fram3 Integer Recommended Framingham weighted: 3. Antihypertensive Therapy 0::6
Query fram4 Integer Recommended Framingham weighted: 4. Diabetes Mellitus 0;2;3
Query fram5 Integer Recommended Framingham weighted: 5. Cigarette Smoking 0;3
Query fram6 Integer Recommended Framingham weighted: 6. Vascular Disease 0;2;3
Query fram7 Integer Recommended Framingham weighted: 7. Atrial Fibrillation 0;4;6
Query fram8 Integer Recommended Framingham weighted: 8. Left Ventricular Hypertrophy LVH 0;4;6
Query framcnt Integer Recommended Framingham Number of Scored Items (FRAM1 - FRAM8) 7;8
Query framgham Integer Recommended Framingham Score: Sum of Scored Items (FRAM1 - FRAM8) 0::27
Query fram10yr Float Recommended Framingham 10 Year Risk in %
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.