NDA Help Center

Autism Phenotypic Concepts

The autism-related phenotypic concepts in this tab are designed to make querying autism data more convenient. These concepts work to simplify your query and streamline the specific concepts you are searching for. You can select multiple concepts, which will apply ‘OR’ logic to the subsequent results. NDA adopted the published ASD phenotype ontology defined in Modeling the Autism Spectrum Disorder Phenotype (McCray et al) as an initial implementation of ontological concepts. For changes or additions to the current model, contact us at NDAHelp@mail.nih.gov.

All selections in Autism Phenopypic Concepts tab will run an 'OR' condition in the NDA database.  Subjects with data in any of the selections will be included in the resulting cohort.

Frequently Asked Questions

  • By clicking ‘Expand All’ in the top right of the module, you can see more detailed choices that are resultant of that selection.

  • If you are unsure of the correct option for your query, you can select the small (i) symbol next to each selection and it will display the concept and rules that apply in greater detail. If you are still not sure, you can always contact the NDA Help Desk at NDAHelp@mail.nih.gov.

  • NDA accepts suggestions for additions to current query definitions. For this and any other questions regarding the Autism Phenotypic Concepts, please reach out to the NDA Help Desk at NDAHelp@mail.nih.gov.

Glossary

  • The NDA supports pre-built queries to dynamically access data based upon a number of phenotypes.  Having implemented the autism phenotypic concepts defined in Modeling the Autism Spectrum Disorder Phenotype (McCray et al), phenotypic concepts can be extended as needed through definitions by the scientific research community.  However, at present, only a small subset of data (approximately 3% of the variables in the NDA) are queriable in this way. 

  • NDA has predefined ontological concepts that can be used to query all NDA and federated data. One selects a Concept and applies the filter to see the number of subjects available. Those that have access (NDA Credentials) may then download any datasets. The NDA has adopted the published Autism Spectrum Disorder (ASD) phenotype ontology, defined in "Modeling the Autism Spectrum Disorder Phenotype" as an initial implementation of ontological concepts.

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Workspace

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.

If a different filter type is added to your Workspace, or a fliter 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 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 fliter 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

  • 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.

  • 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.

  • 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.

  • 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.

  • 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 righthand 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.

  • 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.

Glossary

  • 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. 

  • Once queries are added to the Workspace and verified, the next step is to submit them to the Filter Cart.

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Data from Labs

Data from Labs is an inventory of all NDA Collections. Each NDA Collection contains data from one grant or project. The Data from Labs tool is a data browser where you can search and filter NDA Collections and then select to add one or multiple NDA Collections to your Workspace. Identify NDA Collections of interest by filtering for Submission Status, Funding Source, Organization, Permission Group and NIH Research Initiative. Each NDA Collection tile contains charts with numbers of shared subjects by sex, age, and data type. Data type is broken down by imaging (such as neurosignal recordings), omics, and clinical data.

All selections in the Data from Labs tab will run an 'OR' condition in the NDA database. Subjects with data in any of the selections will be included in the Filter Cart.

Frequently Asked Questions

  • An NDA Collection is a virtual container of data that is stored in the NIMH Data Archive (NDA). NDA Collections are the primary method of organizing data in NDA and are created and organized based on funding source/grant, project, and laboratory. They provide useful tools to manage submission projects and allow investigators to define a wide array of other elements that provide context for their data, including all general information regarding the data and source project, experimental parameters used to collect any event-based data, methods, and other supporting documentation.

    NDA Collections also allow investigators to link underlying data to an NDA Study, defining populations and subpopulations specific to the aims of the research project. NDA Collections are grouped in one or more research clusters, or data repositories, for granting data access.

  • The Text Search function allows easy search and filter capabilities by typing text into the Text Search box. To return desired search results, type the word(s) that describes a Title, Description, Investigator, Organization, etc., and hit the enter key to immediately see results below. To search by a specific NDA Collection number, type the search into the Text Search box with the following format: id:xxxx where xxxx is the NDA Collection number, e.g., id:2026. From there, you can select the relevant boxes next to the desired results and click ‘Add to Workspace’.

  • Filtering data is a useful way to display only the results you want to extract from a large dataset. By selecting one or more NDA Collections and adding them to your Filter Cart, you can access the data more precisely and prepare for download. In the Data from Labs tab, conditions are set in the search boxes, using the drop-down menus to narrow down the results.

Glossary

  • NDA Collections are virtual containers for data located on the NDA website and are the primary method of organizing data in NDA. They are created by NDA and organized on the basis of source grant, project, and laboratory. NDA Collections provide tools useful in managing submission projects and allow investigators to define a wide array of other elements that provide context for their data, including all general information regarding the data and source project, experimental parameters used to collect any event-based data contained in the Collection, methods, and other supporting documentation.

  • Data Source defines the affiliation of the data. It represents the data repository (sometimes referred to as a permission group) and the affiliation with a selected consortia.

  • Data Use Limitations (DULs) describe the appropriate secondary use of a dataset and are based on the original informed consent of a research participant. NDA only accepts consent-based data use limitations defined by the NIH Office of Science Policy.

  • Funding Source is a company, agency, foundation or institute, that provides money for the purpose of conducting research. Most research data shared within NDA is federally funded. NIH funding includes intramural, extramural and contracts. Also, NDA accepts data from privately funded organizations, such as the Stanley Medical Foundation and other federal agencies, like Department of Defense.

  • NDA Collections may be organized by scientific similarity into NIH Research Initiatives, to facilitate query tool user experience. NIH Research Initiatives map to one or multiple Funding Opportunity Announcements. 

  • The research institution affiliated with the grant or principal investigator of the project.

  • Access to shared record-level data in NDA is provisioned at the level of a Permission Group. NDA Permission Groups consist of one or multiple NDA Collections that contain data with the same subject consents.

  • The individual(s) designated by the applicant organization that has the responsibility and proper level of authority to direct the project or program supported by the award. The applicant organization may designate multiple individuals as program directors/principal investigators (PD/PIs) who share the authority and responsibility for leading and directing the project, intellectually and logistically.

  • Data on this page can be sorted by NDA Collection Creation Date, Collection ID (Identification Number), or Submission Status in either Ascending or Descending rank.

  • Submitting Data: refers to the specific NDA Collection that is still in the process of actively submitting data to NDA.

    Submissions Completed: refers to each NDA Collection that has completed all expectations of data submission, of both raw and analyzed data.

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Experiments - Biosamples

Biosamples are biological source materials used in omics experiments. This Query tab allows user to use predefined filters to select banked or samples with generated data organized either by sample type or by biorepository name.

All selections in the Biosamples tab will run an 'OR' condition in the NDA database.  Subjects with data in any of the selections will be included in the resulting cohort.

Frequently Asked Questions

  • Banked Data: The data type option collected by a research project that provided information about the sample ID type and biorepository.

    Generated Data: The data type option that provides query access to Omics data associated with collected samples.

  • First decide if you want to query datasets for Biosamples using Banked or Generated data, located in the tab ‘Data Type’. Once the distinction is selected, continue by choosing ‘Sample Type’ in the boxes below or ‘Biorepository’ selections.

  • Biosamples have predefined filters for shared subjects with the ability to filter and add multiple items simultaneously with ‘OR’ logic for Biosamples, by Sample Type and Biorepository.

Glossary

  • A biobank is a repository that stores and manages biological samples known as biospecimens for use in research.

  • A biorepository is a biological materials repository that collects, processes, stores, and distributes biospecimens to support future scientific investigation.

  • Predefined filter queries help to select "ready to package" data in one click. These queries are organized by combining several filters in a single procedure. Filters are based on sample type and the name of the biorepository.

  • Sample type provides information about the type of biological sample, such as serum, whole blood, etc.

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Frequently Asked Questions

Glossary

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Data Elements

The Data Elements tab includes all Data Elements from all Data Structures within NDA.  Data Elements can belong to multiple Data Structures. Expanding a Data Element will show the Data Structures to which it belongs and allow adding the Data Element or entire Data Structure to your workspace.  You can also see a chart of data distribution for that Data Structure Data Element combination. Creating a Data Element filter allows further filtering by specifc values or ranges of values.

When adding Data Elements to your workspace, only results from that Data Structure and Data Element combination will be included.  To add results from the same Data Element on muliple Data Structures, add a new Data Element filter per Data Structure you are interested in.

 

Frequently Asked Questions

  • Defining the Data Elements and whether they are used as a Primary or Secondary outcome helps to further characterize the data used in the analysis. Furthermore, when you select Edit Measure at the Data Element level you will see and can further define the subject/age records specific to that measure and cohort.  

Glossary

  • Intended to be re-used as much as possible to honor harmonization standards, a Data Element is an individual item (variable/field) within a Data Structure that represents a question/field on an assessment or a discrete data point.

  • A defined organization and group of Data Elements to represent an electronic definition of a measure, assessment, questionnaire, or collection of data points.  Data structures that have been defined in the NDA Data Dictionary are available at https://ndar.nih.gov/data_dictionary.html. 

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Frequently Asked Questions

Glossary

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Featured Dataset - HCP

The Featured Dataset Tab allows users to jump to data that is already prepackaged or to use custom predefined filters to review and download data.

Current HCP Release datasets and prepackaged data are available via this tab. It includes data from 2 projects: HCP-A Mapping the Human Connectome During Typical Aging and HCP-D Mapping the Human Connectome During Typical Development (HCP-D).

Frequently Asked Questions

  • The Connectome Coordination Facility (CCF) houses and distributes public research data for a series of studies that focus on the connections within the human brain. These are known as Human Connectome Projects.

  • A predefined filter query enables users to select and define categories of data they want related to relevant subjects. These filters are displayed as checkable boxes to select items to query. This includes the ability to query by sub-sets of connections based on experimental conditions or other parameters. This way, data is narrowed down to include the concepts of most interest.

  • Yes, NDA provides a way to add predefined filters. If the data are present a predefined filter can be created. Contact the NDA Help Desk for more information on how to add queries for data that interests you.  

Glossary

  • NDA has predefined ontological concepts that can be used to query all NDA and federated data. One selects a Concept and applies the filter to see the number of subjects available. Those that have access (NDA Credentials) may then download any datasets. The NDA has adopted the published Autism Spectrum Disorder (ASD) phenotype ontology, defined in "Modeling the Autism Spectrum Disorder Phenotype" as an initial implementation of ontological concepts.

  • A dataset is a named grouping of data that contains individual units organized into a type of data structure. NDA's defined data structures can be found the NDA Data Dictionary.

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Frequently Asked Questions

Glossary

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Featured Dataset - OAI

This feature allows users to jump to data that is already prepackaged or to use custom predefined filters to review and download data.

The OAI datasets featured here are categorized by visit and age (in months). One may access X-Ray, MRI, or Clinical Data (if available) associated with that visit.
 

Frequently Asked Questions

  • The Osteoarthritis Initiative (OAI), an eleven-year observational cohort study developed to enable a better understanding of prevention and treatment of knee osteoarthritis, one of the most common causes of disability in adults. OAI is sponsored by the National Institute of Arthritis and Musculoskeletal and Skin Diseases.
     

  • The OAI dataset contains clinical data, patient reported outcomes, biospecimen analyses, quantitative image analyses, radiographs (X-Rays), and magnetic resonance images (MRIs). There are longitudinal assessments and measurements from 4,796 subjects, with data from over 431,000 clinical and imaging visits, and almost 26,626,000 images in this archive.

  • A predefined filter query enables users to select and define categories of data they want related to relevant subjects. These filters are displayed as checkable boxes to select items to query. This includes the ability to query by sub-sets of connections based on experimental conditions or other parameters. This way, data is narrowed down to include the concepts of most interest.

  • Yes, NDA provides a way to add predefined filters. If the data are present a predefined filter can be created. Contact the NDA Help Desk for more information on how to add queries for data that interests you.  

Glossary

  • A dataset is a named grouping of data that contains individual units organized into a type of data structure. NDA's defined data structures can be found the NDA Data Dictionary.

  • Knee MRI (3T, Right and Left Knees separately), Thigh MRI (3T, Bilateral) and Knee MRI (3T, Incident Knee only, Trabecular Series)

  • Predefined filter queries help to select "ready to package" data in one click. These queries are organized by combining several filters in single procedure. Filters are usually based on experimental parameters and/or data element values.

  • Knee Radiographs (Bilateral PA Fixed Flexion), Pelvis Radiographs, Hand Radiographs, and Full Limb Radiographs (Bilateral AP).

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Query by GUID

The Global Unique Identifier (GUID) is a universal subject identification (ID) allowing researchers to share specific data about a study participant without exposing personally identifiable information (PII) and to match participants across labs and research data repositories.

Frequently Asked Questions

  • The Global Unique Identifier (GUID) is a universal subject identification (ID) allowing researchers to share specific data about a study participant without exposing personally identifiable information (PII) and to match participants across labs and research data repositories.
     

  • Query by GUID is useful if you are interested in obtaining all of the available data on one or more specific subjectkey (GUID), representing a deidentified individual. To obtain all data associated with a list of GUIDs, add multiple GUIDs to the tool by using the copy-paste feature or uploading them as .csv file and selecting ‘Apply Filters’. GUIDs must be entered one per line, with no other delimiting characters.

  • Query by GUID requires that users authenticate and have access to at least one of the NDA data repositories or NDA Collections. If you have trouble or have additional questions about the 'Query by GUID' feature, please contact the NDA Help Desk at NDAHelp@mail.nih.gov.

Glossary

  • A universal subject ID allowing researchers to share data specific to a study participant without exposing personally identifiable information (PII) and match participants across labs and research data repositories. GUIDs are required for all submitted data and are created using the GUID Tool which can be requested through an NDA account. GUIDs are based on basic information typically found on a birth certificate (first name, last name, date of birth, sex at birth and town/municipality of birth) and can be generated either individually or through a batch process using the template available in the GUID Tool.

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Frequently Asked Questions

Glossary

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Frequently Asked Questions

Glossary

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Experiments - Browse

Experiments can be searched and selected to add to your Workspace/Filter Cart. Searching the Title of the experiment or experiment id are effective ways to query experiments.

All selections in the Browse tab will run an OR condition in the NDA database.  Subjects with data in any of the selections will be included in the resulting cohort.

Frequently Asked Questions

  • An NDA Experiment is the output, as defined by researchers who originally collected the data, which provides useful metadata specific to complex experiment definitions for Omics and Neurosignal Recordings (e.g., EEG, fMRI, Eye Tracking) data. Experiment metadata include the Equipment/Scanner, Software, Environment/Stimuli and additional necessary information which will allow secondary users to reproduce the same experimental conditions.

    Experiments can be searched, selected, and added to the Workspace/Filter Cart. Searching the Title of the experiment or experiment id are effective ways to query experiments.

Glossary

  • Provides information about vendor and make/model of EEG amplifier.

  • Provides information about electrode schema used during EEG and EGG experiments.

  • Provides information about vendor and make/model of experimental device, such MRI scanner, sequencer, etc.

  • There are several types of Experiments to choose from in the Experiments tab:

    Electroencephalogram (EEG) Experiment: An EEG os a test that detects abnormalities in your brain waves, or in the electrical activity of your brain. During the procedure, electrodes consisting of small metal discs with thin wires are pasted onto your scalp. The electrodes detect tiny electrical charges that result from the activity of your brain cells.

    Functional Magnetic Resonance Imaging (fMRI) Experiment: measures brain activity by detecting changes associated with blood flow. This technique relies on the fact that cerebral blood flow and neuronal activation are coupled. When an area of the brain is in use, blood flow to that region also increases. Specialized brain scan and body scan used to map neural activity in the brain or spinal cord of humans or other animals. At the NDA, only for humans. fMRI maps neural activity by imaging the change in blood flow.

      • Resting State: A resting state fMRI is also known as a taskless fMRI. This type of MRI measures the human subjects baseline blood-oxygen-level-dependent (BOLD) variance. This is useful to show there is a functionally connected neuronal network of apparent 'Brain States".
      • Event Based: Event Based fMRI is a technique in magnetic resonance imaging that can be used to detect changes in the BOLD (Blood Oxygen Level Dependent) hemodynamic response to neural activity in response to certain events. This type of MRI attempts to model the change in fMRI signal in response to neural events associated with behavioral trials. and will be useful to address a number of cognitive psychology questions.

    Eye Tracking Experiment: Eye tracking as the name suggests involves tracking of eye-movements. It is a non-invasive, sensitive tool that quantifies and measures eye-movements to describe an individuals' cognitive state. An eye-movement between two fixation points is called a saccade, which is one of the fastest motor movements in our body. By observing the profiles of these eye movements, scientists can better understand neural deficits in patients with cognitive impairments.

    Omics Experiment: Omics are a type of experiment that contain datasets with genomics, transcriptomics, proteomics, or metabolomics. You can query and perform selections based on experimental molecule, platform and technology type.

  • Experimental Molecule provides information about the biological source of an omics experiment.

  • Provides information about vendor and make/model of omics experimental platform.

  • Provides information about the vendor and the make/model of the software used to produce experimental data files.

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Data Dictionary

The Data Dictionary is a compilation of all the data structures currently defined in NDA. Each structure represents a standardized definition of a measure or instrument used by researchers to collect and submit data. To view the detailed definition of an individual structure, click on the structure’s title.  Select one or more structures on this page and add them to the Filter Cart as one filter. Like in all NDA query tools, the contents of one filter are queried on an ‘OR’ basis. Multiple filters return filtered results on an ‘AND’ basis.

Frequently Asked Questions

  • The Data Dictionary is a compilation of all the data structures currently defined in NDA. Each structure represents a standardized definition of a measure or instrument used by researchers to collect and submit data. To view the detailed definition of an individual structure, click on the structure’s title.  Select one or more structures on this page and add them to the Filter Cart as one filter. Like in all NDA query tools, the contents of one filter are queried on an ‘OR’ basis. Multiple filters return filtered results on an ‘AND’ basis.

  • A Data Structure is an electronic definition of a measure or assessment. Data Structures are organized by Structure Source, Data Type, and Category.

  • A Data Element is a unit of a Data Structure, which defines item level questions, scores, and necessary information about subject. There are five required Data Elements in each Data Structure, which are the: subjectkey, the src_subject_id, interview_date, interview_age, and sex.

  • Using the ‘Text Search’ function under ‘Browse Data Dictionary’ allows users to search through the Title, Structure, and Descriptions associated with Data Structures in the NDA Data Dictionary.

Glossary

  • The Category tab will describe the purpose of the assessment, information on data collection methodologies, and assessment source.  Categories are not concepts, but rather several fundamental and distinct classes to which entities or concepts belong. For Data Structures , one can query based on Category which represents different Data Structures that are mostly phenotypic traits or physiological traits. 

     

  • Data Types are structures that allow you to access required information and contain a data file element that allows you to specify the path of associated data files for upload.

    To query information on experimental parameters used to collect the data (e.g., event/task descriptions, acquisition hardware, post-processing, etc.) on a participant-record level, these data types also require you to define an Experiment.

    The NDA hosts a variety of data. The Data Type refers to where the dataset comes from. For example, a dataset can come from a clinical assessment, federated source, or neurosignaling and omics. Once you click on the Data Type you want, the categories become more refined as well as the Data Sources.

    Data Types include demographic data, clinical assessments, imaging data, omic data, and biosamples. The human subject research data is broadly consented for (mostly) and summary level data are available to the research community with the approval of an institutional official (unless it is open access). Shared data are those datasets that have been submitted and verified by NDA as valid. Additional data are held (embargoed) by NDA as some NDA Collection owners may not be ready for sharing as the grant is still active or they have not published a paper and created an NDA Study.

  • Shared Subjects refers to information provided based on data from shared datasets. The number of Submitted Subjects may be larger and that number will display in the Filter Cart and on the Landing Page.

  • Source in the Data Dictionary refers to the origin of the assessment. In this sense, Source should not be confused with "Data Source", as the data structure source is not an indicator of the location of the data.

  • Structure Description provides a short explanation about a defined assessment, its version/edition, and the definition provider.

  • Structure Title provides summary information about an assessment and is defined by the author/publisher.

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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). 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.

  • 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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Experiments - Methods

The Methods tab provides users the ability to use custom predefined filters to review and download data.

All selections in the Methods tab will run an 'OR' condition in the NDA database.  Subjects with data in any of the selections will be included in the resulting cohort.

 

Frequently Asked Questions

  • Omics are a type of experiment that contain datasets with genomics, transcriptomics, proteomics, or metabolomics. Queries are performed on selections based on the experimental molecule, platform and technology type.

  • The Neurosignaling Recordings section represents MRI, Eye Tracking, EEG, EGG, spectroscopy, X-RAY and PET data in predefined query formats. The data are organized by type of recording and then by the type of equipment used in experiment.

  • A predefined filter query enables users to select and define categories of data they want related to relevant subjects. These filters are displayed as checkable boxes to select items to query. This includes the ability to query by sub-sets of connections based on experimental conditions or other parameters. This way, data is narrowed down to include the concepts of most interest.

  • Yes, NDA provides a way to add predefined filters. If the data are present a predefined filter can be created. Contact the NDA Help Desk for more information on how to add queries for data that interests you.  

  • Yes, but please note that if more than one Method is selected, it will act as an ‘OR’ operator and return all results with those possible methods. 

Glossary

  • Predefined filter queries help to select "ready to package" data in one click. These queries are organized by combining several filters in single procedure. Filters are usually based on experimental parameters and/or data element values, such as scan_type for MRI or experimental platform in omics.

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Demographics

Demographics allow you to further define results in the Workspace or Filter Cart by sex and age (in months). Additionally, you can filter by race by clicking the boxes next to the racial demographic you're interested in. To use the Demographics tab, you must have selections added to the Workspace or Filter Cart. You need to make a selection in the other tabs to be able to add Demographics filter(s) to Filter Cart.

All demographics selections are combined into a single ‘demographics’ filter in the filter cart and are linked through 'AND' query logic. Only subjects who satisfy all demographic filter selections will be included in the resulting cohort.

Frequently Asked Questions

  • Parameters for age range can be set two separate ways and will update simultaneously by following the following steps:

    • Use buttons at each end of the age range bar to reduce or expand the range
    • Manually update the numbers
    • Pressing the ‘Reset’ button will clear all selections and will default the Age Range back to 0 and 1260 months.

Glossary

  • The participant's age value as listed in months.

  • Race is defined according to NIH standard:

    American Indian or Alaska Native: A person having origins in any of the original peoples of North, Central, or South America, and who maintains tribal affiliation or community attachment.
     
    Asian: A person having origins in any of the original peoples of the Far East, Southeast Asia, or the Indian subcontinent including, for example, Cambodia, China, India, Japan, Korea, Malaysia, Pakistan, the Philippine Islands, Thailand, and Vietnam. 
     
    Black or African American: A person having origins in any of the black racial groups of Africa. 
     
    Native Hawaiian or Other Pacific Islander: A person having origins in any of the original peoples of Hawaii, Guam, Samoa, or other Pacific Islands.
     
    White: A person having origins in any of the original peoples of Europe, the Middle East, or North Africa.

  • Sex of a subject refers to the classification of research subjects in two categories: male and female - the biological sex assigned at birth.

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Frequently Asked Questions

Glossary

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Data from Papers

Data from Papers is an inventory of all shared NDA Studies. An NDA Study is a container for data and metadata specific to a finding, publication, or data release and may be shared for authorized access even if the original dataset remains embargoed. The Data from Papers tool is a data browser where you can search and filter NDA Studies and then select to add one or multiple NDA Studies to your Workspace. Identify NDA Studies of interest by filtering for free text, Study Type, Permission Group, NIH Research Initiative, or Organization. Each NDA Study tile contains charts with numbers of shared subjects by sex, age, and data type. Data type is broken down by imaging (such as neurosignal recordings), omics, and clinical data.

All selections in the Data from Papers tab will run an 'OR' condition in the NDA database. Subjects with data in any of the selections will be included in the Filter Cart.

Select Add New Study to open the NDA Study Tool and create an NDA Study. From the NDA Study Tool you can add details about the study, attach data analysis and results files, and add NDA Data related to a finding, publication, or data release.

Frequently Asked Questions

  • Data from Papers is a list of NDA Studies. Each NDA Study represents a publication or result based on data contained in NDA and serves as a link between the publication/release and underlying data. Adding an NDA Study to your Filter Cart from the list, using the text search boxes to narrow down results, provides the number of primary and secondary measures, the number of subjects by cohort, and the results which can be viewed in each NDA Study. Every NDA Study displays a snapshot chart of the shared subjects’ data it includes. Subject demographic information, such as sex and age range, are displayed along with a breakdown of the Imaging (such as Neurosignal Recordings), Omics, and Clinical Data that were used for a given NDA Study.

  • An NDA Study is a container on the NDA website that defines specific subjects and measures relevant to a publication and links this data back to the publication/finding or data release. 

  • To add data/subjects to a cohort, first create a new NDA Study in your user account. Then, within that NDA Study, create an empty cohort. This is in the ‘Data from Papers’ section of the website. Fill in the text boxes ‘Type’, ‘Name’, ‘Sex’, and ‘Age From’ range.

    Add subjects by creating a query filter just as if you were downloading the data. Once the filter is applied, resulting subjects appear in the Filter Cart at the top righthand corner of the page. This takes you to the Data Packaging Page where specific measures and NDA Collections are assigned to the NDA Study previously created by clicking ‘Add to Study Cohort,’ and selecting the correct Study and Cohort.

  • The ‘Text Search’ function is useful if you generally know what you’re looking for in the Data from Papers tab but are unsure of the specifics. Type in a relevant word or name that you’re searching for and the tool will sort through Titles, Abstracts, Investigators, Publications and DOIs. If you want to search by a specific NDA Collection id, type it in the following format: id:xxx where xxx is the specific NDA Study you are interested in, e.g., id:500.

Glossary

  • Data Source defines the affiliation of the data. It represents the data repository (sometimes referred to as a permission group) and the affiliation with a selected consortia.

  • In the Data from Papers tab, Data Usage refers to All data contained in NDA, data from only Primary Analysis, or data from only Secondary Analysis.

    Primary Analysis is defined as the initial grantee or Collection who contributed the first data (submitted the raw and analyzed de-identified data) allowing NDA to link all information on research participants, giving other researchers the ability for use the data to advance science together through a secondary analysis.

    Secondary Analysis refers to a user or investigator that requests access to NDA to use data that already exists for further analysis.

  • Data Use Limitations (DULs) describe the appropriate secondary use of a dataset and are based on the original informed consent of a research participant. NDA only accepts consent-based data use limitations defined by the NIH Office of Science Policy.

  • A Digital Object Identifier (DOI) is a URN (Uniform Resource Name), a compact string that provides a unique, persistent, and actionable identifier for the digital object with which it is associated. DOIs are commonly assigned to scientific articles in their electronic form, but DOIs may also be used as identifiers for any object in any location, although this usage is not yet common outside the online world.

     

    Each NDA Study has a Digital Object Identifier (DOI), which is a persistent link that should be used to reliably cite or reference the data supporting publication.

  • Researchers are expected to associate the data deposited in NDA with their publications/findings – both positive and negative - using the NDA Study feature. An NDA Study shares the specific data it references, enabling other data to remain embargoed, allowing a project to release data for a specific aim when that aim is published or a finding is made.  An NDA Study is automatically issued a DOI and can be searched and accessed though the General Query or Data from Papers interface.

  • NDA Collections may be organized by scientific similarity into NIH Research Initiatives, to facilitate query tool user experience. NIH Research Initiatives map to one or multiple Funding Opportunity Announcements. 

  • The institution, business, or research center responsible for submitting Data.

  • Access to shared record-level data in NDA is provisioned at the level of a Permission Group. NDA Permission Groups consist of one or multiple NDA Collections that contain data with the same subject consents.

  • The individual(s) designated by the applicant organization that has the responsibility and proper level of authority to direct the project or program supported by the award. The applicant organization may designate multiple individuals as program directors/principal investigators (PD/PIs) who share the authority and responsibility for leading and directing the project, intellectually and logistically.

  • PubMed ID (PMID) is the unique identifier number used in PubMed. PMIDs are assigned to each article record when it enters the PubMed system, so an in press publication will not have one unless it is issued as an electronic pre-pub. The PMID number is always found at the end of a PubMed citation.

  • NDA offers various Study Types: Analysis, Clinical Trial, Finding, Release Study, and Release-Archived.

    • Analysis: is often associated with a computational pipeline.
    • Clinical Trial:  relates to diagnostic assessments, clinical measures, medical histories, demographic data, and questionnaires. 
    • Finding: a result associated with a publication.
    • Release Study: a static, curated data set.
    • Release-Archived: represents a snapshot release of a dynamic dataset that has been superseded by a more recent version. These data may only be appropriate for archival purposes, or to cite if this was the original dataset used in an analysis.
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Frequently Asked Questions

Glossary

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Featured Dataset - ABCD

The Featured Dataset Tab allows users to jump to data that is already prepackaged or to use custom predefined filters to review and download data.

Current ABCD Release datasets and prepackaged data are available via this tab.

Frequently Asked Questions

  • Adolescent Brain Cognitive Development (ABCD) is a Data Repository in NDA that houses all data generated by the ABCD Study. The ABCD Study is a landmark, longitudinal study of brain development and child health. Investigators at 21 sites around the country measure brain maturation in the context of social, emotional, and cognitive development, as well as a variety of health and environmental outcomes.

  • Fast Track is ABCD data that is uploaded on an ongoing basis as they become available. Fast Track data releases contain unprocessed neuroimaging data from ABCD Study participants to date, as well as basic participant demographics (age, sex), including:

    - High-resolution structural data (3D T1 - and T2 - weighted scans)
    - Advanced diffusion MRI (multiple b-values and directions)
    - Resting State fMRI
    - Task fMRI (Monetary Incentive Delay, Stop-Signal), and Emotional N-Back), along with raw E-Prime task files for each fMRI run

    These data are available in the ABCD Collection. To user Fast Track data, you need to define an NDA Study to identify the raw data cases they've used, which is assigned a DOI. If any records in Fast Track data are corrected, this change is applied to the original dataset and documented in a Fast Track change report.

  • Prepackaged data:  ABCD imaging files are over 100TB and are not included in prepackaged data.  Only tabular imaging data are included in the prepackaged data.  You can download up to 5TB of raw imaging files by creating a miNDAR (NDA’s cloud database service) with the ABCDStudyNDA prepackaged data and then downloading specific files from the cloud.  The ABCDStudyDEAP prepackaged data cannot be used to create a miNDAR.  Detailed instructions for accessing raw files in the NDA cloud are on the ABCD/NDA website.

    Available datasets:  When your filter cart is finalized, you can create a download package and select to “include associated files” to access up to 5TB of raw imaging files as well as genotyping and mobile actigraphy files.  The download will not succeed if you include associated files and there are more than 5TB of imaging files referenced in the query results. 

    If you do not select to include associated files, you can download a subset of raw imaging files as well as genotyping and mobile actigraphy data by following the Cloud Access instructions on the ABCD/NDA website.

    Computational credits:  Apply for credits to work on all ABCD imaging data in the cloud using NDA’s computational credits program.

  • Prepackaged data: Genotyping and raw mobile actigraphy data are included in prepackaged datasets.

    Available datasets: When your Filter Cart is finalized, you can create a download package and select to “include associated files” to access genotyping and raw mobile actigraphy files.  If you are also querying for minimally processed imaging data, you may exceed the 5TB download limit.  In this case, follow the Cloud Access instructions on the ABCD/NDA website to access the data.

  • Minimally Processed data, or minproc, are raw minimally processed imaging files from the ABCD longitudinal study. These images are extremely large which make data transfer difficult. To access those images, you can apply for  Computational Credits and compute on the data in the cloud without downloading the files in their entirety. Contact the NDA Help Desk if you need the full imaging data (NDAHelp@mail.nih.gov).

     

  • Tabulated data are images and data that are processed by putting them in tables (tabulated format). ABCD Annual Release data are static, curated datasets that include minimally processed brain image volumes and tabulated structural MRI, diffusion MRI, resting-state fMRI and task fMRI results, as well as all non-imaging assessment data from the physical & mental health, neurocognition, substance use, biospecimens and culture and environment domains.

  • A predefined filter query enables users to select and define categories of data they want related to relevant subjects. These filters are displayed as checkable boxes to select items to query. This includes the ability to query by sub-sets of connections based on experimental conditions or other parameters. This way, data is narrowed down to include the concepts of most interest.

  • Yes, NDA provides a way to add predefined filters. If the data are present a predefined filter can be created. Contact the NDA Help Desk for more information on how to add queries for data that interests you.  

Glossary

  • A dataset is a named grouping of data that contains individual units organized into a type of data structure. NDA's defined data structures can be found the NDA Data Dictionary.

  • Predefined filter queries help to select "ready to package" data in one click. These queries are organized by combining several filters in single procedure. Filters are usually based on experimental parameters and/or data element values.

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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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Query by Global Unique Identifier (GUID)

Use Query by GUID to request all available data associated with one or more specific subjects. Query specific subjects using one or multiple GUIDs (subjectkey). Each GUID is an alphanumeric code that corresponds to a deidentified subject in the NDA database. Copy-paste one or multiple GUIDs into the tool or upload them as .csv file and then select ‘Apply Filters’ to initiate the query.

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