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[Deprecated]: V1.0

post

/ec-datahub-svc/rest/v1.0/tenant/{tenantId}/studies/{studyId}/{mode}/subjects/blindedVisits

Deprecated: Use latest version instead.

Retrieves the study-permissioned Blinded Subject Event dataset for a single study and mode.

The dataset exposes blinded subject visit history, including site, subject, visit scheduling and status, transfer context, form completion counts, and audit columns, without exposing unblinded treatment assignment details.

Supports select, filter, sort, limit, and offset query patterns.

The dataset returns versioned subject-visit rows for subjects associated with the study and mode.

Required permission: BlindedSubjectEventDatasetPost.

Recommended order columns: The backend query always orders results by DH_TIMESTAMP and VERSION_START in ascending order first. If orderColumns is empty, only these two columns are used. If orderColumns is provided, the specified columns are appended after DH_TIMESTAMP and VERSION_START. For stable, deterministic pagination, use STUDY_ID, SUBJECT_ID, EVENT_ID, and EVENT_INSTANCE_NUM in the orderColumns field of the request payload.

Request

Path Parameters

• mode(required): string

  Execution mode for the study.

  Allowed values: test, active, training.

  Example: test.

• studyId(required): string(uuid)

  Unique study identifier supplied in the studyId path parameter.

  Use the uppercase hexadecimal UUID value for the study.

  Example: 0C7CBA3F70034C47947E2FAB086BFBF5.

• tenantId(required): string(uuid)

  Unique tenant identifier supplied in the tenantId path parameter.

  Use the uppercase hexadecimal UUID value for the tenant.

  Example: EC942244BB30163BE053BEC44C64CF34.

Query Parameters

• limit: integer(int32)
  Minimum Value: 0

  Page size for the result set.

  • 0 disables pagination and returns the maximum result set allowed by the dataset endpoint.
  • Positive values enable pagination.
  • Negative values return HTTP 400.
• offset: integer(int32)
  Minimum Value: 0

  Zero-based row offset.

  • Counts rows, not pages.
  • To fetch the next page, repeat the same request body and set offset = previous offset + previous count.
  • When limit = 0, this value is ignored and the response echoes offset = 0.
  • When limit > 0, an offset beyond the available rows returns HTTP 200 with an empty page.
  • Negative values return HTTP 400.

Supported Media Types

• application/json

Request Body - application/json ()

Root Schema : schema

Type: object

Submit a structured query for a Data Hub dataset.

• selectColumns is required and must contain one or more valid column names exposed by the target dataset version.
• whereColumns is optional and provides structured filter predicates. Supported operators are =, !=, <>, >, >=, <, <=, LIKE, NOT LIKE, IN, NOT IN, BETWEEN, NOT BETWEEN, IS, and IS NOT.

  Default behavior: Data is filtered based on the STUDY_WID column.

• orderColumns is optional and controls sort order. For stable multi-page retrieval, keep the same orderColumns across page requests.

Show Source

• orderColumns: array orderColumns

  Optional sort instructions to apply to the result set.

  Duplicate order-by columns are rejected.

• selectColumns: array selectColumns

  Required non-empty list of dataset column names to return.

  Column validation is case-insensitive, and the response echoes canonical uppercase dataset column names in the same order.

• whereColumns: array whereColumns

  Optional structured filter predicates.

  This is the request-body equivalent of a WHERE clause.

  All predicate values are supplied as strings and are parsed according to the underlying dataset column type.

{
    "type":"object",
    "properties":{
        "selectColumns":{
            "type":"array",
            "description":"<p>Required non-empty list of dataset column names to return.</p><p>Column validation is case-insensitive, and the response echoes canonical uppercase dataset column names in the same order.</p>",
            "example":[
                "STUDY_VERSION",
                "STUDY_ID"
            ],
            "items":{
                "type":"string",
                "description":"<p>Required non-empty list of dataset column names to return.</p><p>Column validation is case-insensitive, and the response echoes canonical uppercase dataset column names in the same order.</p>",
                "example":"[\"STUDY_VERSION\",\"STUDY_ID\"]"
            }
        },
        "whereColumns":{
            "type":"array",
            "description":"<p>Optional structured filter predicates.</p><p>This is the request-body equivalent of a <code>WHERE</code> clause.</p><p>All predicate values are supplied as strings and are parsed according to the underlying dataset column type.</p>",
            "example":[
                {
                    "columnName":"STUDY_ID",
                    "operator":"=",
                    "value":[
                        "A86F2D0BB610404DB62D37AFA9C20B50"
                    ]
                }
            ],
            "items":{
                "$ref":"#/components/schemas/QueryPredicate"
            }
        },
        "orderColumns":{
            "type":"array",
            "description":"<p>Optional sort instructions to apply to the result set.</p><p>Duplicate order-by columns are rejected.</p>",
            "example":[
                {
                    "columnName":"VERSION_START",
                    "sortOrder":"ASC"
                }
            ],
            "items":{
                "$ref":"#/components/schemas/QueryOrder"
            }
        }
    },
    "description":"<p>Submit a structured query for a Data Hub dataset.</p>\n<ul>\n  <li><code>selectColumns</code> is required and must contain one or more valid column names exposed by the target dataset version.</li>\n  <li><code>whereColumns</code> is optional and provides structured filter predicates. Supported operators are <code>=</code>, <code>!=</code>, <code>&lt;&gt;</code>, <code>&gt;</code>, <code>&gt;=</code>, <code>&lt;</code>, <code>&lt;=</code>, <code>LIKE</code>, <code>NOT LIKE</code>, <code>IN</code>, <code>NOT IN</code>, <code>BETWEEN</code>, <code>NOT BETWEEN</code>, <code>IS</code>, and <code>IS NOT</code>.\n    <p><strong>Default behavior</strong>: Data is filtered based on the <code>STUDY_WID</code> column.</p>\n  </li>\n  <li><code>orderColumns</code> is optional and controls sort order. For stable multi-page retrieval, keep the same <code>orderColumns</code> across page requests.</li>\n</ul>\n"
}

Nested Schema : orderColumns

Type: array

Optional sort instructions to apply to the result set.

Duplicate order-by columns are rejected.

Show Source

• Array of: object QueryOrder

  Sort instruction specifying a dataset column and optional order direction.

{
    "type":"array",
    "description":"<p>Optional sort instructions to apply to the result set.</p><p>Duplicate order-by columns are rejected.</p>",
    "example":[
        {
            "columnName":"VERSION_START",
            "sortOrder":"ASC"
        }
    ],
    "items":{
        "$ref":"#/components/schemas/QueryOrder"
    }
}

Example:

[
    {
        "columnName":"VERSION_START",
        "sortOrder":"ASC"
    }
]

Nested Schema : selectColumns

Type: array

Required non-empty list of dataset column names to return.

Column validation is case-insensitive, and the response echoes canonical uppercase dataset column names in the same order.

Show Source

• Array of: string

  Required non-empty list of dataset column names to return.

  Column validation is case-insensitive, and the response echoes canonical uppercase dataset column names in the same order.

  Example: ["STUDY_VERSION","STUDY_ID"]

{
    "type":"array",
    "description":"<p>Required non-empty list of dataset column names to return.</p><p>Column validation is case-insensitive, and the response echoes canonical uppercase dataset column names in the same order.</p>",
    "example":[
        "STUDY_VERSION",
        "STUDY_ID"
    ],
    "items":{
        "type":"string",
        "description":"<p>Required non-empty list of dataset column names to return.</p><p>Column validation is case-insensitive, and the response echoes canonical uppercase dataset column names in the same order.</p>",
        "example":"[\"STUDY_VERSION\",\"STUDY_ID\"]"
    }
}

Example:

[
    "STUDY_VERSION",
    "STUDY_ID"
]

Nested Schema : whereColumns

Type: array

Optional structured filter predicates.

This is the request-body equivalent of a WHERE clause.

All predicate values are supplied as strings and are parsed according to the underlying dataset column type.

Show Source

• Array of: object QueryPredicate
  Structured filter predicate used to constrain dataset results by column, operator, and value

{
    "type":"array",
    "description":"<p>Optional structured filter predicates.</p><p>This is the request-body equivalent of a <code>WHERE</code> clause.</p><p>All predicate values are supplied as strings and are parsed according to the underlying dataset column type.</p>",
    "example":[
        {
            "columnName":"STUDY_ID",
            "operator":"=",
            "value":[
                "A86F2D0BB610404DB62D37AFA9C20B50"
            ]
        }
    ],
    "items":{
        "$ref":"#/components/schemas/QueryPredicate"
    }
}

Example:

[
    {
        "columnName":"STUDY_ID",
        "operator":"=",
        "value":[
            "A86F2D0BB610404DB62D37AFA9C20B50"
        ]
    }
]

Nested Schema : QueryOrder

Type: object

Sort instruction specifying a dataset column and optional order direction.

Show Source

• columnName: string

  Required dataset column name to sort by.

  Column-name validation is case-insensitive.

  Example: VERSION_START
• sortOrder: string
  Allowed Values: [ "ASC", "DESC" ]

  Optional sort direction.

  If omitted, SQL default ascending order is used for that column. Allowed values are ASC and DESC.

  Example: ASC

{
    "type":"object",
    "properties":{
        "columnName":{
            "type":"string",
            "description":"<p>Required dataset column name to sort by.</p><p>Column-name validation is case-insensitive.</p>",
            "example":"VERSION_START"
        },
        "sortOrder":{
            "type":"string",
            "description":"<p>Optional sort direction.</p><p>If omitted, SQL default ascending order is used for that column. Allowed values are ASC and DESC.</p>",
            "example":"ASC",
            "enum":[
                "ASC",
                "DESC"
            ]
        }
    },
    "description":"<p>Sort instruction specifying a dataset column and optional order direction.</p>",
    "example":[
        {
            "columnName":"VERSION_START",
            "sortOrder":"ASC"
        }
    ]
}

Example:

[
    {
        "columnName":"VERSION_START",
        "sortOrder":"ASC"
    }
]

Nested Schema : QueryPredicate

Type: object

Structured filter predicate used to constrain dataset results by column, operator, and value

Show Source

• columnName: string
  Required dataset column name to filter on. Column-name validation is case-insensitive.

  Example: STUDY_ID
• operator: string
  Allowed Values: [ ">", "<", "=", ">=", "<=", "<>", "!=", "IN", "NOT IN", "BETWEEN", "NOT BETWEEN", "LIKE", "NOT LIKE", "IS", "IS NOT" ]

  Required comparison operator. Use one value for =, !=, <>, >, >=, <, <="," like, and not like; one or more values for in in; exactly two between between; value equal to null is not.< div>

  Example: =
• value: array value
  Filter values as strings. Value cardinality depends on the operator: one for most operators, one or more for IN/NOT IN, exactly two for BETWEEN/NOT BETWEEN, and exactly one value equal to NULL for IS/IS NOT.

{
    "type":"object",
    "properties":{
        "columnName":{
            "type":"string",
            "description":"Required dataset column name to filter on. Column-name validation is case-insensitive.",
            "example":"STUDY_ID"
        },
        "operator":{
            "type":"string",
            "description":"Required comparison operator. Use one value for =, !=, <>, >, >=, <, <=, LIKE, and NOT LIKE; one or more values for IN and NOT IN; exactly two values for BETWEEN and NOT BETWEEN; and exactly one value equal to NULL for IS and IS NOT.",
            "example":"=",
            "enum":[
                ">",
                "<",
                "=",
                ">=",
                "<=",
                "<>",
                "!=",
                "IN",
                "NOT IN",
                "BETWEEN",
                "NOT BETWEEN",
                "LIKE",
                "NOT LIKE",
                "IS",
                "IS NOT"
            ]
        },
        "value":{
            "type":"array",
            "description":"Filter values as strings. Value cardinality depends on the operator: one for most operators, one or more for IN/NOT IN, exactly two for BETWEEN/NOT BETWEEN, and exactly one value equal to NULL for IS/IS NOT.",
            "example":[
                "A86F2D0BB610404DB62D37AFA9C20B50"
            ],
            "items":{
                "type":"string",
                "description":"Filter values as strings. Value cardinality depends on the operator: one for most operators, one or more for IN/NOT IN, exactly two for BETWEEN/NOT BETWEEN, and exactly one value equal to NULL for IS/IS NOT.",
                "example":"[\"A86F2D0BB610404DB62D37AFA9C20B50\"]"
            }
        }
    },
    "description":"Structured filter predicate used to constrain dataset results by column, operator, and value",
    "example":[
        {
            "columnName":"STUDY_ID",
            "operator":"=",
            "value":[
                "A86F2D0BB610404DB62D37AFA9C20B50"
            ]
        }
    ]
}

Example:

[
    {
        "columnName":"STUDY_ID",
        "operator":"=",
        "value":[
            "A86F2D0BB610404DB62D37AFA9C20B50"
        ]
    }
]

Nested Schema : value

Type: array

Filter values as strings. Value cardinality depends on the operator: one for most operators, one or more for IN/NOT IN, exactly two for BETWEEN/NOT BETWEEN, and exactly one value equal to NULL for IS/IS NOT.

Show Source

• Array of: string
  Filter values as strings. Value cardinality depends on the operator: one for most operators, one or more for IN/NOT IN, exactly two for BETWEEN/NOT BETWEEN, and exactly one value equal to NULL for IS/IS NOT.

  Example: ["A86F2D0BB610404DB62D37AFA9C20B50"]

{
    "type":"array",
    "description":"Filter values as strings. Value cardinality depends on the operator: one for most operators, one or more for IN/NOT IN, exactly two for BETWEEN/NOT BETWEEN, and exactly one value equal to NULL for IS/IS NOT.",
    "example":[
        "A86F2D0BB610404DB62D37AFA9C20B50"
    ],
    "items":{
        "type":"string",
        "description":"Filter values as strings. Value cardinality depends on the operator: one for most operators, one or more for IN/NOT IN, exactly two for BETWEEN/NOT BETWEEN, and exactly one value equal to NULL for IS/IS NOT.",
        "example":"[\"A86F2D0BB610404DB62D37AFA9C20B50\"]"
    }
}

Example:

[
    "A86F2D0BB610404DB62D37AFA9C20B50"
]

Examples

Select an example BlindedSubjectEventDataSetQuery

Back to Top

Response

Supported Media Types

• application/json
• text/plain

200 Response

Response behavior

• The response is tabular. columns defines the selected output order, and each row in data follows that same order.
• Every value in data is returned as a JSON string or null, including logical numbers and date/time values.
• hasMore = "true" means more matching rows exist after the current page.
• If filters match no rows, or offset is beyond the last row, the API returns HTTP 200 with data = [], count = 0, and hasMore = "false".

Section index

Study context | Site context | Subject context | Event context | Aggregation context | Audit context | Reference and system identifiers

Study context

Study-level identifiers, version metadata, and protocol attributes associated with the dataset row.

Column Name	Data Type	Description
STUDY_NAME	VARCHAR2(64 CHAR)	Study title associated with the dataset row.
STUDY_VERSION	VARCHAR2(100 CHAR)	Indicates the study version number of the referencing data in a custom report.

Parent topic: Section index

Site context

Site profile, operational settings, and site-maintained contact details associated with the dataset row.

Column Name	Data Type	Description
SITE_NAME	VARCHAR2(500 CHAR)	Indicates the site's name as entered by a site manager when they created or last modified a site.
FROM_SITE_NAME	VARCHAR2(500 CHAR)	Site name from which the subject was transferred.
TO_SITE_NAME	VARCHAR2(500 CHAR)	Site name to which the subject was transferred.
INVESTIGATOR	VARCHAR2(2048 CHAR)	A Principal Investigator's Full Name as listed when the site manager created the site.
ADDRESS_STREET_1	VARCHAR2(150 CHAR)	A site's first address as entered by the site manager when they created or last modified the site.
ADDRESS_STREET_2	VARCHAR2(150 CHAR)	A site's second address as entered by the site manager when they created or last modified the site.
ADDRESS_CITY	VARCHAR2(100 CHAR)	A site's city as entered by the site manager when they created or last modified the site.
ADDRESS_STATE_OR_PROV_OR_CNTY	VARCHAR2(100 CHAR)	A site's state, province, or county as entered by the site manager when they created or last modified the site.
ADDRESS_POSTALCODE	VARCHAR2(20 CHAR)	The Zip Postal Code associated with a site's address.
ADDRESS_COUNTRY	VARCHAR2(4000 CHAR)	A site's country as entered by the site manager when they created or last modified the site. The field display the country ISO code.

Parent topic: Section index

Subject context

Subject identity, status, enrollment, and transfer attributes associated with the record.

Column Name	Data Type	Description
SUBJECT_NAME	VARCHAR2(500 CHAR)	Subject name associated with the dataset row.
SUBJECT_NUMBER	VARCHAR2(500 CHAR)	The number currently assigned to the subject in the system as identifier.
OLD_SUBJECT_NUMBER	VARCHAR2(500 CHAR)	Subject number assigned before the transfer or renumbering.
NEW_SUBJECT_NUMBER	VARCHAR2(500 CHAR)	Subject number assigned after the transfer or renumbering.

Parent topic: Section index

Event context

Event metadata, visit scheduling, and visit-status attributes associated with the dataset row.

Column Name	Data Type	Description
EVENT_NAME	VARCHAR2(64 CHAR)	Visit title associated with the dataset row.
EVENT_TYPE	VARCHAR2(100)	Displays the type of event that impacts a visit's status. Upon selecting this data element, only events that occurred in your study are displayed. For example, you may see some of the following events: Visit_Complete Visit_Date_Changed VisitDateCleared VisitDateEntered Visit_Not_Started Visit_Skip_Undone Visit_Skipped Visit_Started Visit_Inserted: this option refers to new visits inserted into the study's schedule as an Advanced Study Versioning change.
VISIT_TYPE	VARCHAR2(100 CHAR)	Indicates the event type as specified by the study designer when they created the event. Possible values include ScreeningVisit, ScheduleAbleVisit, SubjectWithdrawalVisit, SubjectCompletionVisit, UnScheduleAbleVisit, Event, AdverseEvent, ScreenFailureVisit, or ReScreeningEvent.
VISIT_STATUS	VARCHAR2(32 CHAR)	Indicates a visit's status in the system. Can have one of the following values: NEW: the visit was dynamically triggered and has no data. SCHEDULED: the visit is scheduled for the subject but has no data. Note: Future visits are included with the status of SCHEDULED. Dynamic and cycle visits will not be included until an event happens that causes their creation on the subject's schedule. INPROGRESS: the visit was never completed and has one or more required items with no saved data. INCOMPLETE: the visit was completed at some point but now has one or more required items that are not completed. INCOMPLETE_ERR: the visit was completed at some point but now has one or more required items that are not completed and open queries. COMPLETE: all required items within the visit are completed and there are no open queries. COMPLETE_ERR: all required items within the visit are completed but there are open queries. SKIPPED: the visit was part of the visit schedule for the subject but was skipped by a site user. UNDO_SKIP: the visit was skipped at some point but the skip action was undone.
EVENT_INSTANCE_NUM	NUMBER	Indicates the unscheduled visit instance number as designed by the study designer.
IS_REQUIRED	CHAR(1)	Indicates if the visit is required. Possible values include 0 or 1.
IS_SCHEDULED_VISIT	CHAR(1)	Indicates if the visit is scheduled. Possible values include Y or N.
SCHEDULED_FROM_EVENT_NAME	VARCHAR2(64 CHAR)	Displays the EVENT_TITLE (visit title) of the Scheduled From visit as defined in the Visit Schedule. Note: If a visit is not scheduled or it is the first visit in the schedule, then this element is populated with the visit's own title. For example, Screening Visit is displayed for the Screening Visit, as it is the first visit in the schedule.
VISIT_START_DATE	DATE	Date stamp of a visit's start date.
PROJECTED_VISIT_START_DATE	TIMESTAMP(6)	Date when the next scheduled visit should start in the study, based on the configured visit schedule.
PROJECTED_VISIT_END_DATE	TIMESTAMP(6)	Date when the next scheduled visit should end in the study, based on the configured visit schedule.
PROJECTED_VISIT_DATE	TIMESTAMP(6)	Date when the next scheduled visit should take place in the study, based on the configured visit schedule.
DELAY_DAYS	NUMBER	The number of days between the prior scheduled visit.
DELAY_HOURS	NUMBER	The number of hours between the prior scheduled visit (in addition to the DELAY_DAYS field).
VISIT_WINDOW_BEFORE_DAYS	NUMBER	Indicates how many days before the scheduled date and time the visit can occur, as entered by a study designer.
VISIT_WINDOW_BEFORE_HOURS	NUMBER	Indicates how many hours before the scheduled date and time the visit can occur, as entered by a study designer.
VISIT_WINDOW_AFTER_DAYS	NUMBER	Indicates how many days after the scheduled date and time the visit can occur.
VISIT_WINDOW_AFTER_HOURS	NUMBER	Indicates how many hours after the scheduled date and time the visit can occur.
FREEZE	VARCHAR2(16 CHAR)	Indicates if a visit is frozen by a data manager or CRA. Possible values include FROZEN or UNFROZEN.
VERIFIED	VARCHAR2(16 CHAR)	Indicates the visit's verification status. Data element can be populated with the following values: VERIFIED: A question, form, or visit is verified. UNVERIFIED: A question, form, or visit was once verified, then updated making it unverified. VERIFY_REQUIRED: A question, form, or visit requires verification and is not yet verified. NOT_APPLICABLE
SIGNED	VARCHAR2(16 CHAR)	Indicates if a valid casebook signature is applied to the event. Possible values include SIGNED or UNSIGNED.

Parent topic: Section index

Aggregation context

Derived counts summarizing related form activity for the subject visit.

Column Name	Data Type	Description
FORM_TOTAL_COUNT	NUMBER(10)	Count of all forms created as part of the study design.
FORM_COMPLETED_COUNT	NUMBER(10)	Count of completed forms. Repeating instances are only counted once, meaning that repeating rows are not counted as an additional completed form.

Parent topic: Section index

Audit context

Audit-trail metadata describing row versioning, acting users, and reason-for-change details.

Column Name	Data Type	Description
VERSION_START	TIMESTAMP(6)	Audit trail timestamp when this version of the dataset row became effective. Together with VERSION_END, it defines the validity window for the row version.
VERSION_END	TIMESTAMP(6)	Indicates the date and time of when data was changed, if the data is not current.
OPERATION_TYPE	VARCHAR2(16 CHAR)	Audit trail field that indicates how the dataset row version was produced. CREATED: the row was initially created. MODIFIED: an existing row was updated. REMOVED: the row was removed from the active record set.
USER_NAME	VARCHAR2(255 CHAR)	Audit trail field that represents the user who performed the action. The value for this column may represent a user's actual username or a user's email address, depending on how the user login was defined in Oracle Life Sciences IAMS.
OBJECT_VERSION_NUMBER	NUMBER	Audit trail field that represents the version number of the data.
REASON	VARCHAR2(255 CHAR)	Audit trail reason recorded for the dataset row change. Populated when a reason for change is provided for the row update.
COMMENT	VARCHAR2(2048 CHAR)	Comment recorded for the visit row change. It can come from reason-for-change entry or from system processing.
IS_CURRENT	CHAR(1)	Audit trail flag that indicates whether the dataset row version is the current version (Y) or a historical version (N).

Parent topic: Section index

Reference and system identifiers

System identifiers, numeric reference keys, and technical linkage fields carried with the dataset row.

Column Name	Data Type	Description
STUDY_ID	RAW(16 BYTE)	GUID of the study.
STUDY_WID	NUMBER(10)	A number that represents the unique identifier of the study.
SITE_ID	RAW(16 BYTE)	GUID of the site.
SITE_WID	NUMBER(10)	A number that represents the unique identifier of a site.
FROM_SITE_ID	RAW(16 BYTE)	GUID of the site from which the subject was transferred.
FROM_SITE_WID	NUMBER(10)	Indicates the site numeric identifier from which the subject was transferred.
TO_SITE_ID	RAW(16 BYTE)	GUID of the site to which the subject was transferred.
TO_SITE_WID	NUMBER(10)	Numeric identifier of the site to which the subject was transferred.
USER_ID	RAW(16 BYTE)	GUID of the user.
USER_WID	NUMBER(10)	Indicates a user's numeric identifier.
SUBJECT_ID	RAW(16 BYTE)	GUID of the subject.
SUBJECT_WID	NUMBER(10)	A number that represents the unique identifier of the subject.
SUBJECT_TRANSFER_ID	RAW(16 BYTE)	GUID of the subject transfer record.
SUBJECT_TRANSFER_WID	NUMBER(10)	Numeric identifier of the subject transfer record.
EVENT_ID	RAW(16 BYTE)	GUID of the event.
EVENT_WID	NUMBER(10)	A number that represents the unique identifier of the event.
SCHEDULED_FROM_EVENT_ID	RAW(16 BYTE)	GUID of the parent visit from which the associated visit was scheduled.
SCHEDULED_FROM_EVENT_WID	NUMBER(10)	A number that represents the unique identifier of the parent visit from which the associated visit was scheduled.
ID	RAW(16 BYTE)	GUID of the subject event instance.
SUBJECT_EVENT_INST_WID	NUMBER(10)	A number that represents the unique identifier of the subject event instance.
SUBJECT_TRANSFER_VERSION_START	TIMESTAMP(6)	Date and time when the subject transfer record version became effective.
SUBJECT_TRANSFER_VERSION_END	TIMESTAMP(6)	Date and time when the subject transfer record version stopped being current.
SOFTWARE_VERSION_NUMBER	NUMBER	Audit trail number that increments when the underlying visit row is updated.

Parent topic: Section index

Body ()

Root Schema : DataHubReportDto

Type: object

Tabular dataset response for a dynamic Data Hub query.

columns defines the selected output order, and each row in data aligns positionally to that list.

Show Source

• columns: array columns

  Ordered dataset column names selected by the client.

  Each row in data uses this exact order.

• count: integer (int32)

  Number of rows returned in the current page.

  Example: 2
• data: array data

  Row data aligned positionally with columns.

  Each cell is serialized as a JSON string or null, even for logical numbers and timestamps.

• hasMore: string

  String pagination flag ("true" or "false") indicating whether more matching rows exist after the current page.

  Returned as a string for backward compatibility.

  Example: false
• limit: integer (int32)

  Requested page size.

  Dataset endpoints commonly use 0 to mean unpaginated or all rows.

  Example: 100
• offset: integer (int32)

  Zero-based row offset applied to the result set.

  Dataset endpoints that disable pagination with limit = 0 typically echo offset = 0 in the response.

  Example: 0
• totalResults: integer (int32)

  Total number of matching rows across all pages after filters are applied.

  This can be non-zero even when the current page is empty because the requested offset is beyond the last row.

  Example: 2

{
    "type":"object",
    "properties":{
        "hasMore":{
            "type":"string",
            "description":"<p>String pagination flag (<code>\"true\"</code> or <code>\"false\"</code>) indicating whether more matching rows exist after the current page.</p><p>Returned as a string for backward compatibility.</p>",
            "example":"false"
        },
        "totalResults":{
            "type":"integer",
            "description":"<p>Total number of matching rows across all pages after filters are applied.</p><p>This can be non-zero even when the current page is empty because the requested offset is beyond the last row.</p>",
            "format":"int32",
            "example":2
        },
        "count":{
            "type":"integer",
            "description":"<p>Number of rows returned in the current page.</p>",
            "format":"int32",
            "example":2
        },
        "limit":{
            "type":"integer",
            "description":"<p>Requested page size.</p><p>Dataset endpoints commonly use <code>0</code> to mean unpaginated or all rows.</p>",
            "format":"int32",
            "example":100
        },
        "offset":{
            "type":"integer",
            "description":"<p>Zero-based row offset applied to the result set.</p><p>Dataset endpoints that disable pagination with <code>limit = 0</code> typically echo <code>offset = 0</code> in the response.</p>",
            "format":"int32",
            "example":0
        },
        "columns":{
            "type":"array",
            "description":"<p>Ordered dataset column names selected by the client.</p><p>Each row in <code>data</code> uses this exact order.</p>",
            "example":[
                "STUDY_ID",
                "RECORD_ID",
                "STATUS"
            ],
            "items":{
                "type":"string",
                "description":"<p>Ordered dataset column names selected by the client.</p><p>Each row in <code>data</code> uses this exact order.</p>",
                "example":"[\"STUDY_ID\",\"RECORD_ID\",\"STATUS\"]"
            }
        },
        "data":{
            "type":"array",
            "description":"<p>Row data aligned positionally with <code>columns</code>.</p><p>Each cell is serialized as a JSON string or <code>null</code>, even for logical numbers and timestamps.</p>",
            "example":[
                [
                    "A86F2D0BB610404DB62D37AFA9C20B50",
                    "REC001",
                    "Active"
                ],
                [
                    "A86F2D0BB610404DB62D37AFA9C20B50",
                    "REC002",
                    "Inactive"
                ]
            ],
            "items":{
                "type":"array",
                "description":"<p>Row data aligned positionally with <code>columns</code>.</p><p>Each cell is serialized as a JSON string or <code>null</code>, even for logical numbers and timestamps.</p>",
                "example":[
                    [
                        "A86F2D0BB610404DB62D37AFA9C20B50",
                        "REC001",
                        "Active"
                    ],
                    [
                        "A86F2D0BB610404DB62D37AFA9C20B50",
                        "REC002",
                        "Inactive"
                    ]
                ],
                "items":{
                    "type":"string",
                    "description":"<p>Row data aligned positionally with <code>columns</code>.</p><p>Each cell is serialized as a JSON string or <code>null</code>, even for logical numbers and timestamps.</p>",
                    "example":"[[\"A86F2D0BB610404DB62D37AFA9C20B50\",\"REC001\",\"Active\"],[\"A86F2D0BB610404DB62D37AFA9C20B50\",\"REC002\",\"Inactive\"]]"
                }
            }
        }
    },
    "description":"<p>Tabular dataset response for a dynamic Data Hub query.</p><p><code>columns</code> defines the selected output order, and each row in <code>data</code> aligns positionally to that list.</p>"
}

Nested Schema : columns

Type: array

Ordered dataset column names selected by the client.

Each row in data uses this exact order.

Show Source

• Array of: string

  Ordered dataset column names selected by the client.

  Each row in data uses this exact order.

  Example: ["STUDY_ID","RECORD_ID","STATUS"]

{
    "type":"array",
    "description":"<p>Ordered dataset column names selected by the client.</p><p>Each row in <code>data</code> uses this exact order.</p>",
    "example":[
        "STUDY_ID",
        "RECORD_ID",
        "STATUS"
    ],
    "items":{
        "type":"string",
        "description":"<p>Ordered dataset column names selected by the client.</p><p>Each row in <code>data</code> uses this exact order.</p>",
        "example":"[\"STUDY_ID\",\"RECORD_ID\",\"STATUS\"]"
    }
}

Example:

[
    "STUDY_ID",
    "RECORD_ID",
    "STATUS"
]

Nested Schema : data

Type: array

Row data aligned positionally with columns.

Each cell is serialized as a JSON string or null, even for logical numbers and timestamps.

Show Source

• Array of: array items

  Row data aligned positionally with columns.

  Each cell is serialized as a JSON string or null, even for logical numbers and timestamps.

{
    "type":"array",
    "description":"<p>Row data aligned positionally with <code>columns</code>.</p><p>Each cell is serialized as a JSON string or <code>null</code>, even for logical numbers and timestamps.</p>",
    "example":[
        [
            "A86F2D0BB610404DB62D37AFA9C20B50",
            "REC001",
            "Active"
        ],
        [
            "A86F2D0BB610404DB62D37AFA9C20B50",
            "REC002",
            "Inactive"
        ]
    ],
    "items":{
        "type":"array",
        "description":"<p>Row data aligned positionally with <code>columns</code>.</p><p>Each cell is serialized as a JSON string or <code>null</code>, even for logical numbers and timestamps.</p>",
        "example":[
            [
                "A86F2D0BB610404DB62D37AFA9C20B50",
                "REC001",
                "Active"
            ],
            [
                "A86F2D0BB610404DB62D37AFA9C20B50",
                "REC002",
                "Inactive"
            ]
        ],
        "items":{
            "type":"string",
            "description":"<p>Row data aligned positionally with <code>columns</code>.</p><p>Each cell is serialized as a JSON string or <code>null</code>, even for logical numbers and timestamps.</p>",
            "example":"[[\"A86F2D0BB610404DB62D37AFA9C20B50\",\"REC001\",\"Active\"],[\"A86F2D0BB610404DB62D37AFA9C20B50\",\"REC002\",\"Inactive\"]]"
        }
    }
}

Example:

[
    [
        "A86F2D0BB610404DB62D37AFA9C20B50",
        "REC001",
        "Active"
    ],
    [
        "A86F2D0BB610404DB62D37AFA9C20B50",
        "REC002",
        "Inactive"
    ]
]

Nested Schema : items

Type: array

Row data aligned positionally with columns.

Each cell is serialized as a JSON string or null, even for logical numbers and timestamps.

Show Source

• Array of: string

  Row data aligned positionally with columns.

  Each cell is serialized as a JSON string or null, even for logical numbers and timestamps.

  Example: [["A86F2D0BB610404DB62D37AFA9C20B50","REC001","Active"],["A86F2D0BB610404DB62D37AFA9C20B50","REC002","Inactive"]]

{
    "type":"array",
    "description":"<p>Row data aligned positionally with <code>columns</code>.</p><p>Each cell is serialized as a JSON string or <code>null</code>, even for logical numbers and timestamps.</p>",
    "example":[
        [
            "A86F2D0BB610404DB62D37AFA9C20B50",
            "REC001",
            "Active"
        ],
        [
            "A86F2D0BB610404DB62D37AFA9C20B50",
            "REC002",
            "Inactive"
        ]
    ],
    "items":{
        "type":"string",
        "description":"<p>Row data aligned positionally with <code>columns</code>.</p><p>Each cell is serialized as a JSON string or <code>null</code>, even for logical numbers and timestamps.</p>",
        "example":"[[\"A86F2D0BB610404DB62D37AFA9C20B50\",\"REC001\",\"Active\"],[\"A86F2D0BB610404DB62D37AFA9C20B50\",\"REC002\",\"Inactive\"]]"
    }
}

Example:

[
    [
        "A86F2D0BB610404DB62D37AFA9C20B50",
        "REC001",
        "Active"
    ],
    [
        "A86F2D0BB610404DB62D37AFA9C20B50",
        "REC002",
        "Inactive"
    ]
]

Examples

Select an example BlindedSubjectEventDataSetReport BlindedSubjectEventDataSetEmptyReport

400 Response

Returned when the request is invalid.

• Causes include invalid tenantId or studyId, negative limit or offset, empty selectColumns, invalid dataset columns, invalid whereColumns operator/value combinations, duplicate orderColumns, invalid sortOrder, and malformed typed filter values.
• Error payload format: {"status":"failed","result":null,"errorData":{"errorCode":"...","errorMessage":"...","details":{...}},"version":1}.

Body ()

Root Schema : DataHubResponse

Type: object

Standard Data Hub response envelope.

Successful responses return status as "success" and populate result. Failed responses return status as "failed" and populate errorData.

Show Source

• errorData: object errorData

  Machine-readable error payload when status is "failed".

  This field is null when status is "success".

• result: object result

  Payload returned by the API when status is "success".

  This field is null when status is "failed".

• status: string

  Overall request processing status.

  Allowed values are "success" and "failed".

  Example: success
• version: integer (int32)
  Envelope version number.

  Example: 1

{
    "type":"object",
    "properties":{
        "status":{
            "type":"string",
            "description":"<p>Overall request processing status.</p><p>Allowed values are \"success\" and \"failed\".</p>",
            "example":"success"
        },
        "result":{
            "type":"object",
            "description":"<p>Payload returned by the API when <code>status</code> is \"success\".</p><p>This field is null when <code>status</code> is \"failed\".</p>",
            "example":{
                "message":"Operation succeeded"
            }
        },
        "errorData":{
            "type":"object",
            "description":"<p>Machine-readable error payload when <code>status</code> is \"failed\".</p><p>This field is null when <code>status</code> is \"success\".</p>",
            "example":{
                "errorCode":"VALIDATION_ERROR",
                "errorMessage":"Invalid column name specified in the select columns: SITE_ID1",
                "details":{
                    "field":"selectColumns"
                }
            }
        },
        "version":{
            "type":"integer",
            "description":"Envelope version number.",
            "format":"int32",
            "example":1
        }
    },
    "description":"<p>Standard Data Hub response envelope.</p><p>Successful responses return <code>status</code> as \"success\" and populate <code>result</code>. Failed responses return <code>status</code> as \"failed\" and populate <code>errorData</code>.</p>"
}

Nested Schema : errorData

Type: object

Machine-readable error payload when status is "failed".

This field is null when status is "success".

Example:

{
    "errorCode":"VALIDATION_ERROR",
    "errorMessage":"Invalid column name specified in the select columns: SITE_ID1",
    "details":{
        "field":"selectColumns"
    }
}

Nested Schema : result

Type: object

Payload returned by the API when status is "success".

This field is null when status is "failed".

Example:

{
    "message":"Operation succeeded"
}

Examples

Select an example InvalidSelectColumn NegativePagination InvalidWhereOperator InvalidIsOperatorValue

401 Response

Returned when the request cannot be authenticated.

The response body is empty.

403 Response

Returned when the request is authenticated but the caller is not authorized to access the requested resource.

The response body contains a plain-text authorization message.

Possible response bodies:

• Either the resource does not exist, or the user cannot access the resource.
• The entity is in maintenance mode, or the user cannot access the resource.

Body ()

Root Schema : schema

Type: string

500 Response

Returned when an unexpected server-side error occurs while processing the request.

The response body contains the platform error payload with the error code and description.

Body ()

Root Schema : Status

Type: object

Show Source

• code: string
• description: string

{
    "type":"object",
    "properties":{
        "description":{
            "type":"string"
        },
        "code":{
            "type":"string"
        }
    }
}

Examples

Select an example InternalServerError

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