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Module C: Collaboration Data & Question Library

Goal: This module acts as Pihu's comprehensive directory for all TagTaste studies (collaborations). It catalogs:

  1. Collaborations and Products: Details of each study, including the specific products tested and their various identifiers.
  2. Question Library: A complete list of every question asked within each collaboration, detailing the exact question text, the section it belonged to, the type of scale or response format used, the database column where the answer is stored, and the actual response options or scale anchors presented.
  3. Demographic Mappings: How user-friendly terms for respondent groups translate into specific database filters.

Pihu uses this module to identify the correct study, products, and relevant questions (by semantically matching attributes from Module A to question details here) to answer user queries.

How this module helps answer our example question: "Compare the overall liking of SLHB5 and SLHB8 from the Signature Latte Cold V2 study. Did SLHB8 meet the benchmark, and what were the main aroma notes for it among millennials?"

  1. Study & Product Identification: Pihu uses productAndCollaborationCatalog to map "Signature Latte Cold V2 study" to its internal ID (e.g., COLLAB_SLC_V2_JAN24), and "SLHB5"/"SLHB8" to their databaseProductIdForCollab (e.g., 1498, 1497) within that study.
  2. Finding Relevant Questions:
    • For "overall liking": Pihu's Data Linking Agent searches the collaborationQuestionLibrary for COLLAB_SLC_V2_JAN24. It looks for questions whose text (e.g., "Overall, how much do you LIKE...") and type (e.g., "9-point Hedonic") semantically match the definition of ATTR_LIKING_OVERALL_001 (from Module A). It would identify QID 43449.
    • For "main aroma notes": It again searches questions in COLLAB_SLC_V2_JAN24, looking for those in the "AROMA" section with scaleTypeUsed like "CATA". It would identify QID 43417 and use its responseOptions list to determine the notes.
  3. Demographic Filter Mapping: Pihu uses demographicSegmentMappings to translate "millennials" into a database filter.

1) Text-Based Structure with Actual Examples (Relevant to the User Question)

A. Product & Collaboration Catalog Entry Form

  • Collaboration ID (Unique Database ID for the study): COLLAB_SLC_V2_JAN24
  • User-Facing Collaboration Name(s) (How users might refer to the study):
    • Signature Latte Cold V2 study
    • SigLatte V2 Jan 2024
  • Status: Active
  • Date of Execution (approximate): 2024-01-10
  • Description (brief overview of the study): Sensory evaluation of two new Signature Latte Cold variants (Version 2).
  • Products Tested in this Collaboration (add rows as needed):
    • Product 1:
      • Database Product ID (unique ID for this product within this study's data): 1497
      • User-Facing Name (common name for this product in this study): Sample B8
      • Internal Code / Alias 1: SLHB8
      • Description (optional): Test variant B of Signature Latte Cold, V2.
    • Product 2:
      • Database Product ID: 1498
      • User-Facing Name: Sample B5
      • Internal Code / Alias 1: SLHB5
      • Description: Test variant A of Signature Latte Cold, V2.
  • Notes for Pihu (internal instructions): This is the primary reference for product IDs and aliases for the "Signature Latte Cold V2 study". SLHB5 is product 1498, SLHB8 is product 1497.
  • Created By: user_project_manager_X
  • Created At: 2024-01-15T09:00:00Z
  • Last Modified By: user_project_manager_X
  • Last Modified At: 2024-01-15T09:00:00Z

B. Collaboration Question Library Entry Form (One entry per question, per collaboration)

(This form would be filled out for EVERY question in the "Signature Latte Cold V2 study" and all other studies)

Example Entry 1: Overall Liking Question

  • Owning Collaboration ID (Links to entry in Product & Collaboration Catalog): COLLAB_SLC_V2_JAN24
  • Database Question ID (QID in raw data for this specific question): 43449
  • Question Text (Verbatim as asked to panelists in this study): Overall, how much do you LIKE or DISLIKE this product?
  • Section Name (Section of the questionnaire, e.g., APPEARANCE, AROMA, PRODUCT EXPERIENCE): PRODUCT EXPERIENCE
  • Scale Type Used (e.g., 9-point Hedonic, CATA, Open-ended Text, Multiple Choice Single Answer): 9-point Hedonic
  • Response Value Column (Database column where the answer/score is stored): option_value_numeric
  • Response Options / Scale Anchors (Actual options or scale points & labels presented in this study for this question):
    • 1: Dislike Extremely
    • 2: Dislike Very Much
    • 3: Dislike Moderately
    • 4: Dislike Slightly
    • 5: Neither Like nor Dislike
    • 6: Like Slightly
    • 7: Like Moderately
    • 8: Like Very Much
    • 9: Like Extremely
  • (Optional Hint for AI) Primary Concept Measured (Canonical Attribute ID from Module A, if this is THE main question for that concept in this study): ATTR_LIKING_OVERALL_001
  • Notes for Pihu (internal instructions for this specific question): Standard overall liking question. Score is directly in option_value_numeric.
  • Created By: user_survey_designer_Y
  • Created At: 2024-01-05T15:00:00Z

Example Entry 2: Aroma Notes Question

  • Owning Collaboration ID: COLLAB_SLC_V2_JAN24
  • Database Question ID: 43417
  • Question Text: Which of these sensations or feelings are more pronounced than the others in this Coffee [Latte]? (Adjusted for latte context based on HCB)
  • Section Name: AROMA
  • Scale Type Used: CATA (Check-All-That-Apply)
  • Response Value Column: selected_option_text (Or the column where CATA selections are stored; might involve multiple rows per respondent/product if data is long format)
  • Response Options (The actual list of aroma notes presented to panelists for QID 43417 in this study):
    • Coffee-Roast
    • Dairy
    • Sugary
    • Cocoa
    • Toasted
    • Nutty
    • Ash/Smokey
    • Over Roasted Coffee
    • Burnt
    • Smokey
    • (This list must be complete for this specific QID in this study. Example options from HCB for SLHB5 Aroma.)
  • (Optional Hint for AI) Primary Concept Measured: ATTR_AROMA_NOTE_CATA_001
  • Notes for Pihu: This is the CATA list for aroma notes. To find "main aroma notes," count frequencies of these listed 'Response Options' selected for QID 43417.
  • Created By: user_survey_designer_Y
  • Created At: 2024-01-05T15:05:00Z

C. Demographic Segment Mapping Entry Form (This structure remains the same as previously discussed)

  • Segment Map ID: DSM_GENERATION_MILLENNIALS_001
  • User Term (What the user says, e.g., "millennials", "gen y"): Millennials
  • Status: Active
  • Description: Defines the Millennial / Gen Y cohort based on TagTaste's standard segmentation.
  • Database Filter Logic (How to find these respondents in the data):
    • Condition (if multiple rules): AND
    • Rules (add rows as needed):
      • Rule 1:
        • Respondent Data Table Column: generation (Name of column in Respondents table)
        • Operator: EQUALS
        • Value: Gen Y (The exact value stored in the database for this segment)
        • Value Data Type: STRING
  • Notes for Pihu (internal instructions): When a user query includes "millennials" or "Gen Y", apply this filter to the respondent data by joining with the Respondents table on user_id and filtering where generation = 'Gen Y'.
  • Created By: user_analyst_Z
  • Created At: 2023-05-10T11:00:00Z
  • Last Modified By: user_analyst_Z
  • Last Modified At: 2023-05-10T11:00:00Z

2) Actual Data Example in JSON (for Module C - New Structure)

This JSON file would store all these catalog entries and question library details.

{
  "moduleName": "Collaboration Data & Question Library",
  "version": "2.0",
  "lastUpdated": "2024-01-25T16:00:00Z",
  "catalog": {
    "productAndCollaborationCatalog": [
      {
        "collaborationId": "COLLAB_SLC_V2_JAN24",
        "userFacingCollaborationNames": ["Signature Latte Cold V2 study", "SigLatte V2 Jan 2024"],
        "status": "Active",
        "dateOfExecution": "2024-01-10",
        "description": "Sensory evaluation of two Signature Latte Cold variants (V2).",
        "productsInCollaboration": [
          { "databaseProductIdForCollab": "1497", "userFacingName": "Sample B8", "internalCode": "SLHB8", "aliases": ["Latte Variant B8"], "description": "Test variant B of Signature Latte Cold, V2." },
          { "databaseProductIdForCollab": "1498", "userFacingName": "Sample B5", "internalCode": "SLHB5", "aliases": ["Latte Variant B5"], "description": "Test variant A of Signature Latte Cold, V2." }
        ],
        "notesForPihu": "Primary reference for product IDs and aliases for the Signature Latte Cold V2 study.",
        "createdBy": "project_manager_jane", "createdAt": "2024-01-15T09:00:00Z", "lastModifiedBy": "project_manager_jane", "lastModifiedAt": "2024-01-15T10:30:00Z"
      }
      // ... Other collaboration catalog entries
    ],
    "collaborationQuestionLibrary": [
      // Questions for COLLAB_SLC_V2_JAN24
      {
        "owningCollaborationId": "COLLAB_SLC_V2_JAN24",
        "databaseQuestionId": "43449",
        "questionText": "Overall, how much do you LIKE or DISLIKE this product?",
        "sectionName": "PRODUCT EXPERIENCE",
        "scaleTypeUsed": "9-point Hedonic",
        "responseValueColumn": "option_value_numeric",
        "responseOptions": [
            {"value": 1, "label": "Dislike Extremely"}, {"value": 2, "label": "Dislike Very Much"},
            {"value": 3, "label": "Dislike Moderately"}, {"value": 4, "label": "Dislike Slightly"},
            {"value": 5, "label": "Neither Like nor Dislike"}, {"value": 6, "label": "Like Slightly"},
            {"value": 7, "label": "Like Moderately"}, {"value": 8, "label": "Like Very Much"},
            {"value": 9, "label": "Like Extremely"}
        ],
        "primaryConceptMeasured": "ATTR_LIKING_OVERALL_001",
        "notesForPihu": "Standard overall liking question for this study."
      },
      {
        "owningCollaborationId": "COLLAB_SLC_V2_JAN24",
        "databaseQuestionId": "43417",
        "questionText": "Which of these sensations or feelings are more pronounced than the others in this Coffee [Latte]?",
        "sectionName": "AROMA",
        "scaleTypeUsed": "CATA",
        "responseValueColumn": "selected_option_text",
        "responseOptions": [
            "Coffee-Roast", "Dairy", "Sugary", "Cocoa", "Toasted", "Nutty",
            "Ash/Smokey", "Over Roasted Coffee", "Burnt", "Smokey",
            "Floral", "Fruity", "Spicy", "Green/Grassy" // Ensure this list is complete for the actual study
        ],
        "primaryConceptMeasured": "ATTR_AROMA_NOTE_CATA_001",
        "notesForPihu": "CATA list for aroma notes. Frequencies of these options determine 'main aroma notes'."
      }
      // ... ALL other questions from COLLAB_SLC_V2_JAN24 would be listed here
      // ... And then questions from all other studies
    ],
    "demographicSegmentMappings": [
      {
        "segmentMapId": "DSM_GENERATION_MILLENNIALS_001",
        "userTerm": "Millennials",
        "status": "Active",
        "description": "Defines Millennials, typically Gen Y cohort.",
        "databaseFilterLogic": {
          "condition": "AND",
          "rules": [{"respondentDataTableColumn": "generation", "operator": "EQUALS", "value": "Gen Y", "valueDataType": "STRING"}]
        },
        "notesForPihu": "Standard filter for Millennial respondents.",
        "createdBy": "analyst_smith", "createdAt": "2023-05-10T11:00:00Z"
      }
      // ... Other demographic segment mappings
    ]
  }
}

3) JSON Structure (for Module C - New Structure, Simplified Comments)

{
  "moduleName": "Collaboration Data & Question Library",
  "version": "2.0",
  "lastUpdated": "YYYY-MM-DDTHH:MM:SSZ",
  "catalog": {
    "productAndCollaborationCatalog": [
      {
        "collaborationId": "STRING_UNIQUE_ID",      // DB ID for the study
        "userFacingCollaborationNames": ["STRING"], // Common names for the study
        "status": "ENUM_STRING",                    // "Active", "Archived"
        "dateOfExecution": "YYYY-MM-DD",
        "description": "TEXT_AREA_STRING",          // Brief study description
        "productsInCollaboration": [                // Products in *this* study
          {
            "databaseProductIdForCollab": "STRING_PRODUCT_ID_IN_DB", // Product's ID in this study's data
            "userFacingName": "STRING",                             // Name used in Collaboration for this product
            "internalCode": "NULLABLE_STRING",                      // e.g., SLHB5
            "aliases": ["STRING_ALIAS_1"],                          // Other names
            "description": "NULLABLE_TEXT_AREA_STRING"
          }
        ],
        "notesForPihu": "TEXT_AREA_STRING",
        "createdBy": "STRING_USER_ID",
        "createdAt": "YYYY-MM-DDTHH:MM:SSZ",
        "lastModifiedBy": "STRING_USER_ID",
        "lastModifiedAt": "YYYY-MM-DDTHH:MM:SSZ"
      }
    ],
    "collaborationQuestionLibrary": [ // A flat list of ALL questions from ALL studies
      {
        "owningCollaborationId": "STRING_COLLAB_ID",      // Links to productAndCollaborationCatalog
        "databaseQuestionId": "STRING_QID_IN_DB",         // QID from raw data
        "questionText": "TEXT_AREA_STRING",               // Verbatim question
        "sectionName": "NULLABLE_STRING",                 // e.g., "AROMA", "OVERALL EVALUATION"
        "scaleTypeUsed": "STRING",                        // e.g., "9-point Hedonic", "CATA", "Open-ended"
        "responseValueColumn": "STRING_DB_COLUMN_NAME",   // DB column for the answer
        "responseOptions": [                              // Critical: Actual options/anchors for THIS QID in THIS study
            // For CATA/MCQ: "Option Text 1", "Option Text 2"
            // For Scales: { "value": 1, "label": "Scale Anchor 1 Text" }
            // Can be null/empty if not applicable (e.g., open-ended text)
        ],
        "primaryConceptMeasured": "NULLABLE_STRING_ATTR_ID", // Optional hint: Links to Module A attribute ID
        "notesForPihu": "TEXT_AREA_STRING"                 // Specific notes about this question if any
      }
    ],
    "demographicSegmentMappings": [ // Defines how user terms for groups map to DB filters
      {
        "segmentMapId": "STRING_UNIQUE_ID_DSM",
        "userTerm": "STRING", // e.g., "Millennials"
        "status": "ENUM_STRING",
        "description": "TEXT_AREA_STRING",
        "databaseFilterLogic": {
          "condition": "ENUM_STRING_LOGICAL", // "AND", "OR"
          "rules": [
            {
              "respondentDataTableColumn": "STRING_DB_COLUMN_NAME",
              "operator": "ENUM_STRING_OPERATOR",
              "value": "ANY_PRIMITIVE_OR_ARRAY",
              "valueDataType": "ENUM_STRING_DATATYPE"
            }
          ]
        },
        "notesForPihu": "TEXT_AREA_STRING",
        "createdBy": "STRING_USER_ID",
        "createdAt": "YYYY-MM-DDTHH:MM:SSZ",
        "lastModifiedBy": "STRING_USER_ID",
        "lastModifiedAt": "YYYY-MM-DDTHH:MM:SSZ"
      }
    ]
  }
}