{
  "format": "dataset-manifest/1",
  "slug": "journeys-unfolded",
  "version": 1,
  "seed": "journeys-unfolded:1",
  "spec": {
    "format": "dataset/1",
    "slug": "journeys-unfolded",
    "name": "Journeys Unfolded",
    "tagline": "Chronicle your adventures and share experiences from unique travel destinations.",
    "description": "Journeys Unfolded is a synthetic dataset designed for travel enthusiasts who document their adventures through detailed logs. This dataset models the experiences and memories tied to various destinations, capturing the essence of travel through personal narratives. It includes unique entries detailing locations visited, the experiences had, and the social interactions made along the way. The table includes a variety of destinations, with some being off-the-beaten-path while others are popular tourist spots that see a high density of visits. The data is structured to allow users to explore common travel routes as well as rare entries, making it an interesting resource for practicing SQL and teaching data manipulation. As a synthetic dataset, it provides a safe and flexible environment for users to experiment with queries and gain insights into travel patterns and social connections.",
    "domain": "travel",
    "shape": "graph-edges",
    "useCases": [
      "sql-practice",
      "teaching"
    ],
    "keywords": [
      "travel",
      "adventure",
      "journals",
      "destinations",
      "logs",
      "experiences",
      "social",
      "connections"
    ],
    "locale": "en",
    "license": "CC0-1.0",
    "version": 1,
    "tables": {
      "travel_logs": {
        "description": "Each row represents a unique travel log entry capturing a destination, experiences, and social interactions. The logs link different destinations and highlight the relationships between travelers and their journeys.",
        "rows": 500,
        "columns": {
          "id": {
            "kind": "pk",
            "description": "Unique identifier for each travel log entry."
          },
          "destination": {
            "kind": "words",
            "min": 5,
            "max": 100,
            "description": "Name of the destination visited.",
            "nullable": true,
            "when": {
              "column": "location_type",
              "in": [
                "tourist"
              ]
            }
          },
          "travel_date": {
            "kind": "date",
            "from": "2020-01-01",
            "to": "2023-12-31",
            "description": "Date of travel to the destination.",
            "trend": "growing"
          },
          "experience": {
            "kind": "paragraph",
            "min": 50,
            "max": 500,
            "description": "Detailed account of experiences at the destination.",
            "nullable": true
          },
          "connections": {
            "kind": "words",
            "min": 5,
            "max": 200,
            "description": "Names of other travelers met during the journey.",
            "nullable": true
          },
          "location_type": {
            "kind": "enum",
            "values": [
              "tourist",
              "off-the-beaten-path"
            ],
            "description": "Indicates whether the destination is a popular tourist spot or a lesser-known location."
          }
        }
      }
    },
    "structure": "single-table",
    "traits": [
      "free-text",
      "high-cardinality",
      "nullable"
    ],
    "analysisQuestions": [
      "What are the most common destinations logged by travelers?",
      "How do experiences differ between tourist spots and off-the-beaten-path locations?",
      "What trends can be observed in travel dates throughout the year?",
      "How do social interactions vary between different types of destinations?"
    ],
    "suggestedQueries": [
      {
        "title": "Find all travel logs for a specific destination",
        "sql": "SELECT * FROM travel_logs WHERE destination = 'Paris';",
        "dialect": "postgres"
      },
      {
        "title": "Count logs by location type",
        "sql": "SELECT location_type, COUNT(*) FROM travel_logs GROUP BY location_type;",
        "dialect": "postgres"
      },
      {
        "title": "List unique travelers met during journeys",
        "sql": "SELECT DISTINCT connections FROM travel_logs;",
        "dialect": "postgres"
      },
      {
        "title": "Find the most frequent travel date",
        "sql": "SELECT travel_date, COUNT(*) FROM travel_logs GROUP BY travel_date ORDER BY COUNT(*) DESC LIMIT 1;",
        "dialect": "postgres"
      }
    ],
    "usageScenarios": [
      {
        "title": "Travel Blogger Database",
        "body": "A travel blogger can utilize this dataset to analyze their own travel logs, comparing unique experiences with popular destinations. This analysis can help them create engaging content that resonates with their audience."
      },
      {
        "title": "Data Science in Travel Industry",
        "body": "Data scientists working in the travel industry can use this dataset to identify travel patterns and preferences. Insights gained can inform marketing strategies and enhance customer experiences."
      },
      {
        "title": "Interactive Learning for Students",
        "body": "Students in data analytics courses can practice SQL queries using this dataset. They can explore different aspects of travel behavior and learn to derive insights from real-world-like data."
      }
    ]
  },
  "counts": {
    "travel_logs": 500
  },
  "stats": {
    "travel_logs": {
      "rows": 500,
      "columns": {
        "id": {
          "nulls": 0,
          "distinct": 500,
          "min": 1,
          "max": 500
        },
        "destination": {
          "nulls": 266,
          "distinct": 234
        },
        "travel_date": {
          "nulls": 0,
          "distinct": 430,
          "min": "2020-01-10",
          "max": "2023-12-31"
        },
        "experience": {
          "nulls": 47,
          "distinct": 453
        },
        "connections": {
          "nulls": 43,
          "distinct": 457
        },
        "location_type": {
          "nulls": 0,
          "distinct": 2,
          "min": "off-the-beaten-path",
          "max": "tourist"
        }
      }
    }
  },
  "artifacts": [
    {
      "file": "csv/travel_logs.csv",
      "format": "csv",
      "table": "travel_logs",
      "key": "datasets/journeys-unfolded/v1/csv/travel_logs.csv",
      "url": "https://database-sample-website.s3.eu-north-1.amazonaws.com/datasets/journeys-unfolded/v1/csv/travel_logs.csv",
      "bytes": 485120,
      "sha256": "ca50fb0edea275022099a7f071cba68e4d0f60a86d59013618749e263aefeb88",
      "rows": 500,
      "contentType": "text/csv; charset=utf-8"
    },
    {
      "file": "journeys-unfolded.json",
      "format": "json",
      "table": null,
      "key": "datasets/journeys-unfolded/v1/journeys-unfolded.json",
      "url": "https://database-sample-website.s3.eu-north-1.amazonaws.com/datasets/journeys-unfolded/v1/journeys-unfolded.json",
      "bytes": 557875,
      "sha256": "00e03940e59ffe69d3049522a8121111eb542e96d890608441562d09bba89b3f",
      "rows": null,
      "contentType": "application/json; charset=utf-8"
    },
    {
      "file": "sql/postgres.sql",
      "format": "sql-postgres",
      "table": null,
      "key": "datasets/journeys-unfolded/v1/sql/postgres.sql",
      "url": "https://database-sample-website.s3.eu-north-1.amazonaws.com/datasets/journeys-unfolded/v1/sql/postgres.sql",
      "bytes": 496832,
      "sha256": "dc191e980cc2bf1fbfd81fdf1e08dac2133585595a92b098c6e7a6c02f122180",
      "rows": null,
      "contentType": "application/sql; charset=utf-8"
    },
    {
      "file": "sql/mysql.sql",
      "format": "sql-mysql",
      "table": null,
      "key": "datasets/journeys-unfolded/v1/sql/mysql.sql",
      "url": "https://database-sample-website.s3.eu-north-1.amazonaws.com/datasets/journeys-unfolded/v1/sql/mysql.sql",
      "bytes": 496727,
      "sha256": "2ec54fbb4485742493ffceb5c5fa51a4c0e646327303876d88cef04a27b50189",
      "rows": null,
      "contentType": "application/sql; charset=utf-8"
    },
    {
      "file": "sql/mssql.sql",
      "format": "sql-mssql",
      "table": null,
      "key": "datasets/journeys-unfolded/v1/sql/mssql.sql",
      "url": "https://database-sample-website.s3.eu-north-1.amazonaws.com/datasets/journeys-unfolded/v1/sql/mssql.sql",
      "bytes": 498950,
      "sha256": "1447646515105369b7b5a646f0bd327b9963807057d3f84dad167e54bda3e1f0",
      "rows": null,
      "contentType": "application/sql; charset=utf-8"
    },
    {
      "file": "sql/sqlite.sql",
      "format": "sql-sqlite",
      "table": null,
      "key": "datasets/journeys-unfolded/v1/sql/sqlite.sql",
      "url": "https://database-sample-website.s3.eu-north-1.amazonaws.com/datasets/journeys-unfolded/v1/sql/sqlite.sql",
      "bytes": 496685,
      "sha256": "69052736bc69d75ff3998a85b071cf920f0e29d840f8a7c3571a597caaeef02a",
      "rows": null,
      "contentType": "application/sql; charset=utf-8"
    },
    {
      "file": "prisma/seed.ts",
      "format": "prisma-seed",
      "table": null,
      "key": "datasets/journeys-unfolded/v1/prisma/seed.ts",
      "url": "https://database-sample-website.s3.eu-north-1.amazonaws.com/datasets/journeys-unfolded/v1/prisma/seed.ts",
      "bytes": 536581,
      "sha256": "3eb72d2a76bf58773c9d5f057878d369101125e1b141b2acaa3ecdb73a63773f",
      "rows": null,
      "contentType": "application/typescript; charset=utf-8"
    },
    {
      "file": "django/fixtures.json",
      "format": "django-fixture",
      "table": null,
      "key": "datasets/journeys-unfolded/v1/django/fixtures.json",
      "url": "https://database-sample-website.s3.eu-north-1.amazonaws.com/datasets/journeys-unfolded/v1/django/fixtures.json",
      "bytes": 580852,
      "sha256": "416fd69efd3d07c6b445d7690842a27d48b870687d0e1d3208b5764a5740a252",
      "rows": null,
      "contentType": "application/json; charset=utf-8"
    }
  ],
  "publishedAt": 1788767533296,
  "updatedAt": 1788767533296
}