{
  "format": "dataset-manifest/1",
  "slug": "citizen-science-and-data-collection-platform",
  "version": 3,
  "seed": "citizen-science-and-data-collection-platform:1",
  "spec": {
    "format": "dataset/1",
    "slug": "citizen-science-and-data-collection-platform",
    "name": "Community Engagement in Data Collection",
    "tagline": "Community participation data on environmental observations, projects, sensors, and quizzes.",
    "description": "Citizens actively contribute to scientific research by collecting environmental data and wildlife observations through various initiatives. This dataset includes tables that model participant engagement, project details, and the types of observations made. It allows users to explore how citizen science projects foster community involvement and the extent of data collection across different regions. The observations are particularly concentrated in urban areas, while remote regions show less activity, highlighting disparities in participation. The tables are interconnected, enabling comprehensive analysis of engagement metrics, the effectiveness of educational quizzes, and the impact of sensor data on overall participation. This synthetic dataset serves as an excellent resource for practicing data analysis, creating visualizations for BI dashboards, and understanding community-driven data collection efforts.",
    "domain": "government",
    "shape": "time-series",
    "useCases": [
      "analytics-demo",
      "bi-dashboards"
    ],
    "keywords": [
      "citizen science",
      "community engagement",
      "data collection",
      "environmental observations",
      "scientific research",
      "public participation"
    ],
    "locale": "en",
    "license": "CC0-1.0",
    "version": 1,
    "tables": {
      "participants": {
        "description": "This table holds information about the citizens participating in various data collection projects. Each row represents a unique participant, linking to their observations and project involvement.",
        "rows": 200,
        "columns": {
          "participant_id": {
            "kind": "pk",
            "description": "Unique identifier for each participant."
          },
          "full_name": {
            "kind": "fullName",
            "description": "The full name of the participant."
          },
          "email": {
            "kind": "email",
            "from": "full_name",
            "description": "Email address of the participant."
          },
          "city": {
            "kind": "city",
            "description": "City where the participant resides."
          },
          "registration_date": {
            "kind": "date",
            "from": "2020-01-01",
            "to": "2023-12-31",
            "description": "Date when the participant registered."
          }
        }
      },
      "projects": {
        "description": "This table details the various citizen science projects available. Each project can have multiple associated observations and participants.",
        "rows": 50,
        "columns": {
          "project_id": {
            "kind": "pk",
            "description": "Unique identifier for each project."
          },
          "project_name": {
            "kind": "words",
            "min": 1,
            "max": 3,
            "description": "Name of the citizen science project.",
            "pool": [
              "Eco",
              "Citizen",
              "Data",
              "Science",
              "Engagement",
              "Project",
              "Green",
              "Community",
              "Research",
              "Wildlife",
              "Conservation",
              "Monitoring",
              "Survey",
              "Habitat",
              "Mapping",
              "Activity",
              "Participatory",
              "Study",
              "Initiative",
              "Collaboration"
            ]
          },
          "start_date": {
            "kind": "date",
            "from": "2020-01-01",
            "to": "2023-12-31",
            "description": "Start date of the project."
          },
          "end_date": {
            "kind": "date",
            "from": "2020-01-01",
            "to": "2023-12-31",
            "description": "End date of the project."
          },
          "project_type": {
            "kind": "enum",
            "values": [
              "wildlife observation",
              "environmental monitoring",
              "community survey"
            ],
            "description": "Type of project conducted.",
            "weights": [
              6,
              2,
              2
            ]
          }
        }
      },
      "observations": {
        "description": "This table contains the detailed observations made by participants during various projects. Each observation is linked to a specific participant and project.",
        "rows": {
          "per": "participants",
          "via": "participant_id",
          "min": 1,
          "max": 5,
          "skew": "long-tail"
        },
        "columns": {
          "observation_id": {
            "kind": "pk",
            "description": "Unique identifier for each observation."
          },
          "participant_id": {
            "kind": "fk",
            "ref": "participants.participant_id",
            "description": "Reference to the participant making the observation."
          },
          "project_id": {
            "kind": "fk",
            "ref": "projects.project_id",
            "description": "Reference to the project associated with the observation."
          },
          "observation_date": {
            "kind": "datetime",
            "from": "2020-01-01",
            "to": "2023-12-31",
            "dayProfile": "business",
            "description": "Date and time of the observation."
          },
          "location": {
            "kind": "words",
            "min": 1,
            "max": 3,
            "description": "Description of the observation location.",
            "pool": [
              "Park",
              "River",
              "Forest",
              "Beach",
              "Urban",
              "Rural",
              "Wetland",
              "Field",
              "Neighborhood",
              "School",
              "Community",
              "Garden",
              "Campus",
              "Trail",
              "Mountain",
              "Coast",
              "Estuary",
              "Site",
              "Area",
              "Zone"
            ]
          },
          "observation_details": {
            "kind": "paragraph",
            "min": 10,
            "max": 200,
            "description": "Detailed notes about the observation."
          }
        }
      },
      "quizzes": {
        "description": "This table models the quizzes designed to educate participants about data collection and environmental awareness. Each quiz can be linked to multiple projects.",
        "rows": 30,
        "columns": {
          "quiz_id": {
            "kind": "pk",
            "description": "Unique identifier for each quiz."
          },
          "quiz_name": {
            "kind": "words",
            "min": 1,
            "max": 3,
            "description": "Name of the quiz.",
            "pool": [
              "Knowledge",
              "Challenge",
              "Test",
              "Trivia",
              "Assessment",
              "Check",
              "Quiz",
              "Evaluation",
              "Engagement",
              "Participation",
              "Awareness",
              "Learning",
              "Fun",
              "Interactive",
              "Explore",
              "Discover",
              "Facts",
              "Skills",
              "Topics",
              "Concepts"
            ]
          },
          "project_id": {
            "kind": "fk",
            "ref": "projects.project_id",
            "description": "Reference to the project for which the quiz is created."
          },
          "creation_date": {
            "kind": "date",
            "from": "2020-01-01",
            "to": "2023-12-31",
            "description": "Date when the quiz was created."
          },
          "total_questions": {
            "kind": "int",
            "min": 5,
            "max": 20,
            "description": "Total number of questions in the quiz."
          }
        }
      },
      "sensor_data": {
        "description": "This table holds the sensor data collected in real-time for various environmental factors. Data from sensors can complement citizen observations and provide context.",
        "rows": {
          "per": "projects",
          "via": "project_id",
          "min": 1,
          "max": 10,
          "skew": "heavy-tail"
        },
        "columns": {
          "sensor_id": {
            "kind": "pk",
            "description": "Unique identifier for each sensor reading."
          },
          "project_id": {
            "kind": "fk",
            "ref": "projects.project_id",
            "description": "Reference to the project from which the data is sourced."
          },
          "timestamp": {
            "kind": "datetime",
            "from": "2020-01-01",
            "to": "2023-12-31",
            "dayProfile": "business",
            "description": "Date and time of the sensor reading."
          },
          "temperature": {
            "kind": "decimal",
            "min": -30,
            "max": 50,
            "scale": 1,
            "description": "Temperature reading in degrees Celsius."
          },
          "humidity": {
            "kind": "decimal",
            "min": 0,
            "max": 100,
            "scale": 1,
            "description": "Humidity percentage reading."
          },
          "air_quality_index": {
            "kind": "int",
            "min": 0,
            "max": 500,
            "description": "Air quality index value.",
            "distribution": "long-tail"
          }
        }
      }
    },
    "structure": "multi-table",
    "traits": [
      "timestamped",
      "categorical",
      "nullable",
      "high-cardinality"
    ],
    "analysisQuestions": [
      "What environmental factors are most commonly observed by participants?",
      "How do quiz scores correlate with the number of observations made?",
      "Which projects have the highest participant engagement and why?",
      "What are the trends in environmental data collected over time?",
      "How does urban participation compare to rural and remote areas?"
    ],
    "suggestedQueries": [
      {
        "title": "Join Participants and Observations",
        "sql": "SELECT p.full_name, o.observation_details FROM participants p JOIN observations o ON p.participant_id = o.participant_id;",
        "dialect": "postgres"
      },
      {
        "title": "Count Observations by Project",
        "sql": "SELECT project_id, COUNT(*) FROM observations GROUP BY project_id;",
        "dialect": "postgres"
      },
      {
        "title": "Average Temperature by Project",
        "sql": "SELECT project_id, AVG(temperature) FROM sensor_data GROUP BY project_id;",
        "dialect": "postgres"
      },
      {
        "title": "Observations Over Time",
        "sql": "SELECT DATE(observation_date), COUNT(*) FROM observations GROUP BY DATE(observation_date);",
        "dialect": "postgres"
      },
      {
        "title": "Top Projects by Participant Count",
        "sql": "SELECT project_id, COUNT(DISTINCT participant_id) FROM observations GROUP BY project_id ORDER BY COUNT(DISTINCT participant_id) DESC;",
        "dialect": "postgres"
      }
    ],
    "usageScenarios": [
      {
        "title": "Environmental Researchers",
        "body": "Environmental researchers can utilize this dataset to analyze citizen-reported observations and sensor data to identify trends in biodiversity. By assessing the data collected through various projects, they can better understand how public engagement affects environmental monitoring and conservation efforts."
      },
      {
        "title": "Government Agencies",
        "body": "Government agencies can leverage this dataset to evaluate the effectiveness of citizen science programs. By analyzing participant engagement and the quality of data collected, they can make informed decisions about future initiatives and allocate resources to enhance community involvement in environmental issues."
      },
      {
        "title": "Data Analysts",
        "body": "Data analysts can use this dataset to create visualizations and dashboards that track participant engagement over time. By exploring the trends and patterns in observations, they can provide insights to stakeholders on the impact of educational quizzes and the effectiveness of different project types."
      },
      {
        "title": "Community Organizers",
        "body": "Community organizers can analyze this dataset to identify areas with low participation rates and devise strategies to engage more citizens in data collection efforts. By understanding the demographics of participants and the types of projects that attract interest, they can tailor outreach programs to increase involvement."
      }
    ]
  },
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    "quizzes": 30,
    "sensor_data": 182
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