name: "data-model-designer" description: "Design data models for construction projects. Create entity-relationship diagrams, define schemas, and generate database structures." homepage: "https://datadrivenconstruction.io" metadata: {"openclaw": {"emoji": "📐", "os": ["darwin", "linux", "win32"], "homepage": "https://datadrivenconstruction.io", "requires": {"bins": ["python3"]}}}

Data Model Designer

Business Case

Problem Statement

Construction data management challenges: - Fragmented data across systems - Inconsistent data structures - Missing relationships between entities - Difficult data integration

Solution

Systematic data model design for construction projects, defining entities, relationships, and schemas for effective data management.

Technical Implementation

from typing import Dict, Any, List, Optional
from dataclasses import dataclass, field
from enum import Enum
import json


class DataType(Enum):
    STRING = "string"
    INTEGER = "integer"
    FLOAT = "float"
    BOOLEAN = "boolean"
    DATE = "date"
    DATETIME = "datetime"
    TEXT = "text"
    JSON = "json"


class RelationType(Enum):
    ONE_TO_ONE = "1:1"
    ONE_TO_MANY = "1:N"
    MANY_TO_MANY = "N:M"


class ConstraintType(Enum):
    PRIMARY_KEY = "primary_key"
    FOREIGN_KEY = "foreign_key"
    UNIQUE = "unique"
    NOT_NULL = "not_null"


@dataclass
class Field:
    name: str
    data_type: DataType
    nullable: bool = True
    default: Any = None
    description: str = ""
    constraints: List[ConstraintType] = field(default_factory=list)


@dataclass
class Entity:
    name: str
    description: str
    fields: List[Field] = field(default_factory=list)
    primary_key: str = "id"


@dataclass
class Relationship:
    name: str
    from_entity: str
    to_entity: str
    relation_type: RelationType
    from_field: str
    to_field: str


class ConstructionDataModel:
    """Design data models for construction projects."""

    def __init__(self, project_name: str):
        self.project_name = project_name
        self.entities: Dict[str, Entity] = {}
        self.relationships: List[Relationship] = []

    def add_entity(self, entity: Entity):
        """Add entity to model."""
        self.entities[entity.name] = entity

    def add_relationship(self, relationship: Relationship):
        """Add relationship between entities."""
        self.relationships.append(relationship)

    def create_entity(self, name: str, description: str,
                      fields: List[Dict[str, Any]]) -> Entity:
        """Create entity from field definitions."""

        entity_fields = [
            Field(
                name=f['name'],
                data_type=DataType(f.get('type', 'string')),
                nullable=f.get('nullable', True),
                default=f.get('default'),
                description=f.get('description', ''),
                constraints=[ConstraintType(c) for c in f.get('constraints', [])]
            )
            for f in fields
        ]

        entity = Entity(name=name, description=description, fields=entity_fields)
        self.add_entity(entity)
        return entity

    def create_relationship(self, from_entity: str, to_entity: str,
                           relation_type: str = "1:N",
                           from_field: str = None) -> Relationship:
        """Create relationship between entities."""

        rel = Relationship(
            name=f"{from_entity}_{to_entity}",
            from_entity=from_entity,
            to_entity=to_entity,
            relation_type=RelationType(relation_type),
            from_field=from_field or f"{to_entity.lower()}_id",
            to_field="id"
        )
        self.add_relationship(rel)
        return rel

    def generate_sql_schema(self, dialect: str = "postgresql") -> str:
        """Generate SQL DDL statements."""

        sql = []
        type_map = {
            DataType.STRING: "VARCHAR(255)",
            DataType.INTEGER: "INTEGER",
            DataType.FLOAT: "DECIMAL(15,2)",
            DataType.BOOLEAN: "BOOLEAN",
            DataType.DATE: "DATE",
            DataType.DATETIME: "TIMESTAMP",
            DataType.TEXT: "TEXT",
            DataType.JSON: "JSONB" if dialect == "postgresql" else "JSON"
        }

        for name, entity in self.entities.items():
            columns = []
            for fld in entity.fields:
                col = f"    {fld.name} {type_map.get(fld.data_type, 'VARCHAR(255)')}"
                if not fld.nullable:
                    col += " NOT NULL"
                if ConstraintType.PRIMARY_KEY in fld.constraints:
                    col += " PRIMARY KEY"
                columns.append(col)

            sql.append(f"CREATE TABLE {name} (\n" + ",\n".join(columns) + "\n);")

        for rel in self.relationships:
            sql.append(f"""ALTER TABLE {rel.from_entity}
ADD CONSTRAINT fk_{rel.name}
FOREIGN KEY ({rel.from_field}) REFERENCES {rel.to_entity}({rel.to_field});""")

        return "\n\n".join(sql)

    def generate_json_schema(self) -> Dict[str, Any]:
        """Generate JSON Schema representation."""

        schemas = {}
        for name, entity in self.entities.items():
            properties = {}
            required = []

            for fld in entity.fields:
                prop = {"description": fld.description}
                if fld.data_type == DataType.STRING:
                    prop["type"] = "string"
                elif fld.data_type == DataType.INTEGER:
                    prop["type"] = "integer"
                elif fld.data_type == DataType.FLOAT:
                    prop["type"] = "number"
                elif fld.data_type == DataType.BOOLEAN:
                    prop["type"] = "boolean"
                else:
                    prop["type"] = "string"

                properties[fld.name] = prop
                if not fld.nullable:
                    required.append(fld.name)

            schemas[name] = {
                "type": "object",
                "title": entity.description,
                "properties": properties,
                "required": required
            }
        return schemas

    def generate_er_diagram(self) -> str:
        """Generate Mermaid ER diagram."""

        lines = ["erDiagram"]
        for name, entity in self.entities.items():
            for fld in entity.fields[:5]:
                lines.append(f"    {name} {{")
                lines.append(f"        {fld.data_type.value} {fld.name}")
                lines.append("    }")

        for rel in self.relationships:
            rel_symbol = {
                RelationType.ONE_TO_ONE: "||--||",
                RelationType.ONE_TO_MANY: "||--o{",
                RelationType.MANY_TO_MANY: "}o--o{"
            }.get(rel.relation_type, "||--o{")
            lines.append(f"    {rel.from_entity} {rel_symbol} {rel.to_entity} : \"{rel.name}\"")

        return "\n".join(lines)

    def validate_model(self) -> List[str]:
        """Validate data model for issues."""

        issues = []
        for rel in self.relationships:
            if rel.from_entity not in self.entities:
                issues.append(f"Missing entity: {rel.from_entity}")
            if rel.to_entity not in self.entities:
                issues.append(f"Missing entity: {rel.to_entity}")

        for name, entity in self.entities.items():
            has_pk = any(ConstraintType.PRIMARY_KEY in f.constraints for f in entity.fields)
            if not has_pk:
                issues.append(f"Entity '{name}' has no primary key")

        return issues


class ConstructionEntities:
    """Standard construction data entities."""

    @staticmethod
    def project_entity() -> Entity:
        return Entity(
            name="projects",
            description="Construction projects",
            fields=[
                Field("id", DataType.INTEGER, False, constraints=[ConstraintType.PRIMARY_KEY]),
                Field("code", DataType.STRING, False, constraints=[ConstraintType.UNIQUE]),
                Field("name", DataType.STRING, False),
                Field("status", DataType.STRING),
                Field("start_date", DataType.DATE),
                Field("end_date", DataType.DATE),
                Field("budget", DataType.FLOAT)
            ]
        )

    @staticmethod
    def activity_entity() -> Entity:
        return Entity(
            name="activities",
            description="Schedule activities",
            fields=[
                Field("id", DataType.INTEGER, False, constraints=[ConstraintType.PRIMARY_KEY]),
                Field("project_id", DataType.INTEGER, False),
                Field("wbs_code", DataType.STRING),
                Field("name", DataType.STRING, False),
                Field("start_date", DataType.DATE),
                Field("end_date", DataType.DATE),
                Field("percent_complete", DataType.FLOAT)
            ]
        )

    @staticmethod
    def cost_item_entity() -> Entity:
        return Entity(
            name="cost_items",
            description="Project cost items",
            fields=[
                Field("id", DataType.INTEGER, False, constraints=[ConstraintType.PRIMARY_KEY]),
                Field("project_id", DataType.INTEGER, False),
                Field("wbs_code", DataType.STRING),
                Field("description", DataType.STRING),
                Field("budgeted_cost", DataType.FLOAT),
                Field("actual_cost", DataType.FLOAT)
            ]
        )
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Quick Start

# Create model
model = ConstructionDataModel("Office Building A")

# Add standard entities
model.add_entity(ConstructionEntities.project_entity())
model.add_entity(ConstructionEntities.activity_entity())
model.add_entity(ConstructionEntities.cost_item_entity())

# Add relationships
model.create_relationship("activities", "projects")
model.create_relationship("cost_items", "projects")

# Generate SQL
sql = model.generate_sql_schema("postgresql")
print(sql)

Common Use Cases

1. Custom Entity

model.create_entity(
    name="change_orders",
    description="Project change orders",
    fields=[
        {"name": "id", "type": "integer", "nullable": False, "constraints": ["primary_key"]},
        {"name": "project_id", "type": "integer", "nullable": False},
        {"name": "amount", "type": "float"},
        {"name": "status", "type": "string"}
    ]
)

2. Generate ER Diagram

er_diagram = model.generate_er_diagram()
print(er_diagram)

3. Validate Model

issues = model.validate_model()
for issue in issues:
    print(f"Issue: {issue}")

Resources

• DDC Book: Chapter 2.5 - Data Models and Standards
• Website: https://datadrivenconstruction.io

这个Skill质量中等偏上，文档结构清晰、代码规范，容易上手使用。它能帮助设计建筑项目的数据模型，生成数据库结构。主要优点是功能明确、实现规范；不足之处是功能较为基础，缺乏实际使用示例，说明文档不够详细，部分信息分类可能不够准确。对于需要基础数据建模的用户来说有一定帮助，但复杂场景可能不够用。