datadrivenconstruction

Data Lineage Tracker

Data Analysisv2.1.0
By datadrivenconstructionUpdated 2026-05-172 versions · latest released 2026-02-15data-lineage-tracker@clawhub_datadrivenconstruction/data-lineage-tracker
Data Insights#Debugging

According to AlphaMoat, as of 2026-09, Data Lineage Tracker has 4,677 downloads and 0 stars — ranked #2,034 of 5,078 AI skills overall, and #162 of 399 in Data Analysis.

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Top 41% overall · Top 41% in Data Analysis
PlatformInstallsDownloadsStarsComments
ClawHub ↗1564.6K--
SkillHub ↗1564.7K-—

Platforms count differently and update at different times.

What this skill does

It can record sources and processing steps to help debug issues, assess change impact and prepare audit reports. Project files and exports may reveal internal systems, locations, owners and workflows; use only intended files and remove unnecessary sensitive details before sharing. Requires Python and a reviewed integration of the example tracker. Sources, entities and transformations must actually be registered; it does not automatically discover every operation across external systems. Lineage reflects supplied records and can omit unrecorded changes, so validate completeness before using an export as audit evidence. Review report paths and identifiers before sharing; a lineage diagram is not a compliance certification or tamper-proof log.

Profile published 2026-10-27

What you can do with it

  • Record data sources and transformation steps
  • Trace upstream/downstream dependencies and assess impact

When to use it

  • When input files are approved and report audience and scope are clear

Example prompts

Generated from the skill’s documentation as examples; not results of actual runs.

Describe a dataset lineage without exporting real project content.
List information to review and minimize before sharing a lineage report.

Monthly Trend

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SKILL.md (original)

The author’s original file, shown as plain text without edits or review by AlphaMoat. Links are not clickable; check commands before running them. Fetched 2026-10-23.

18 KB · ClawHub v2.1.0
---
name: "data-lineage-tracker"
description: "Track data origin, transformations, and flow through construction systems. Essential for audit trails, compliance, and debugging data issues."
homepage: "https://datadrivenconstruction.io"
metadata: {"openclaw": {"emoji": "✔️", "os": ["darwin", "linux", "win32"], "homepage": "https://datadrivenconstruction.io", "requires": {"bins": ["python3"]}}}
---
# Data Lineage Tracker for Construction

## Overview

Show all (474 lines)
Track the origin, transformations, and flow of construction data through systems. Provides audit trails for compliance, helps debug data issues, and ensures data governance.

## Business Case

Construction projects require data accountability:
- **Audit Compliance**: Know where every number came from
- **Issue Resolution**: Trace data problems to their source
- **Change Impact**: Understand what downstream systems are affected
- **Regulatory Requirements**: Maintain data provenance for legal/insurance

## Technical Implementation

```python
from dataclasses import dataclass, field
from typing import List, Dict, Any, Optional, Set
from datetime import datetime
from enum import Enum
import json
import hashlib
import uuid

class TransformationType(Enum):
    EXTRACT = "extract"
    TRANSFORM = "transform"
    LOAD = "load"
    AGGREGATE = "aggregate"
    JOIN = "join"
    FILTER = "filter"
    CALCULATE = "calculate"
    MANUAL_EDIT = "manual_edit"
    IMPORT = "import"
    EXPORT = "export"

@dataclass
class DataSource:
    id: str
    name: str
    system: str
    location: str
    owner: str
    created_at: datetime

@dataclass
class TransformationStep:
    id: str
    transformation_type: TransformationType
    description: str
    input_entities: List[str]
    output_entities: List[str]
    logic: str  # SQL, Python, or description
    performed_by: str  # user or system
    performed_at: datetime
    parameters: Dict[str, Any] = field(default_factory=dict)

@dataclass
class DataEntity:
    id: str
    name: str
    source_id: str
    entity_type: str  # table, file, field, record
    created_at: datetime
    version: int = 1
    checksum: Optional[str] = None
    parent_entities: List[str] = field(default_factory=list)
    metadata: Dict[str, Any] = field(default_factory=dict)

@dataclass
class LineageRecord:
    id: str
    entity_id: str
    transformation_id: str
    upstream_entities: List[str]
    downstream_entities: List[str]
    recorded_at: datetime

class ConstructionDataLineageTracker:
    """Track data lineage for construction data flows."""

    def __init__(self, project_id: str):
        self.project_id = project_id
        self.sources: Dict[str, DataSource] = {}
        self.entities: Dict[str, DataEntity] = {}
        self.transformations: Dict[str, TransformationStep] = {}
        self.lineage_records: List[LineageRecord] = []

    def register_source(self, name: str, system: str, location: str, owner: str) -> DataSource:
        """Register a new data source."""
        source = DataSource(
            id=f"SRC-{uuid.uuid4().hex[:8]}",
            name=name,
            system=system,
            location=location,
            owner=owner,
            created_at=datetime.now()
        )
        self.sources[source.id] = source
        return source

    def register_entity(self, name: str, source_id: str, entity_type: str,
                       parent_entities: List[str] = None,
                       metadata: Dict = None) -> DataEntity:
        """Register a data entity (table, file, field)."""
        entity = DataEntity(
            id=f"ENT-{uuid.uuid4().hex[:8]}",
            name=name,
            source_id=source_id,
            entity_type=entity_type,
            created_at=datetime.now(),
            parent_entities=parent_entities or [],
            metadata=metadata or {}
        )
        self.entities[entity.id] = entity
        return entity

    def calculate_checksum(self, data: Any) -> str:
        """Calculate checksum for data verification."""
        if isinstance(data, str):
            content = data
        else:
            content = json.dumps(data, sort_keys=True, default=str)
        return hashlib.sha256(content.encode()).hexdigest()[:16]

    def record_transformation(self,
                             transformation_type: TransformationType,
                             description: str,
                             input_entities: List[str],
                             output_entities: List[str],
                             logic: str,
                             performed_by: str,
                             parameters: Dict = None) -> TransformationStep:
        """Record a data transformation."""
        transformation = TransformationStep(
            id=f"TRF-{uuid.uuid4().hex[:8]}",
            transformation_type=transformation_type,
            description=description,
            input_entities=input_entities,
            output_entities=output_entities,
            logic=logic,
            performed_by=performed_by,
            performed_at=datetime.now(),
            parameters=parameters or {}
        )
        self.transformations[transformation.id] = transformation

        # Create lineage records
        for output_id in output_entities:
            record = LineageRecord(
                id=f"LIN-{uuid.uuid4().hex[:8]}",
                entity_id=output_id,
                transformation_id=transformation.id,
                upstream_entities=input_entities,
                downstream_entities=[],
                recorded_at=datetime.now()
            )
            self.lineage_records.append(record)

            # Update downstream references for input entities
            for input_id in input_entities:
                for existing_record in self.lineage_records:
                    if existing_record.entity_id == input_id:
                        existing_record.downstream_entities.append(output_id)

        return transformation

    def trace_upstream(self, entity_id: str, depth: int = None) -> List[Dict]:
        """Trace all upstream sources of an entity."""
        visited = set()
        lineage = []

        def trace(eid: str, current_depth: int):
            if eid in visited:
                return
            if depth is not None and current_depth > depth:
                return

            visited.add(eid)

            entity = self.entities.get(eid)
            if not entity:
                return

            # Find transformations that produced this entity
            for record in self.lineage_records:
                if record.entity_id == eid:
                    transformation = self.transformations.get(record.transformation_id)
                    if transformation:
                        lineage.append({
                            'entity': entity.name,
                            'entity_id': eid,
                            'depth': current_depth,
                            'transformation': transformation.description,
                            'transformation_type': transformation.transformation_type.value,
                            'performed_at': transformation.performed_at.isoformat(),
                            'performed_by': transformation.performed_by,
                            'upstream': record.upstream_entities
                        })

                        for upstream_id in record.upstream_entities:
                            trace(upstream_id, current_depth + 1)

        trace(entity_id, 0)
        return sorted(lineage, key=lambda x: x['depth'])

    def trace_downstream(self, entity_id: str, depth: int = None) -> List[Dict]:
        """Trace all downstream dependencies of an entity."""
        visited = set()
        dependencies = []

        def trace(eid: str, current_depth: int):
            if eid in visited:
                return
            if depth is not None and current_depth > depth:
                return

            visited.add(eid)

            entity = self.entities.get(eid)
            if not entity:
                return

            # Find entities that use this entity
            for record in self.lineage_records:
                if eid in record.upstream_entities:
                    transformation = self.transformations.get(record.transformation_id)
                    if transformation:
                        dependencies.append({
                            'entity': self.entities[record.entity_id].name if record.entity_id in self.entities else record.entity_id,
                            'entity_id': record.entity_id,
                            'depth': current_depth,
                            'transformation': transformation.description,
                            'transformation_type': transformation.transformation_type.value
                        })

                        trace(record.entity_id, current_depth + 1)

        trace(entity_id, 0)
        return sorted(dependencies, key=lambda x: x['depth'])

    def get_entity_history(self, entity_id: str) -> List[Dict]:
        """Get complete history of changes to an entity."""
        history = []

        for record in self.lineage_records:
            if record.entity_id == entity_id:
                transformation = self.transformations.get(record.transformation_id)
                if transformation:
                    history.append({
                        'timestamp': transformation.performed_at.isoformat(),
                        'action': transformation.transformation_type.value,
                        'description': transformation.description,
                        'performed_by': transformation.performed_by,
                        'inputs': [
                            self.entities[eid].name if eid in self.entities else eid
                            for eid in record.upstream_entities
                        ]
                    })

        return sorted(history, key=lambda x: x['timestamp'])

    def impact_analysis(self, entity_id: str) -> Dict:
        """Analyze impact of changes to an entity."""
        downstream = self.trace_downstream(entity_id)

        impact = {
            'entity': self.entities[entity_id].name if entity_id in self.entities else entity_id,
            'total_affected': len(downstream),
            'affected_by_depth': {},
            'affected_entities': downstream
        }

        for dep in downstream:
            depth = dep['depth']
            impact['affected_by_depth'][depth] = impact['affected_by_depth'].get(depth, 0) + 1

        return impact

    def validate_lineage(self) -> List[str]:
        """Validate lineage for completeness and consistency."""
        issues = []

        # Check for orphan entities (no source or transformation)
        for eid, entity in self.entities.items():
            has_lineage = any(r.entity_id == eid for r in self.lineage_records)
            if not has_lineage and entity.entity_type != 'source':
                issues.append(f"Entity '{entity.name}' has no lineage record")

        # Check for broken references
        all_entity_ids = set(self.entities.keys())
        for record in self.lineage_records:
            for upstream_id in record.upstream_entities:
                if upstream_id not in all_entity_ids:
                    issues.append(f"Lineage references unknown entity: {upstream_id}")

        # Check for circular dependencies
        for eid in self.entities:
            upstream = set()
            to_check = [eid]
            while to_check:
                current = to_check.pop()
                if current in upstream:
                    issues.append(f"Circular dependency detected involving entity: {self.entities[eid].name}")
                    break
                upstream.add(current)
                for record in self.lineage_records:
                    if record.entity_id == current:
                        to_check.extend(record.upstream_entities)

        return issues

    def generate_lineage_graph(self, entity_id: str) -> str:
        """Generate Mermaid diagram of lineage."""
        lines = ["```mermaid", "graph LR"]

        upstream = self.trace_upstream(entity_id, depth=5)
        downstream = self.trace_downstream(entity_id, depth=5)

        # Add nodes
        added_nodes = set()
        for item in upstream + downstream:
            node_id = item['entity_id'].replace('-', '_')
            if node_id not in added_nodes:
                entity = self.entities.get(item['entity_id'])
                name = entity.name if entity else item['entity_id']
                lines.append(f"    {node_id}[{name}]")
                added_nodes.add(node_id)

        # Add target node
        target_node = entity_id.replace('-', '_')
        if target_node not in added_nodes:
            entity = self.entities.get(entity_id)
            name = entity.name if entity else entity_id
            lines.append(f"    {target_node}[{name}]:::target")

        # Add edges
        for item in upstream:
            for upstream_id in item.get('upstream', []):
                from_node = upstream_id.replace('-', '_')
                to_node = item['entity_id'].replace('-', '_')
                lines.append(f"    {from_node} --> {to_node}")

        for item in downstream:
            from_node = entity_id.replace('-', '_')
            to_node = item['entity_id'].replace('-', '_')
            if to_node != from_node:
                lines.append(f"    {from_node} --> {to_node}")

        lines.append("    classDef target fill:#f96")
        lines.append("```")

        return "\n".join(lines)

    def export_lineage(self) -> Dict:
        """Export complete lineage data."""
        return {
            'project_id': self.project_id,
            'exported_at': datetime.now().isoformat(),
            'sources': {k: {
                'id': v.id,
                'name': v.name,
                'system': v.system,
                'location': v.location,
                'owner': v.owner
            } for k, v in self.sources.items()},
            'entities': {k: {
                'id': v.id,
                'name': v.name,
                'source_id': v.source_id,
                'entity_type': v.entity_type,
                'parent_entities': v.parent_entities
            } for k, v in self.entities.items()},
            'transformations': {k: {
                'id': v.id,
                'type': v.transformation_type.value,
                'description': v.description,
                'input_entities': v.input_entities,
                'output_entities': v.output_entities,
                'performed_by': v.performed_by,
                'performed_at': v.performed_at.isoformat()
            } for k, v in self.transformations.items()},
            'lineage_records': [{
                'id': r.id,
                'entity_id': r.entity_id,
                'transformation_id': r.transformation_id,
                'upstream_entities': r.upstream_entities
            } for r in self.lineage_records]
        }

    def generate_report(self) -> str:
        """Generate lineage report."""
        lines = [f"# Data Lineage Report: {self.project_id}", ""]
        lines.append(f"**Generated:** {datetime.now().strftime('%Y-%m-%d %H:%M')}")
        lines.append(f"**Sources:** {len(self.sources)}")
        lines.append(f"**Entities:** {len(self.entities)}")
        lines.append(f"**Transformations:** {len(self.transformations)}")
        lines.append("")

        # Sources
        lines.append("## Data Sources")
        for source in self.sources.values():
            lines.append(f"- **{source.name}** ({source.system})")
            lines.append(f"  - Location: {source.location}")
            lines.append(f"  - Owner: {source.owner}")
        lines.append("")

        # Validation
        issues = self.validate_lineage()
        if issues:
            lines.append("## Lineage Issues")
            for issue in issues:
                lines.append(f"- ⚠️ {issue}")
            lines.append("")

        # Transformation summary
        lines.append("## Transformation Summary")
        type_counts = {}
        for t in self.transformations.values():
            type_counts[t.transformation_type.value] = type_counts.get(t.transformation_type.value, 0) + 1
        for t_type, count in sorted(type_counts.items()):
            lines.append(f"- {t_type}: {count}")

        return "\n".join(lines)
```

## Quick Start

```python
# Initialize tracker
tracker = ConstructionDataLineageTracker("PROJECT-001")

# Register sources
procore = tracker.register_source("Procore", "SaaS", "cloud", "PM Team")
sage = tracker.register_source("Sage 300", "Database", "on-prem", "Finance")

# Register entities
budget = tracker.register_entity("Project Budget", procore.id, "table")
costs = tracker.register_entity("Job Costs", sage.id, "table")
report = tracker.register_entity("Cost Variance Report", procore.id, "file")

# Record transformation
tracker.record_transformation(
    transformation_type=TransformationType.JOIN,
    description="Join budget and actual costs for variance calculation",
    input_entities=[budget.id, costs.id],
    output_entities=[report.id],
    logic="SELECT b.*, c.actual, (b.budget - c.actual) as variance FROM budget b JOIN costs c ON b.cost_code = c.cost_code",
    performed_by="ETL Pipeline"
)

# Trace lineage
upstream = tracker.trace_upstream(report.id)
print("Upstream lineage:", upstream)

# Generate graph
print(tracker.generate_lineage_graph(report.id))

# Export for audit
lineage_data = tracker.export_lineage()
```

## Resources

- **Data Governance**: DAMA DMBOK lineage guidelines
- **Audit Requirements**: SOX, ISO compliance

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Data month: 2026-09 · Downloads, stars and installs are aggregated monthly from public skill registries (ClawHub, SkillHub). See methodology.