GCS Medarbejdere (Employees) Data Catalog

Employee and workplace safety data from regulatory inspections and incident reports.

Frontend Metrics Supported

| Metric Key | Danish Name | Description | |------------|-------------|-------------| | worker_safety_violations | Arbejdsmiljøovertrædelser | Workplace safety violations | | foreign_workers | Udenlandske arbejdere | Foreign worker registrations | | work_accidents | Arbejdsulykker | Workplace accident count | | inspection_frequency | Tilsynsfrekvens | Inspection frequency rate | | compliance_rate | Overholdelsesrate | Overall compliance rate |

Available Datasets

Gold Layer

Arbejdstilsynet Inspections (536 rows)

Path: gs://$GCS_BUCKET/gold/arbejdstilsynet_inspections/*/data.parquet

| Column | Type | Description | Example | |--------|------|-------------|---------| | date | date | Inspection date | 2024-05-15 | | case_count | int | Number of cases | 3 | | decision | string | Inspection decision | Påbud | | work_env_issue | string | Work environment issue | Ergonomi | | cvr_number | string | Company CVR | 31373077 | | company_name | string | Company name | Landbrugsbedrift A/S | | industry | string | Industry classification | Landbrug | | severity_score | float | Severity (0-10) | 7.5 | | company_compliance_rate | float | Historical compliance (0-1) | 0.85 | | is_repeat_offender | bool | Previous violations | false | | inspector_id | string | Inspector identifier | AT-123 | | follow_up_date | date | Follow-up scheduled | 2024-08-15 | | fine_amount_dkk | float | Fine if applicable | 25000.0 | | corrective_deadline | date | Deadline for correction | 2024-06-30 |

Schema (introspected):

date: date32
case_count: int64
decision: string
work_env_issue: string
cvr_number: string
company_name: string
industry: string
severity_score: double
company_compliance_rate: double
is_repeat_offender: bool
inspector_id: string
follow_up_date: date32
fine_amount_dkk: double
corrective_deadline: date32
[29 columns total]

Silver Layer

Work Permits

Path: gs://$GCS_BUCKET/silver/work permits/*/data.parquet

| Column | Type | Description | |--------|------|-------------| | cvr_number | string | Company CVR | | permit_type | string | Type of permit | | nationality | string | Worker nationality | | issue_date | date | Permit issue date | | expiry_date | date | Permit expiry date | | worker_count | int | Number of workers |

Worker Safety Reports

Path: gs://$GCS_BUCKET/silver/worker safety/*/data.parquet

| Column | Type | Description | |--------|------|-------------| | cvr_number | string | Company CVR | | report_date | date | Report date | | incident_type | string | Type of incident | | injury_severity | string | Severity level | | days_lost | int | Workdays lost | | body_part_affected | string | Injured body part | | activity_during | string | Activity at time |

Stable Fires (Incidents)

Path: gs://$GCS_BUCKET/silver/stable fires/*/data.parquet

| Column | Type | Description | |--------|------|-------------| | incident_date | date | Date of fire | | location | binary | Location (WKB) | | farm_type | string | Type of farm | | animals_affected | int | Animals impacted | | cause | string | Fire cause | | damage_estimate_dkk | float | Estimated damage |

Transport Accidents

Path: gs://$GCS_BUCKET/silver/transportation accidents/*/data.parquet

| Column | Type | Description | |--------|------|-------------| | incident_date | date | Accident date | | location | binary | Location (WKB) | | vehicle_type | string | Type of vehicle | | cargo_type | string | Cargo description | | injuries | int | Number injured | | fatalities | int | Number of fatalities |

Bronze Layer

DMA Permits

Path: gs://$GCS_BUCKET/bronze/dma/*/data.parquet

| Column | Type | Description | |--------|------|-------------| | cvr_number | string | Company CVR | | permit_number | string | Permit ID | | permit_type | string | Permit category | | valid_from | date | Start date | | valid_until | date | End date | | conditions | string | Permit conditions |

Common Queries

Get Inspection History for CVR

import pyarrow.parquet as pq
from google.cloud import storage
import io

client = storage.Client()
bucket = client.bucket('$GCS_BUCKET')

# Read arbejdstilsynet inspections
blob = bucket.blob('gold/arbejdstilsynet_inspections/2025-01-10/data.parquet')
buffer = io.BytesIO()
blob.download_to_file(buffer)
buffer.seek(0)
df = pq.read_table(buffer).to_pandas()

# Filter by CVR
cvr = '31373077'
company_inspections = df[df['cvr_number'] == cvr]

print(f"Total inspections: {len(company_inspections)}")
print(f"Total cases: {company_inspections['case_count'].sum()}")
print(f"Average severity: {company_inspections['severity_score'].mean():.2f}")
print(f"Compliance rate: {company_inspections['company_compliance_rate'].iloc[-1]:.2%}")

Calculate Industry Compliance Rates

# Aggregate by industry
industry_stats = df.groupby('industry').agg({
    'cvr_number': 'nunique',
    'case_count': 'sum',
    'severity_score': 'mean',
    'company_compliance_rate': 'mean',
    'is_repeat_offender': 'sum'
}).reset_index()

industry_stats.columns = ['industry', 'companies', 'total_cases',
                          'avg_severity', 'avg_compliance', 'repeat_offenders']
industry_stats = industry_stats.sort_values('avg_compliance', ascending=True)

Find Repeat Offenders

# Companies with multiple violations
repeat_offenders = df[df['is_repeat_offender'] == True]

# Group by company
offender_summary = repeat_offenders.groupby(['cvr_number', 'company_name']).agg({
    'case_count': 'sum',
    'severity_score': 'mean',
    'fine_amount_dkk': 'sum'
}).reset_index()
offender_summary = offender_summary.sort_values('case_count', ascending=False)

Severity Analysis by Issue Type

# Analyze by work environment issue category
issue_analysis = df.groupby('work_env_issue').agg({
    'case_count': 'sum',
    'severity_score': 'mean',
    'fine_amount_dkk': 'sum'
}).reset_index()
issue_analysis = issue_analysis.sort_values('severity_score', ascending=False)

Monthly Inspection Trends

import pandas as pd

# Convert to datetime
df['inspection_month'] = pd.to_datetime(df['date']).dt.to_period('M')

monthly_stats = df.groupby('inspection_month').agg({
    'cvr_number': 'nunique',
    'case_count': 'sum',
    'severity_score': 'mean'
}).reset_index()
monthly_stats.columns = ['month', 'companies_inspected', 'total_cases', 'avg_severity']

Calculate Fines by Municipality

# Join with CVR address data for geographic analysis
# (requires joining with okonomi/cvr_enrichment data)
from gcs_data_catalog.okonomi import read_cvr_data

cvr_geo = read_cvr_data()
inspections_with_geo = df.merge(
    cvr_geo[['cvr_number', 'municipality']],
    on='cvr_number',
    how='left'
)

municipal_fines = inspections_with_geo.groupby('municipality').agg({
    'fine_amount_dkk': 'sum',
    'case_count': 'sum'
}).reset_index()

Foreign Worker Analysis

# Read work permits
blob = bucket.blob('silver/work permits/2025-01-10/data.parquet')
buffer = io.BytesIO()
blob.download_to_file(buffer)
buffer.seek(0)
permits = pq.read_table(buffer).to_pandas()

# Count by nationality
nationality_counts = permits.groupby('nationality').agg({
    'worker_count': 'sum'
}).reset_index()
nationality_counts = nationality_counts.sort_values('worker_count', ascending=False)

# Companies with most foreign workers
company_workers = permits.groupby('cvr_number').agg({
    'worker_count': 'sum'
}).reset_index()
company_workers = company_workers.sort_values('worker_count', ascending=False)

Decision Types

| Decision (Danish) | English | Severity | |-------------------|---------|----------| | Påbud | Order/Requirement | Medium | | Forbud | Prohibition | High | | Vejledning | Guidance | Low | | Afgørelse | Decision | Varies | | Strakspåbud | Immediate Order | High | | Rådgivningspåbud | Advisory Order | Medium |

Work Environment Issues

Common categories in work_env_issue:

Ergonomi - Ergonomic issues (lifting, posture)
Kemisk arbejdsmiljø - Chemical hazards
Psykisk arbejdsmiljø - Psychological work environment
Ulykker - Accident prevention
Støj - Noise exposure
Maskinsikkerhed - Machine safety
Bygge og anlæg - Construction safety

Join Keys

| This Dataset | Join Column | Target Dataset | Target Column | |--------------|-------------|----------------|---------------| | arbejdstilsynet | cvr_number | subsidies | cvr_number | | arbejdstilsynet | cvr_number | field_production | cvr_number | | arbejdstilsynet | cvr_number | pesticide_disaggregation | cvr_number | | work_permits | cvr_number | arbejdstilsynet | cvr_number | | worker_safety | cvr_number | arbejdstilsynet | cvr_number |

Data Quality Notes

Arbejdstilsynet Inspections

Update frequency: After inspection completion
Coverage: All inspected agricultural businesses
Source: Danish Working Environment Authority
Caveat: Not all farms inspected - risk-based selection

Work Permits

Update frequency: Monthly
Coverage: All registered foreign worker permits
Source: SIRI (Danish Immigration Service)

Incidents (Fires, Accidents)

Update frequency: After incident reporting
Coverage: Reported incidents only
Caveat: Underreporting possible

Compliance Score Interpretation

The company_compliance_rate field (0-1 scale):

0.90-1.00: Excellent compliance history
0.75-0.89: Good compliance, minor issues
0.50-0.74: Moderate compliance, attention needed
0.00-0.49: Poor compliance, likely repeat offender

Related Skills

okonomi/ - Company financial data for CVR context
landbrugsareal/ - Land area and farm size context
miljo/ - Environmental compliance (related violations)
husdyr/ - Livestock operations (animal handling safety)

GCS Paths Reference

# List arbejdstilsynet inspection data
gsutil ls gs://$GCS_BUCKET/gold/arbejdstilsynet_inspections/

# List work permit data
gsutil ls gs://$GCS_BUCKET/silver/work\ permits/

# List worker safety data
gsutil ls gs://$GCS_BUCKET/silver/worker\ safety/

# List incident data
gsutil ls gs://$GCS_BUCKET/silver/stable\ fires/
gsutil ls gs://$GCS_BUCKET/silver/transportation\ accidents/

# List DMA permit data
gsutil ls gs://$GCS_BUCKET/bronze/dma/

Agricultural-Specific Safety Concerns

Common issues in agricultural workplace inspections:

Machine safety - Tractors, harvesters, feed machinery
Chemical exposure - Pesticides, fertilizers, cleaning agents
Animal handling - Large animal injuries, zoonotic diseases
Ergonomics - Repetitive lifting, awkward postures
Confined spaces - Silos, manure pits, grain bins
Environmental - Heat stress, cold exposure, UV radiation

gcs-medarbejdere-data

GCS Medarbejdere (Employees) Data Catalog

Frontend Metrics Supported

Available Datasets

Gold Layer

Arbejdstilsynet Inspections (536 rows)

Silver Layer

Work Permits

Worker Safety Reports

Stable Fires (Incidents)

Transport Accidents

Bronze Layer

DMA Permits

Common Queries

Get Inspection History for CVR

Calculate Industry Compliance Rates

Find Repeat Offenders

Severity Analysis by Issue Type

Monthly Inspection Trends

Calculate Fines by Municipality

Foreign Worker Analysis

Decision Types

Work Environment Issues

Join Keys

Data Quality Notes

Arbejdstilsynet Inspections

Work Permits

Incidents (Fires, Accidents)

Compliance Score Interpretation

Related Skills

GCS Paths Reference

Agricultural-Specific Safety Concerns