electricsheepeurope/europe-ilo-sdg-n881-sex-mig-rt-sdg-indicator-8-8-1-non-fatal-occupational-injurie

SDG indicator 8.8.1 - Non-fatal occupational injuries per 100'000 workers by sex and migra | Europe (ILOSTAT)

🇪🇺 1,740 observations · 35 Europe countries · 2000–2024 · Repackaged by Electric Sheep Europe

TL;DR

This dataset contains 1,740 observations of Occupational injuries data across 35 Europe countries, spanning 2000–2024, covering 1 distinct indicators.

About the source

ILOSTAT is the ILO's central statistics database, the leading global source for labour statistics. It compiles indicators across employment, unemployment, wages, working time, child labour, informal economy, social protection, occupational injuries, and SDG decent work targets — drawing on national labour force surveys, household income surveys, establishment surveys, and administrative records. Coverage spans 200+ economies, with the ILO's Department of Statistics responsible for harmonisation.

• Source: ILOSTAT
• Publisher: International Labour Organization (ILO)
• License: cc-by-4.0
• Topic: Occupational injuries

Methodology

Data pulled directly from the ILOSTAT REST API at https://rplumber.ilo.org/data/indicator?id=SDG_N881_SEX_MIG_RT and filtered to Europe ISO3 country codes. ILOSTAT harmonises raw survey microdata using ICLS (International Conference of Labour Statisticians) definitions; sources are flagged in the source.label column for traceability.

Geographic coverage

35 Europe countries · top rows shown below, sorted by row count:

Country	Rows	First year	Last year
ESP	120	2000	2023
MLT	105	2000	2024
HUN	95	2000	2024
FIN	91	2000	2023
LUX	85	2000	2024
BLR	75	2000	2024
RUS	67	2000	2022
BGR	66	2000	2023
SWE	65	2000	2024
UKR	64	2000	2021
LTU	61	2000	2024
SVK	59	2000	2024
EST	58	2000	2023
CZE	56	2000	2023
AUT	55	2004	2024
...	20 more countries

Indicators (sample)

• SDG_N881_SEX_MIG_RT — SDG indicator 8.8.1 - Non-fatal occupational injuries per 100'000 workers by sex and migrant status

Schema

Column	Type	Description	Example
ref_area	string	ISO 3166-1 alpha-3 country code	AUT
ref_area.label	string	Country name in English	Austria
source	string	ILOSTAT source code (e.g. labour force survey)	FA:257
source.label	string	Source name in English	ADM-IR - Database Records from all in…
indicator	string	ILOSTAT indicator code	SDG_N881_SEX_MIG_RT
indicator.label	string	Indicator name in English	SDG indicator 8.8.1 - Non-fatal occup…
sex	string	Disaggregation by sex (SEX_T = total, SEX_M = male, SEX_F = female)	SEX_T
sex.label	string	—	Total
classif1	string	First classification variable (age, education, status, etc.)	MIG_STATUS_TOTAL
classif1.label	string	—	Migrant status: Total
time	int64	Observation year	2024
obs_value	float64	Observed indicator value (unit varies — see indicator definition)	2322.598
obs_status	string	Observation status flag (e.g. provisional, unreliable)	U
obs_status.label	string	—	Unreliable
note_indicator	string	—	T13:149_T14:153
note_indicator.label	string	—	Coverage of occupational injuries: Re…
note_source	string	—	S3:24_S9:259
note_source.label	string	—	Data reference period: End of the yea…

Disaggregation dimensions

The following columns provide disaggregation dimensions:

• sex (3 unique values): SEX_T, SEX_M, SEX_F

Data quality & caveats

• Data is annual frequency. Some indicators also publish monthly or quarterly series — those are not included here.
• When an indicator has multiple sources for the same country×year, the ILO-selected 'best source' is used.
• Disaggregation columns (sex, classif1, classif2) are non-null only when the indicator publishes that breakdown.

Usage

from datasets import load_dataset

ds = load_dataset("electricsheepeurope/europe-ilo-sdg-n881-sex-mig-rt-sdg-indicator-8-8-1-non-fatal-occupational-injurie")
df = ds["train"].to_pandas()
print(df.head())

Filter to one country

germany = df[df["ref_area"] == "DEU"]

Time-series for a single indicator

sample = (df[df["indicator"] == "SDG_N881_SEX_MIG_RT"]
          .sort_values("time"))
sample.plot(x="time", y="obs_value", title="SDG_N881_SEX_MIG_RT")

Pivot to country × year matrix

matrix = (df[df["indicator"] == "SDG_N881_SEX_MIG_RT"]
          .pivot_table(index="time", columns="ref_area", values="obs_value"))
print(matrix.tail())

Citation

@misc{europe_ilo_sdg_n881_sex_mig_rt_sdg_indicator_8_8_1_non_fatal_occupational_injurie_2024,
  title        = {SDG indicator 8.8.1 - Non-fatal occupational injuries per 100'000 workers by sex and migra | Europe (ILOSTAT)},
  author       = {International Labour Organization (ILO)},
  year         = {2024},
  url          = {https://www.ilo.org/shinyapps/bulkexplorer/?id=SDG_N881_SEX_MIG_RT},
  publisher    = {HuggingFace Datasets, repackaged by Electric Sheep Europe},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepeurope/europe-ilo-sdg-n881-sex-mig-rt-sdg-indicator-8-8-1-non-fatal-occupational-injurie}}
}

License

Released under cc-by-4.0.

Original data © International Labour Organization (ILO). When using this dataset, please cite both the original source above and the Electric Sheep Europe repackaging.

About Electric Sheep

Electric Sheep Europe is part of the Electric Sheep mission: a unified, ML-ready data layer for Europe on HuggingFace. We pull data from authoritative open sources, normalize the schemas, package as Parquet, and publish with consistent dataset cards so researchers and developers can use load_dataset() to start working in seconds.

Browse the full collection: huggingface.co/electricsheepeurope

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Provenance: ingested 2026-05-25 via the Electric Sheep pipeline. Source URL: https://www.ilo.org/shinyapps/bulkexplorer/?id=SDG_N881_SEX_MIG_RT