Kossisoroyce commited on
Commit
a7780d4
·
verified ·
1 Parent(s): 6596836

Upload README.md with huggingface_hub

Browse files
Files changed (1) hide show
  1. README.md +191 -0
README.md ADDED
@@ -0,0 +1,191 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ license: cc-by-4.0
3
+ task_categories:
4
+ - tabular-classification
5
+ - tabular-regression
6
+ - time-series-forecasting
7
+ language:
8
+ - en
9
+ tags:
10
+ - mining
11
+ - tailings-dam
12
+ - dam-safety
13
+ - risk-assessment
14
+ - environmental
15
+ - geotechnical
16
+ - africa
17
+ - synthetic-data
18
+ pretty_name: African Tailings Dam Risk Dataset
19
+ size_categories:
20
+ - 1K<n<10K
21
+ ---
22
+
23
+ # African Tailings Dam Risk Dataset
24
+
25
+ ## Dataset Description
26
+
27
+ ### Overview
28
+
29
+ This dataset provides synthetic monitoring records and risk assessments for tailings storage facilities (TSFs) across African mining operations. Tailings dams represent one of the most significant environmental and safety risks in mining, with catastrophic failures causing loss of life and long-term environmental damage.
30
+
31
+ The dataset captures dam characteristics, geotechnical monitoring data, environmental conditions, and risk indicators aligned with the Global Industry Standard on Tailings Management (GISTM).
32
+
33
+ ### Dataset Statistics
34
+
35
+ | Attribute | Value |
36
+ |-----------|-------|
37
+ | Records | 5,000 |
38
+ | Variables | 31 |
39
+ | Temporal Coverage | 2020-2024 |
40
+ | Geographic Scope | 8 African countries |
41
+ | Facility Count | ~500 unique TSFs |
42
+ | Format | CSV, Parquet |
43
+
44
+ ## Data Schema
45
+
46
+ ### Variable Dictionary
47
+
48
+ | Variable | Type | Description | Value Range/Categories |
49
+ |----------|------|-------------|----------------------|
50
+ | `record_id` | string | Unique monitoring record ID | TSF-XXXXXXXX |
51
+ | `facility_id` | string | Tailings facility identifier | FAC-XXXX |
52
+ | `country` | categorical | Country of facility | south_africa, ghana, drc, zambia, zimbabwe, tanzania, mali, mauritania |
53
+ | `commodity` | categorical | Primary commodity | gold, copper, platinum, iron_ore, coal, diamond, uranium, other |
54
+ | `operational_status` | categorical | Facility status | active, inactive, closed, under_construction |
55
+ | `dam_type` | categorical | Dam construction type | earthfill, rockfill, concrete, composite |
56
+ | `construction_method` | categorical | Raise method (critical for stability) | upstream, downstream, centerline, dry_stack |
57
+ | `max_height_m` | float | Maximum design height | 10-250 meters |
58
+ | `current_height_m` | float | Current embankment height | meters |
59
+ | `storage_capacity_mm3` | float | Total storage capacity | million m³ |
60
+ | `current_volume_mm3` | float | Current stored volume | million m³ |
61
+ | `catchment_area_km2` | float | Contributing catchment area | km² |
62
+ | `year_constructed` | integer | Initial construction year | 1960-2023 |
63
+ | `design_life_years` | integer | Designed operational life | 20-100 years |
64
+ | `last_raise_year` | integer | Year of most recent raise | Year |
65
+ | `consequence_classification` | categorical | Failure consequence class | extreme, very_high, high, significant, low |
66
+ | `monitoring_date` | datetime | Date of monitoring record | 2020-01-01 to 2024-12-31 |
67
+ | `freeboard_m` | float | Water surface to crest distance | 0.5-10 meters |
68
+ | `piezometer_level_m` | float | Phreatic surface height | meters |
69
+ | `seepage_rate_lpm` | float | Measured seepage rate | liters per minute |
70
+ | `settlement_mm` | float | Cumulative crest settlement | millimeters |
71
+ | `inclinometer_displacement_mm` | float | Lateral displacement | millimeters |
72
+ | `rainfall_24h_mm` | float | 24-hour precipitation | millimeters |
73
+ | `earthquake_pga` | float | Peak ground acceleration | g (gravitational) |
74
+ | `water_balance_status` | categorical | Water management status | surplus, balanced, deficit |
75
+ | `factor_of_safety` | float | Calculated stability FoS | 0.8-2.5 |
76
+ | `risk_score` | float | Composite risk score | 0-100 |
77
+ | `risk_category` | categorical | Risk classification | low, medium, high, critical |
78
+ | `last_inspection_days_ago` | integer | Days since last inspection | 1-730 days |
79
+ | `governance_score` | integer | Management system score | 20-100 |
80
+ | `has_eap` | boolean | Emergency Action Plan exists | True/False |
81
+
82
+ ## Methodology
83
+
84
+ ### Tailings Dam Risk Framework
85
+
86
+ The dataset models risk factors identified in major tailings dam failures and GISTM requirements:
87
+
88
+ **Construction Method Risk Ranking**:
89
+ | Method | Risk Level | Prevalence | Notes |
90
+ |--------|------------|------------|-------|
91
+ | Upstream | Highest | 35% | Sequential raises on tailings beach; liquefaction vulnerable |
92
+ | Centerline | Medium | 25% | Raises vertically; moderate stability |
93
+ | Downstream | Lower | 30% | Raises downstream; best stability |
94
+ | Dry Stack | Lowest | 10% | Filtered tailings; no impoundment |
95
+
96
+ **Key Risk Indicators Modeled**:
97
+
98
+ 1. **Factor of Safety (FoS)**: Ratio of resisting to driving forces
99
+ - Critical threshold: FoS < 1.3
100
+ - Upstream dams: Mean FoS reduced by 0.2
101
+ - Dry stack: Mean FoS increased by 0.3
102
+
103
+ 2. **Freeboard**: Buffer against overtopping
104
+ - Critical threshold: < 1.5 meters
105
+
106
+ 3. **Seepage**: Indicator of internal erosion
107
+ - Warning threshold: > 100 LPM
108
+
109
+ 4. **Displacement**: Slope movement indicator
110
+ - Warning threshold: > 30 mm cumulative
111
+
112
+ ### Historical Context
113
+
114
+ Major African tailings incidents informing risk modeling:
115
+ - Merriespruit (South Africa, 1994): 17 fatalities, upstream dam
116
+ - Samarco analogs: Liquefaction failure modes
117
+ - Regional seismicity considerations
118
+
119
+ ### Sensor Correlation Structure
120
+
121
+ Monitoring parameters are correlated to reflect realistic failure precursors:
122
+ - Rainfall → Piezometer rise → Seepage increase → Settlement/displacement
123
+ - Seismic events → Pore pressure spike → Stability reduction
124
+
125
+ ## Limitations
126
+
127
+ 1. **Simplified Geotechnics**: Complex soil mechanics reduced to statistical distributions
128
+ 2. **Sensor Density**: Real TSFs have hundreds of instruments; dataset simplified
129
+ 3. **Failure Events**: Actual failures not explicitly modeled (rare events)
130
+ 4. **Site Specificity**: Generic African context; site investigations required
131
+ 5. **Climate Projections**: Historical patterns; climate change effects not modeled
132
+ 6. **Governance Proxies**: Management quality simplified to single score
133
+
134
+ ## Ethical Considerations
135
+
136
+ - **Public Safety**: Tailings failures can kill hundreds and devastate communities
137
+ - **Environmental Justice**: Downstream communities often marginalized
138
+ - **Corporate Accountability**: Dataset should not be used to obscure real risks
139
+ - **Regulatory Implications**: Not a substitute for proper engineering assessment
140
+ - **Transparency**: Supports calls for public disclosure of TSF risks
141
+
142
+ ## Intended Uses
143
+
144
+ ### Appropriate Uses
145
+
146
+ - Development of early warning algorithms
147
+ - Research on risk indicator correlations
148
+ - Educational demonstrations of dam safety monitoring
149
+ - Benchmarking ML approaches for anomaly detection
150
+ - Policy research on tailings governance
151
+
152
+ ### Inappropriate Uses
153
+
154
+ - Actual dam safety assessments
155
+ - Regulatory compliance certification
156
+ - Insurance or liability determinations
157
+ - Investment decisions on specific facilities
158
+ - Replacing qualified geotechnical engineering
159
+
160
+ ## Citation
161
+
162
+ ```bibtex
163
+ @dataset{electric_sheep_africa_tailings_dam_2024,
164
+ title = {African Tailings Dam Risk Dataset},
165
+ author = {Electric Sheep Africa},
166
+ year = {2024},
167
+ publisher = {Hugging Face},
168
+ url = {https://huggingface.co/datasets/electricsheepafrica/african-mining-tailings-dam},
169
+ note = {Synthetic dataset for tailings dam risk research aligned with GISTM}
170
+ }
171
+ ```
172
+
173
+ ## References
174
+
175
+ 1. ICOLD (International Commission on Large Dams). (2001). *Tailings Dams: Risk of Dangerous Occurrences*. Bulletin 121.
176
+
177
+ 2. Global Tailings Review. (2020). *Global Industry Standard on Tailings Management (GISTM)*. ICMM, UNEP, PRI.
178
+
179
+ 3. Santamarina, J.C., Torres-Cruz, L.A., & Bachus, R.C. (2019). Why coal ash and tailings dam disasters occur. *Science*, 364(6440), 526-528.
180
+
181
+ 4. Bowker, L.N., & Chambers, D.M. (2015). The risk, public liability, & economics of tailings storage facility failures. *Earthwork Act*.
182
+
183
+ 5. Franks, D.M., et al. (2021). Tailings facility disclosures reveal stability risks. *Scientific Reports*, 11, 5353.
184
+
185
+ ## License
186
+
187
+ This dataset is released under the [Creative Commons Attribution 4.0 International License](https://creativecommons.org/licenses/by/4.0/) (CC-BY-4.0).
188
+
189
+ ## Contact
190
+
191
+ For questions or feedback, please open an issue on the dataset repository or contact Electric Sheep Africa.