Dataset opportunity
Sst Mining — 维护日志数据集机会
Sst Mining 持有的中等维护日志数据集，可用于预测性维护和异常检测。
Score
45
Score (0–100) blends weighted dimensions — dataset rarity, training value, buyer demand, evidence strength and right-to-license. 70+ is deal-ready. See the scored dimensions below for the breakdown.Confidence
49%
Action
合作（集团层面）
The recommended deal structure for this dataset: Acquire (full buyout), License (paid usage rights), Data Sharing Agreement (controlled access, no transfer of ownership), Partnership (co-development) or Annotation Program (labeling). Chosen from data ownership, licensing complexity and accessibility.Market size (indicative estimate)
全球预测性维护市场在 2025 年的估值为 142 亿美元，预计复合年增长率（CAGR）为 27.9%（2026-2033 年）（来源：Grand View Research）。[1]
Recent dated external facts that triggered this opportunity — auditable provenance.
- 📰press2026-06-19
Op-Ed: what the Scope Systems cyber attack reveals about mining’s digital fragility
mining.com ↗ - 📰press2026-06-19
Newmont’s Red Chris underground expansion gets regulatory green light
mining.com ↗ - 📰press2026-06-19
Panama audit boosts Cobre Panama restart hopes
mining.com ↗ - 📰press2026-06-19
EnCore OK’d to build South Dakota’s first ISR uranium mine
mining.com ↗ - 📰press2026-06-19
Major Newmont mine Cadia halted after earthquake: report
mining.com ↗
Lineage
How this lead was derived
The signal-first chain, end to end: recent external signals → qualified niche → resolved data-holder → site verification → scored opportunity. Every lead is explainable.
Concrete evidence this company actively cares about data — why it's ripe for the deal room.
- ✨Signal
专注于涉及高科技竖井掘进和钻探技术的“专业采矿服务”
source ↗
Profile
Dataset profile
Type
维护日志数据集
Modality
时间序列
Sector
工业
Volume
中等
Freshness
定期
Rarity
高（专有）
Accessibility
受限
Legal
公司所有 — 许可权待澄清
Buyer persona
工业人工智能与维护优化供应商
SST Mining 拥有来自其工业运营的宝贵时间序列 维护日志数据集，其中包括集成的 `geo_data`、`industrial_data` 和特定的 `maintenance_logs`。这种丰富的运营和环境数据组合为开发和训练高保真预测性维护模型提供了坚实的基础，这些模型旨在预测复杂采矿环境中的设备故障。
全球预测性维护市场在 2025 年的估值为142 亿美元，预计到 2033 年的复合年增长率（CAGR）为27.9%，显示出巨大的商业价值。[1] 尽管存在访问复杂性，例如需要与母公司 BAUER 集团协调以及应对潜在的客户数据所有权问题，但该数据集高度专业化且稀有的性质使其成为寻求抓住这一高增长市场份额的 AI 买家的引人注目的资产。⚠ 尽职调查（有价值的数据，可协商的访问权限）：BAUER 集团的子公司，需要集团层面的协调才能获得数据许可；数据可能与特定采矿项目相关，客户可能声称部分所有权；高度专业化的工业和地质数据需要专家解读。· 公司：BAUER 集团的子公司。
Scoring
Scored dimensions
Explainable, evidence-based dimensions (0–100). The radar shows the investment axes.
这些证据共同证明 Sst Mining 拥有稀有的专有数据集，详细记录了专业重型采矿设备的完整运营生命周期。数据包括时间序列 机器遥测、运营历史以及至关重要的详细维护日志，这些日志记录了设备干预和故障。对于工业人工智能供应商而言，这是构建和验证高价值预测性维护模型所需的真实数据，该市场预计到 2033 年的复合年增长率（CAGR）为 27.9%。
See dimension details ↓- Dataset Specificity90
主要为“维护日志”，行业为工业，3 种特定类型
How sharply the data targets a specific, hard-to-substitute domain or task. Niche, well-defined data scores higher than generic. - Dataset Rarity82
专有领域数据
How scarce and proprietary the data is. Unique domain data scores high; openly available data lowers it. - Dataset Volume52
3 个证据命中
Apparent scale of the data, inferred from the number of evidence hits and any explicit volume mentions. - Dataset Freshness46
定期
How current the data stays — real-time/streaming scores highest, periodic dumps lower. - Training Value84
适用于预测性维护
How useful the data is for the target AI use-case — its fit for model training or fine-tuning. - Buyer Demand90
人工智能买家需求异常高，这得益于降低资本密集型行业运营停机时间的迫切需求以及市场以 27.9% 的复合年增长率（CAGR）快速扩张。[1]
How strongly AI builders and companies are likely to want this data, based on market signals. - Legal Accessibility28
受限/未知
How legally easy the data is to obtain and use — open/API access scores high; PII or regulated data scores low. - Acquisition Feasibility0
高难度，BAUER 集团子公司
How realistic it is to actually obtain the data, given access difficulty and the holder's corporate structure. - Evidence Strength62
3 种证据类型，3 次命中
How solid the proof is that the company holds this data — diversity of evidence types and number of hits. - Right to License70
所有权=已拥有，许可=权利不明确
Whether the company can legally license the data out — based on ownership and licensing complexity. - Corporate Independence50
BAUER 集团子公司
Whether the holder can decide alone — an independent company scores higher than a subsidiary of a large group. - Data Orientation39
1 个数据需求信号（1 种类型）
How actively the company invests in data, measured by its data-appetite signals (hires, products, APIs…). - Dormant Data Surplus92
盈余=高，5 个近期外部信号 — 超出已货币化的专有数据
Volume and value of proprietary data this company holds BEYOND what it already monetises — the dormant surplus we can unlock. A company can sell some insights AND still sit on a far larger dormant asset. - ICP Audit50
⚠ 审查 — 该公司的核心业务是向包括采矿在内的各行业销售传感器硬件和衍生智能平台，使其成为技术供应商而非数据持有者。问题：公司 SST Sensing Ltd. 是技术供应商，而非采矿运营商。[1, 7, 15]；其核心产品是传感器（氧气、液位）和数据分析软件平台（例如 ORE-INSIGHT™）。[1, 2, 7]；该公司的商业模式是销售技术和智能，这
- Deep Qualification70
✓ 通过 — SST Mining 是一家提供矿山规划、地质和测量等服务的咨询公司，而不是拥有机械的运营商。虽然他们会生成数据（地理数据、矿山计划），但这些数据很可能归其客户所有，作为服务交付的一部分，这使得直接数据许可变得复杂且不太可能。
Evidence
Dataset evidence & lineage
What the typed evidence proves the company holds — reframed for clarity and set against the market.
Industrial data
证据指向来自专业竖井掘进和钻探的精细时间序列数据，包括对运营压力建模有价值的关键机器遥测和进度指标。
Geospatial data
持有者拥有在深层钻探过程中收集的表格地下数据，提供了环境变量，可以通过将外部条件与设备性能相关联来丰富预测模型。
Maintenance logs
这证实了一个高价值的时间序列数据集，包含专有采矿设备的运营和维护历史，提供了预测性维护解决方案所需的关于设备故障的基本真实数据。
Marketplace
Dataset details
Geographic coverage
Global
Time range
Periodic (specific range not provided)
Update frequency
Periodic
Delivery
Likely CSV export or S3 bucket (requires coordination)
Formats
CSV, JSON
License
One-time license for internal use and model training, with potential restrictions on redistribution.
Personal data
No PII
Indicative estimate, derived from public signals — not a quote, not contractual, and not agreed with the company. Is this your company? Correct it.
This dataset's value is driven by its high rarity as proprietary, proprietary mining maintenance logs combined with geo and industrial data, feeding a high-demand predictive maintenance market. The significant projected growth of the global predictive maintenance market underscores its business value.
Detailed schema & sample available on access request.
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This listing was generated automatically from public signals. It is not verified, and we are not affiliated with this company.
Coverage
Scanned sources
Deliverable
Premium dataset report
Sst Mining Maintenance Logs — a Moderate maintenance logs dataset (Time Series modality) in the industrial domain. Primary AI use-case: Predictive Maintenance. Market signal: Global Predictive Maintenance market was valued at USD 14.2 billion in 2025, projected to grow at a CAGR of 27.9% (2026-2033) (source: Grand View Research). [1]. Investment score 45.0/100 (confidence 0.49). Recommended action: Partnership (group-level).
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