Dataset opportunity
Geotechnicalengineering — Industrial Operations Dataset Opportunity
由岩土工程持有的海量工业运营数据集，可用于工业监控和预测。
Score
70.8
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
51%
Action
收购
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
全球预测性维护市场 = 2025年为149.3亿美元，复合年增长率为32.32%（2026-2035年）
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.
Profile
Dataset profile
Type
工业运营数据集
Modality
时间序列
Sector
工业
Volume
大
Freshness
定期
Rarity
高（专有）
Accessibility
部分
Legal
公司所有 — 可授权
Buyer persona
工业人工智能集成商
岩土工程拥有一个有价值的工业运营数据集，其特点是时间序列模式，包含大量的地理数据和其他工业数据。这些丰富的时间戳信息对于高级工业监控应用至关重要，能够持续跟踪流程、设备行为和环境条件，从而获得可操作的见解。
此类数据的商业价值巨大，推动着一个快速扩张的市场。全球预测性维护市场是该数据的一个关键买家用例，其市场价值在2025年为149.3亿美元，预计到2035年将达到2457.3亿美元，复合年增长率为32.32%。此外，与地理数据高度相关的特定岩土工程仪器和监测市场，在2025年的价值为56.9亿美元，预计到2034年将增长到142.7亿美元，复合年增长率为10.57%。尽管由于现有客户项目报告需要澄清所有权和许可而存在访问复杂性，以及潜在的客户特定数据协议，但高市场规模和复合年增长率凸显了该数据对于寻求优化运营和防止代价高昂的停机的AI买家而言的内在价值。⚠ 尽职调查（有价值的数据，可协商的访问权限）：数据通常作为项目报告的一部分交付给客户，需要澄清所有权和许可才能更广泛地使用；潜在的客户特定数据协议可能会使更广泛的数据许可复杂化。· 公司：独立。
Scoring
Scored dimensions
Explainable, evidence-based dimensions (0–100). The radar shows the investment axes.
该持有者在岩土工程领域拥有深厚、长期的专业知识，这得益于其超过60年的行业经验和一个专有的工业运营数据集。他们在37,000个项目中积累的良好业绩记录，提供了一个独特的高容量时间序列数据源，这对于高级工业监控至关重要。这一稀有而有价值的资产直接满足了快速扩张的预测性维护市场中工业AI集成商的迫切需求，提供了显著的竞争优势。该数据集的专有性质和真实世界的来源使其对AI开发极具吸引力。
See dimension details ↓- Dataset Specificity78
主导的“工业数据”，行业为工业，2个具体类型
How sharply the data targets a specific, hard-to-substitute domain or task. Niche, well-defined data scores higher than generic. - Dataset Rarity70
专有领域数据
How scarce and proprietary the data is. Unique domain data scores high; openly available data lowers it. - Dataset Volume74
4个证据命中，明确提及数据量
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 Value74
适用于工业监控
How useful the data is for the target AI use-case — its fit for model training or fine-tuning. - Buyer Demand92
工业AI市场，该市场高度依赖工业运营数据集进行监控和预测性维护等应用，预计在2025年至2035年间的复合年增长率为46.02%。
How strongly AI builders and companies are likely to want this data, based on market signals. - Legal Accessibility50
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 Feasibility30
中等难度，独立
How realistic it is to actually obtain the data, given access difficulty and the holder's corporate structure. - Evidence Strength65
3种证据类型，4次命中
How solid the proof is that the company holds this data — diversity of evidence types and number of hits. - Right to License92
所有权=已拥有，许可=干净
Whether the company can legally license the data out — based on ownership and licensing complexity. - Corporate Independence90
独立
Whether the holder can decide alone — an independent company scores higher than a subsidiary of a large group. - Data Orientation22
0个数据需求信号（0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 — 专有数据超出已货币化的部分
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 Audit100
✓ 良好目标 — Geotechnical Engineering Ltd 是一家总部位于英国的中小型企业，专注于地面调查和地理空间测量，在其运营服务中产生了大量专有数据，并且似乎不以销售这些数据或衍生情报作为核心产品。
Evidence
Dataset evidence & lineage
What the typed evidence proves the company holds — reframed for clarity and set against the market.
Industrial data
该证据证实了持有者的核心资产：一个专有的时间序列数据集，源自超过60年的工业运营和全面的土壤岩石测试，对于预测性维护模型具有极高的价值。
Geospatial data
这突出了持有者广泛的地理空间测量能力，提供了关于建筑资产和环境条件的表格数据，这对于为工业基础设施监控提供背景信息至关重要。
Data-volume signal
这表明来自超过37,000个项目的大量且经过验证的数据量，证实了持有者广泛的实际经验以及他们收集信息的多模态性质，这对于训练强大的AI模型至关重要。
Marketplace
Dataset details
Geographic coverage
Global
Time range
60+ years historical data, ongoing updates
Update frequency
Periodic
Delivery
API, S3 bucket
Formats
CSV, JSON
License
One-time license for internal use and model training, with 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, large volume of proprietary geotechnical and industrial time-series data, and strong demand from the rapidly growing predictive maintenance market. The extensive project history and deep expertise of the holder further enhance its unique market position.
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
Geotechnicalengineering Industrial Operations — a Large industrial operations dataset (Time Series modality) in the industrial domain. Primary AI use-case: Industrial Monitoring. Market signal: Global Predictive Maintenance Market = USD 14.93 Billion in 2025, CAGR 32.32% (2026-2035). Investment score 70.8/100 (confidence 0.51). Recommended action: Acquire.
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