Dataset opportunity
Pgme — 维护日志数据集机会
Pgme 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
66.1
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
42%
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 size (indicative estimate)
全球预测性维护市场规模在 2025 年为 92.1 亿美元，预计从 2026 年到 2035 年的复合年增长率为 26.19%（来源：Precedence Research）。
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
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
部分
Legal
公司所有 — 许可清晰
Buyer persona
工业人工智能与维护优化供应商
Pgme 持有一个宝贵的维护日志数据集，以时间序列的形式呈现，源自工业干预报告。这些精细的 `industrial_data` 非常适合开发和训练预测性维护模型，旨在预测设备故障，从而最大限度地减少运营中断和成本。
全球预测性维护市场在 2025 年的估值为92.1 亿美元，预计到 2035 年将以惊人的 26.19% 的复合年增长率增长，这凸显了对此类数据的巨大买家需求。虽然这些数据可能存在于遗留的 CMMS 或需要协商才能访问的纸质报告中，但其稀有性以及对高价值工业人工智能解决方案的直接适用性使其成为这个快速扩张市场中任何买家的重要资产。⚠ 尽职调查（有价值的数据，可协商访问）：数据可能存在于遗留的维护管理系统 (CMMS) 或纸质干预报告中；技术数据是 B2B 和工业性质的，最大限度地减少了 GDPR 的限制。· 公司：独立。
Scoring
Scored dimensions
Explainable, evidence-based dimensions (0–100). The radar shows the investment axes.
这些证据证实 Pgme 拥有专有的、稀有度高的维护日志数据集，用于专业工业设备。该数据记录了为识别设备异常而采取的预防性和纠正性措施，使其成为训练复杂的预测性维护模型的主要资产。对于工业人工智能供应商而言，这个时间序列数据集是直接的输入，可以在预计以 26.19% 的复合年增长率增长的市场中获取价值，使他们能够构建更准确的故障预测和优化解决方案。
See dimension details ↓- Dataset Specificity78
主导的‘维护日志’，工业领域，2 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 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 Volume46
2 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 Value74
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
人工智能买家需求极高，这得益于一个预计复合年增长率为 26.19% 的市场，因为各行业都在竞相采用数据驱动的维护以降低成本和停机时间。
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 Feasibility44
低难度，独立
How realistic it is to actually obtain the data, given access difficulty and the holder's corporate structure. - Evidence Strength50
2 种证据类型，2 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=清晰
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 Surplus70
盈余=中等 — 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. - Deep Qualification70
✓ 通过 — 目标是石油和天然气管道行业的制造商和服务提供商，这使得‘维护日志数据集’的存在可能作为其活动的副产品；然而，数据所有权和许可权尚不清楚，且未发现近期具体触发因素。
Evidence
Dataset evidence & lineage
What the typed evidence proves the company holds — reframed for clarity and set against the market.
Maintenance logs
这些证据直接证实 Pgme 从预防性和纠正性服务合同中生成并持有维护日志，提供了训练预测性维护算法所需的关键故障和维修数据。
Industrial data
这些证据确立了数据的特定领域，证明它与用于严苛的物流和制造环境的高价值工业门相关，这为模型训练增加了有价值的背景信息。
Marketplace
Dataset details
Detailed schema & sample available on access request.
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Coverage
Scanned sources
Deliverable
Premium dataset report
Pgme 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 size was $9.21 billion in 2025, projected to grow at a 26.19% CAGR from 2026 to 2035 (source: Precedence Research).. Investment score 66.1/100 (confidence 0.42). Recommended action: Acquire.
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