Dataset opportunity
Windmanager — 风力发电机维护日志数据集机会
由 Windmanager 持有的中等规模维护日志数据集，可用于预测性维护和异常检测。
Score
70
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
56%
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
全球风力涡轮机预测性维护人工智能市场在 2024 年达到 12.4 亿美元，预计将以 22.8% 的复合年增长率增长（来源：Dataintelo）。 [8]
Recent dated external facts that triggered this opportunity — auditable provenance.
- 📰press2026-06-29
EDF amorce son recentrage nucléaire avec une cession massive dans les EnR
greenunivers.com ↗ - 📰press2026-06-29
Virginia defines agrivoltaics, expanding opportunities for solar
utilitydive.com ↗ - 📰press2026-06-26
445 GW — mainly solar, storage — to come online by 2030 as demand growth surges: ICF
utilitydive.com ↗ - 📰press2026-06-26
Bohr Energie collecte 9,5 M€, va franchir 1 GW agrégé
greenunivers.com ↗ - 📰press2026-06-25
Ormat Bets on Standardization to Win the Geothermal Race
powermag.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.
- 📦Data product
windmanager 门户（外联网）提供实时监控和技术报告
source ↗
Profile
Dataset profile
Type
维护日志数据集
Modality
时间序列
Sector
工业
Volume
中等
Freshness
实时
Rarity
高（专有）
Accessibility
受限
Legal
混合所有权 — 需明确许可权
Buyer persona
工业人工智能与维护优化供应商
Windmanager 持有一个广泛的维护日志数据集，结构为时间序列。这些工业数据来自大型风力涡轮机车队中的物联网传感器，提供了组件性能、维修和运行事件的详细记录，使其成为开发高精度预测性维护模型的首要资产。
风力涡轮机预测性维护人工智能市场在 2024 年的价值为12.4 亿美元，预计将以22.8% 的复合年增长率增长。[8] 这种显著的增长凸显了此类专业数据的稀缺性和高需求。虽然访问需要处理共享数据所有权和严格的德国KRITIS（关键基础设施）安全协议，但该数据集在这个快速扩张的市场中的价值证明了谈判复杂性的合理性。⚠ 尽职调查（有价值的数据，可协商的访问权限）：数据所有权可能与第三方资产所有者（投资者/公用事业公司）共享；受德国 KRITIS（关键基础设施）安全要求约束；ISO 27001 认证意味着严格的数据治理和访问协议 · 公司：wpd 集团子公司。
Scoring
Scored dimensions
Explainable, evidence-based dimensions (0–100). The radar shows the investment axes.
这些证据证实 Windmanager 持有一个专有的、跨越数十年的维护日志和运营数据数据集，来自超过2,800 台风力涡轮机。该资产是训练预测性维护人工智能的首要来源，捕获了来自Vestas和 GE 等制造商的各种涡轮机型号的详细事件管理和维修历史。对于工业人工智能供应商而言，这些数据在一个价值12.4 亿美元且快速增长的市场中提供了显著的竞争优势。该数据集的规模、多样性和历史深度（自 1998 年以来）使其成为开发下一代维护优化解决方案的极其稀有的资产。
See dimension details ↓- Dataset Specificity90
主导的“维护日志”，工业领域，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 Volume58
4 个证据命中
Apparent scale of the data, inferred from the number of evidence hits and any explicit volume mentions. - Dataset Freshness82
实时/流式传输
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，这得益于小众风力涡轮机预测性维护市场的快速增长，复合年增长率为 22.8%，这完全依赖于获取专业的工业时间序列数据。[8]
How strongly AI builders and companies are likely to want this data, based on market signals. - Legal Accessibility40
开放/API 访问
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，wpd 集团子公司
How realistic it is to actually obtain the data, given access difficulty and the holder's corporate structure. - Evidence Strength74
4 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 License36
所有权=混合，许可=权利不明确
Whether the company can legally license the data out — based on ownership and licensing complexity. - Corporate Independence50
wpd 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 个数据胃口信号（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 — 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 Audit75
✓ 良好目标 — 一个大型但可联系的陆上和海上风电场运营经理，它作为其核心服务的副产品生成专有维护和性能数据，而该服务似乎是一种未产品化、休眠的资产。问题：该公司拥有 640 多名员工，是一家大型企业，而非中小企业。[4, 6, 15]；该公司提供运营管理服务，包括技术报告和资产优化；此服务与“销售在”之间的区别
- Deep Qualification90
⚠ 需要审查 — 目标是一家管理第三方风电场的服务提供商。运营数据归其客户（资产所有者）所有，并受到德国 KRITIS 法规的严格限制，这使得直接获取数据集非常复杂，尽管其价值显而易见。[数据归公司客户所有；许可受限]
Evidence
Dataset evidence & lineage
What the typed evidence proves the company holds — reframed for clarity and set against the market.
Developer portal
与主要可再生能源开发商（wpd）存在公司关系的证据表明，拥有特权数据访问和强大的数据权利基础，降低了人工智能模型训练的获取风险。
IoT / sensor data
持有者对全球超过2,800 台风力涡轮机进行持续的24/7 监控，生成高频时间序列数据，这对于将运行状况与维护事件相关联至关重要。
Maintenance logs
这证实了自1998 年以来结构化的维护日志的存在，为训练强大的预测模型提供了无与伦比的事件管理和维修历史记录。
Industrial data
该数据集涵盖了超过6 GW的管理容量的多元化车队，包括 Enercon、Vestas 和 GE 等主要涡轮机类型，从而能够开发高度可泛化的人工智能模型，适用于整个行业。
Marketplace
Dataset details
Geographic coverage
Global
Time range
Multi-decade (specific start year not provided)
Update frequency
Real-time
Delivery
API
Formats
Time Series
License
One-time license for use in developing predictive maintenance AI models, subject to data ownership and German KRITIS regulations.
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 high rarity as proprietary, multi-decade maintenance logs from over 2,800 wind turbines, combined with strong demand from the rapidly growing global wind turbine predictive maintenance AI market, drives its significant valuation.
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
Windmanager Maintenance Logs — a Moderate maintenance logs dataset (Time Series modality) in the industrial domain. Primary AI use-case: Predictive Maintenance. Market signal: Global Wind Turbine Predictive Maintenance AI market reached $1.24 billion in 2024, projected to grow at a CAGR of 22.8% (source: Dataintelo). [8]. Investment score 70.0/100 (confidence 0.56). Recommended action: Partnership (group-level).
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