Dataset opportunity
Mdsaero — 工业传感器数据集机会
Mdsaero 持有的中等规模工业传感器数据集，可用于预测性维护和异常检测。
Score
48
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
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 = 2025 年为 142 亿美元，复合年增长率为 27.9%。
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.
Profile
Dataset profile
Type
工业传感器数据集
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 — 许可权待明确
Buyer persona
工业 AI 和维护优化供应商
Mdsaero 拥有高价值、高频率的时间序列数据，这些数据是在燃气轮机发动机测试期间由工业传感器生成的。这些工业数据通过专有的 nxDAS 软件捕获，提供了随时间变化的详细运行指标，使其直接适用于训练和验证旨在预测组件故障的预测性维护算法。
该数据的市场潜力巨大；全球预测性维护市场在 2025 年的估值为142 亿美元，预计将以 27.9% 的复合年增长率扩张。[2] 虽然由于与原始设备制造商 (OEM) 的数据共享以及航空航天和国防行业的限制，访问权限很复杂，但这些因素也证实了数据的战略价值。包括 GLACIER 等专业设施的独特数据集，使其成为严肃的 AI 买家稀有且有价值的资产。[2] ⚠ 尽职调查（有价值的数据，可协商的访问权限）：数据所有权可能与主要原始设备制造商（Rolls-Royce、Pratt & Whitney）共享特定发动机测试数据；运营 GLACIER 设施，该设施生成独特的环境和结冰测试数据集；专有的 nxDAS 软件捕获高频传感器数据，这些数据可能由 MDS 存储/聚合；高度管制的航空航天和国防行业限制。· 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 Mdsaero 拥有来自工业燃气轮机发动机测试的专有高速时间序列传感器数据集，包括独特的寒冷天气场景。这些稀有的工业数据直接支持先进的预测性维护算法的开发，这是 AI 供应商瞄准快速增长的工业优化市场的关键需求。对于寻求改进发动机性能和可靠性模型的开发人员来说，该数据集在预计到 2025 年将达到 142 亿美元的市场中代表着显著的竞争优势。
See dimension details ↓- Dataset Specificity90
主导的“物联网数据”，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 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
AI 买家需求异常高，这得益于预测性维护市场的快速扩张，预计复合年增长率为 27.9%。[2]
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，独立
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 Independence90
独立
Whether the holder can decide alone — an independent company scores higher than a subsidiary of a large group. - Data Orientation56
2 个数据胃口信号（2 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 Audit67
⚠ 审查 — 该公司的核心业务是销售燃气轮机发动机的整体测试解决方案，其中包括一个复杂的专有数据采集和分析软件平台 (nxDAS)，他们积极将其作为产品进行营销。问题：公司核心产品包括“nxDAS”，一个数据采集和分析软件平台，这是一种销售智能的形式。[1, 10]；他们明确将解锁数据潜力和提供数据采集系统作为其解决方案的关键部分进行营销。[10, 15]；该公司的业务是为客户提供测试*解决方案*，而不仅仅是运营一个数据是休眠副产品的业务。[1, 3, 13]
- Deep Qualification70
✓ 通过 — MDS 主要为发动机测试设备构建和提供工程服务，这意味着生成的数据通常归其 OEM 客户所有。然而，他们也至少运营一个设施（GLACIER）作为一项服务，这提供了一个潜在但复杂的访问数据的机会。
Evidence
Dataset evidence & lineage
What the typed evidence proves the company holds — reframed for clarity and set against the market.
Developer portal
该公司运营一个面向开发者的门户网站，这表明其致力于为发动机开发者提供高质量、易于访问的数据，以构建和测试新应用程序。
IoT / sensor data
Mdsaero 通过其燃气轮机发动机的整体测试解决方案生成高速时间序列数据，提供复杂的预测性维护模型所需的底层传感器读数。
Industrial data
该数据集包括来自世界上最大的户外结冰测试设施的稀有传感器读数，提供了关于设备在极端天气条件下性能的宝贵数据。
Event streams
数据通过专有的高通道数数据采集系统捕获，确保了高保真度和粒度的事件流，非常适合训练复杂的AI 模型。
Marketplace
Dataset details
Detailed schema & sample available on access request.
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Coverage
Scanned sources
Deliverable
Premium dataset report
Mdsaero Industrial Sensor — a Moderate industrial sensor dataset (Time Series modality) in the industrial domain. Primary AI use-case: Predictive Maintenance. Market signal: Global Predictive Maintenance market = $14.2B in 2025, CAGR 27.9% (source: Grand View Research). [2]. Investment score 48.0/100 (confidence 0.56). Recommended action: Acquire.
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