Dataset opportunity
Amloceanographic — 工业传感器数据集机会
Amloceanographic 持有的中等工业传感器数据集，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
56%
Action
许可
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，预计复合年增长率为 27.9%（2026-2033 年）。
Recent dated external facts that triggered this opportunity — auditable provenance.
- 📰press2026-08-07
Marina de Lagos expansion: New berths enter final stretch
dredgingtoday.com ↗ - 📰press2026-07-09
WiseParker OÜ — Estonia – Surveying, hydrographic, oceanographic and hydrological instruments and appliances – Meredünaamika seiresüsteem
ted.europa.eu ↗
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
中等
Accessibility
部分
Legal
混合所有权 — 许可权待明确
Buyer persona
工业人工智能与维护优化供应商
Amloceanographic 拥有源自其自身运营设备的有价值的工业传感器数据集，结构为时间序列模式。此专有资产并非其客户拥有的主要任务数据；相反，它包含一个庞大的历史校准数据库和内部传感器遥测数据。传感器性能和校准调整的丰富历史正是训练和验证强大的预测性维护算法以预测组件故障和优化维护计划所需的此类数据。
商业价值巨大，运营于全球预测性维护市场，该市场在 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。[1] 虽然访问需要仔细协商以区分 AML 的内部数据与最终用户环境数据，但数据集的核心价值在于其稀有且专有的传感器性能元数据。这种复杂性保护了其高价值，使其成为旨在利用快速增长的、专注于最大限度地减少工业设备停机时间的市场的 AI 买家的战略收购。 [1] ⚠ 尽职调查（有价值的数据，可协商的访问权限）：主要任务数据由客户（水文部门、研究机构）拥有；专有价值在于庞大的历史校准数据库和传感器性能元数据；访问需要区分最终用户环境数据和 AML 的内部传感器遥测数据。· 公司：独立。
Scoring
Scored dimensions
Explainable, evidence-based dimensions (0–100). The radar shows the investment axes.
这些证据共同表明 AML Oceanographic 拥有由其专有工业传感器生成并通过专用软件管理的时间序列数据。此类物联网数据是训练预测性维护模型的关键资产，该市场预计将以 27.9% 的复合年增长率增长。对于工业优化领域的 AI 供应商而言，此数据集代表了开发和完善预测设备故障、减少停机时间并提高高价值海洋和工业资产运营效率的算法的直接机会。
See dimension details ↓- Dataset Specificity78
主导的“iot_data”，行业工业，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 Rarity46
专有领域数据（开放降低稀有度）
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 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 Demand95
AI 买家需求异常高，这得益于预测性维护市场的快速扩张，该市场在 2025 年的估值为 142 亿美元，复合年增长率为 27.9%。[1]
How strongly AI builders and companies are likely to want this data, based on market signals. - Legal Accessibility56
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 Feasibility66
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 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 Surplus70
盈余=中等，2 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制造和销售海洋传感器硬件及相关软件，而不是持有其自身运营的专有数据，这使其成为一个工具供应商，并且不适合。问题：该公司的主要业务是为其他组织设计和制造海洋设备（传感器、剖面仪、声纳），[3, 4, 7]；数据由其客户（在水文学、研究等领域）使用 AML 的工具生成；AML 似乎不拥有此运营数据。[4, 7, 21]；该公司提供软件（Sailfish、SeaCast）供其客户配置仪器、管理数据收集和导出数据，这是一种销售形式；该公司被一家私募股权公司收购，作为海洋技术平台的基础，表明其战略重点是技术/产品扩展。
- Deep Qualification70
✓ 通过 — AML 是海洋传感器的工具供应商，这使得假设的“工业传感器数据集”极有可能作为其广泛的全球校准和服务运营的副产品。最近被一家私募股权公司收购以构建海洋技术平台，这是一个强烈的触发因素。然而，关键校准数据集的数据所有权和许可权并未公开记录，仍然是关键的未知数。
Evidence
Dataset evidence & lineage
What the typed evidence proves the company holds — reframed for clarity and set against the market.
Downloads / exports
该公司为其数据收集仪器提供文档，证实了数据集的硬件来源，这对于构建物理基础的预测模型的 AI 供应商至关重要。
IoT / sensor data
校准证书的可用性表明了高质量、可靠的时间序列数据集，这是一项高级功能，可显著减少 AI 开发者的预处理工作。
Industrial data
该公司自身的产品营销强调为工业运营增加可预测性，直接将数据集的目的与预测性维护 AI 供应商的核心需求相匹配。
Data catalog / marketplace
专用数据管理和导出软件的存在表明数据集结构化且易于访问，从而减少了集成摩擦并加速了AI 开发的价值实现时间。
Marketplace
Dataset details
Detailed schema & sample available on access request.
Want this data?
Request access — we broker a secure deal room. Operator-reviewed, no automatic sharing.
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
Amloceanographic 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 was valued at $14.2 billion in 2025, with a projected CAGR of 27.9% (2026-2033) (source: Predictive Maintenance Market Size & Share Report, 2033). [1]. Investment score 45.0/100 (confidence 0.56). Recommended action: License.
From the marketplace
Explore live data opportunities
Aquablu — 事件流数据集机会
View opportunity →工业Weil Wasser — 维护日志数据集机会
View opportunity →工业Cycle0 — 维护日志数据集机会
View opportunity →