Dataset opportunity
Ospreycharging — Mobility & Geospatial Dataset Opportunity
Large mobility & geospatial dataset held by Ospreycharging, usable for Geo AI and Routing & Forecasting.
Score
78.7
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
65%
Action
Data Sharing Agreement
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
Global Location Intelligence market = $21.03B in 2024, CAGR 16.0% (source: Fortune Business Insights) [1]
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
Mobility & Geospatial Dataset
Modality
Tabular
Sector
mobility
Volume
Large
Freshness
Real-time
Rarity
High (proprietary)
Accessibility
Restricted
Legal
Owned by the company — GDPR-sensitive (PII review)
Buyer persona
Geospatial-AI & mobility-analytics teams
Ospreycharging holds a valuable Mobility & Geospatial Dataset in Tabular format, detailing EV charging events across their UK network. The dataset integrates `geo_data` (charger locations), `iot_data` (technical charging curves), and `transaction_data` (usage patterns), making it exceptionally well-suited for Geo AI applications like network planning, demand forecasting, and site selection analysis.
The business value of this data is significant, tapping into the Global Location Intelligence market, which is estimated at $21.03 billion in 2024 and projected to grow at a 16.0% CAGR. [1] Despite access complexities—such as PII in user history (GDPR), proprietary technical data, and shared ownership clauses with site partners—the rarity and real-world nature of this granular charging data make it a premium asset for AI buyers seeking a competitive advantage in the mobility sector. ⚠ Diligence (valuable data, access to negotiate): User-level charging history contains PII (GDPR sensitive); Technical charging curves and battery handshake data are proprietary and likely dormant; Data from chargers located on partner sites (e.g., Lidl, McDonald's) may have shared ownership clauses · corporate: independent.
Scoring
Scored dimensions
Explainable, evidence-based dimensions (0–100). The radar shows the investment axes.
This evidence collectively proves Osprey Charging owns a proprietary, high-resolution dataset detailing the operation of its 1,500+ UK electric vehicle charging stations. The data combines granular geospatial, transactional, and IoT streams, offering a uniquely detailed view of real-world EV charging behavior and network performance. For Geospatial-AI and mobility-analytics teams, this dataset is a powerful asset for developing advanced site selection models, optimizing infrastructure, and capturing share in the rapidly growing $21B+ global location intelligence market.
See dimension details ↓- Dataset Specificity100
dominant 'geo_data', sector mobility, 4 specific types
How sharply the data targets a specific, hard-to-substitute domain or task. Niche, well-defined data scores higher than generic. - Dataset Rarity70
proprietary domain data (open lowers rarity)
How scarce and proprietary the data is. Unique domain data scores high; openly available data lowers it. - Dataset Volume70
6 evidence hits
Apparent scale of the data, inferred from the number of evidence hits and any explicit volume mentions. - Dataset Freshness82
real-time/streaming
How current the data stays — real-time/streaming scores highest, periodic dumps lower. - Training Value94
fit for Geo AI
How useful the data is for the target AI use-case — its fit for model training or fine-tuning. - Buyer Demand90
AI buyer demand is extremely high, driven by the rapid growth of the **$21.03 billion** Location Intelligence market (CAGR **16.0%**) where granular, real-world mobility data is a key competitive differentiator. [1]
How strongly AI builders and companies are likely to want this data, based on market signals. - Legal Accessibility14
open/API access
How legally easy the data is to obtain and use — open/API access scores high; PII or regulated data scores low. - Acquisition Feasibility48
medium difficulty, independent
How realistic it is to actually obtain the data, given access difficulty and the holder's corporate structure. - Evidence Strength89
5 evidence types, 6 hits
How solid the proof is that the company holds this data — diversity of evidence types and number of hits. - Right to License62
ownership=owned, licensing=gdpr_sensitive
Whether the company can legally license the data out — based on ownership and licensing complexity. - Corporate Independence90
independent
Whether the holder can decide alone — an independent company scores higher than a subsidiary of a large group. - Data Orientation73
3 data-appetite signals (3 types)
How actively the company invests in data, measured by its data-appetite signals (hires, products, APIs…). - Dormant Data Surplus92
surplus=high — proprietary data beyond what's already monetised
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
✓ good target — Osprey Charging is an ideal target as it operates a large, rapidly growing UK network of EV chargers, generating valuable proprietary mobility and energy data as a by-product of its core business, and does not appear to be selling this data or derived intelligence. Issues: The company is heavily backed by private equity and institutional investors (Cube Infrastructure Managers, Investec), which could influence data strategy or com; The company mentions a proprietary software platform, 'Osprey Iris', used to manage the network and gain insights, indicating they are data-aware, though there ; Their privacy policy notes they share anonymised or metadata with property partners, which is a very low-level form of data monetization but does not constitute
- Deep Qualification90
✓ pass — Osprey is a data holder, not a seller; its core business is operating an EV charging network. The 'Mobility & Geospatial Dataset' is a coherent byproduct, but it is laden with PII (GDPR sensitive) and potential shared ownership clauses with site partners, complicating its commercialization.
Evidence
Dataset evidence & lineage
What the typed evidence proves the company holds — reframed for clarity and set against the market.
Geospatial data
With a dedicated GIS analyst and a strategy of 'thoughtfully placed' chargers, this proves the existence of a sophisticated site selection dataset, including details on landowner partners.
Downloads / exports
This indicates the company tracks customer payment methods and preferences, providing valuable data on payment behavior and user friction points for optimizing the customer journey.
Industrial data
Evidence of large-scale installation projects with major commercial partners confirms the availability of data on network expansion logistics and B2B partnerships.
IoT / sensor data
This confirms the collection of time-series IoT sensor data directly from chargers, tracking charger performance and power delivery metrics crucial for operational and predictive maintenance models.
Transaction data
This is direct evidence of granular transactional data from over 1,500 stations, detailing cost, power, and duration for analyzing consumer behavior and demand patterns.
Marketplace
Dataset details
Detailed schema & sample available on access request.
Coverage
Scanned sources
Deliverable
Premium dataset report
Ospreycharging Mobility & Geospatial — a Large mobility & geospatial dataset (Tabular modality) in the mobility domain. Primary AI use-case: Geo AI. Market signal: Global Location Intelligence market = $21.03B in 2024, CAGR 16.0% (source: Fortune Business Insights) [1]. Investment score 78.7/100 (confidence 0.65). Recommended action: Data Sharing Agreement.
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