DATEX II: European Road Transport Data Exchange

• DATEX II is a standardized European framework for exchanging static and dynamic road transport data, crucial for comprehensive infrastructure monitoring.
• It employs TablePublication for detailed asset inventories and StatusPublication for real-time status updates, supporting KPI analytics and operational benchmarking.
• The framework underpins advanced KPI integration and resilience measurement, optimizing heavy-duty EV charging and megawatt station performance across diverse scenarios.

DATEX II is a European-standardized data exchange framework for road transport information, widely adopted for the communication, dissemination, and integration of real-time, static, and dynamic data between traffic management entities, infrastructure operators, mobility providers, and—critically—charging infrastructure networks for heavy-duty electric vehicles (EVs) and megawatt-scale charging stations (MSC). With foundational support for infrastructure inventory, operational status, and pricing publications, DATEX II is increasingly central to large-scale resilience, optimization, and operational analytics in next-generation, highly electrified transport networks.

1. DATEX II Structure: Publication Models and Data Types

DATEX II is structured to support both static and dynamic publication models. Its core schema (TablePublication and StatusPublication) enables granular, machine-readable descriptions of infrastructure assets, availability, and operational status. For megawatt charging applications, TablePublication encodes site-level inventories—connector counts, connector types and their rated maximum powers, hierarchical identifiers, and payment options—whereas StatusPublication streams temporal state transitions: charger availability, fault or degradation events, and time-stamped pricing signals. This high-fidelity operational visibility is a prerequisite for system-level key performance indicator (KPI) analytics and cross-site benchmarking (Yeh et al., 11 Jan 2026).

The following table summarizes the principal DATEX II data feeds relevant to charging infrastructure:

Publication Type	Key Contents	Use Case
TablePublication	Static site/asset inventory, connector specs	Planning, site analytics
StatusPublication	Dynamic status, fault tags, event timestamps, prices	Operational monitoring

2. Role in Megawatt Charging Station Operation and Resilience Measurement

For heavy-duty MSCs (aggregate powers 1–8 MW, typical port ratings up to 1.2 MW), operational resilience is a key system property. The Resilience KPI framework for MSCs relies on DATEX II as the backbone for infrastructure and state observability, feeding directly into the computation of headline resilience scores and their subcomponents (Yeh et al., 11 Jan 2026):

• Ride-through capability is computed by interval-tagging fault events and confirming whether minimal viable power (as recorded in DATEX II) is delivered.
• Restoration speed and N–1 service rely on accurate site topology, connector status logs, and feeder–connector mapping.
• Queue impact and expected unserved energy require integration of session logs and energy delivery records, both of which can be timestamped and streamed using DATEX II StatusPublication.

DATEX II thus serves as a foundational data source not only for routine site management, but also for resilience benchmarking, cost–benefit analyses (e.g., investments in backup power or redundancy), and cross-site/jurisdictional audits, as described in the formal SRS (Site Resilience Score) methodology (Yeh et al., 11 Jan 2026).

3. Integration with Advanced KPI and Optimization Frameworks

The utility of DATEX II extends into advanced KPI integration and design optimization. The Resilience KPI framework aggregates five normalized subcomponents—ride-through ($R_{rt}$), restoration speed ($R_{rs}$), N–1 service ($R_{n1}$), normalized unserved energy ($1 - \widetilde E_{ue}$), and queue impact ($Q_i$)—into a headline score:

$$\mathrm{SRS} \;=\; 100 \sum_{i\in\mathcal{S}} w_i\,\mathrm{Norm}_i$$

with all input signals traceable to or supported by DATEX II core feeds wherever possible (Yeh et al., 11 Jan 2026). When combined with auxiliary event logs (e.g., CSMS/OCPP), as well as SCADA and EMS data for power availability and BESS (battery energy storage system) status, the framework enables:

• Monthly or quarterly automated pipeline reporting of cross-site resilience.
• Stressor-specific breakouts for diagnostics and targeted mitigation, utilizing event tags and status codes from DATEX II.
• Asset-specific trend monitoring and alerting for operational anomalies.

While DATEX II provides a robust foundation for most asset inventory and dynamic status KPIs, full resilience assessment for MSCs often requires data extensions: real-time grid headroom, BESS state-of-charge, bay geometry, and environmental hardening—domains outside the current DATEX II schema.

4. Extensions and Limitations in Charging and Maritime Contexts

While DATEX II is prominent in road mobility and land-based charging, offshore charging stations (OCS) and electrified ship corridors present novel data interoperability challenges. For example, the placement and sizing of OCSs—and the operational scheduling of battery-electric ships—requires integration of static and real-time data not only on station location and status, but on route-specific marine geography and renewable resource availability. The Shanghai–Busan corridor study implicitly assumes availability of asset status and operational data in a machine-readable format analogous to DATEX II (Li et al., 2023).

A plausible implication is that future offshore transport electrification will necessitate either extension of DATEX II or robust interoperation with marine data protocols for site inventory, renewable energy status, ship–station matching, and dynamic queue/event management. Generalizing, the use of DATEX II for heavy-duty megawatt-class charging (land or maritime) will require enhanced schemas to cover grid capacity, flexibility, geometry, weather resilience, and other KPIs that transcend current publication types (Yeh et al., 11 Jan 2026).

5. Procedures, Data Pipelines, and Operationalization

Automated data ingestion pipelines leveraging DATEX II typically involve:

1. Ingesting Table/StatusPublication feeds, plus relevant charging session and grid-side logs.
2. Event segmentation and interval tagging, using DATEX II event codes.
3. Computation of normalized sub-KPIs using published formulas; for example, $R_{rt}$ via fault interval analysis, $E_{ue}$ via delivered/requested energy deltas.
4. Weighted aggregation to form SRS or other composite metrics.
5. Publication of results, including headline resilience scores, stressor-specific breakouts, and visualizations for diagnostic or procurement use.

DATEX II-driven routines are employed both for routine monitoring and for supporting strategic and regulatory objectives—such as benchmarking site resilience, justifying investment in on-site flexibility (e.g., BESS, backup generation), and informing cost–benefit analyses over diverse operational and contingency scenarios (Yeh et al., 11 Jan 2026).

6. Broader Impact and Future Directions

DATEX II underpins resilient, interoperable EV charging infrastructure across large markets. As transport electrification scales into heavy-duty road and maritime segments—where interdependence between grid, battery, and renewable resources is acute—DATEX II's extensibility and integration with SCADA, EMS, and other data sources will delineate its utility. Essential future enhancements include:

• Real-time power/energy headroom and status signals from DSO/TSO/SCADA interfaces.
• On-site energy storage (BESS) and islanding support data.
• Extension of publication models to encode bay/vehicle geometry, hardening, and environmental KPIs.
• Procedures for harmonized cross-sector reporting, combining transportation, grid, and site-level data on a common timescale.

DATEX II’s centrality in the data ecosystem for megawatt-class charging infrastructures establishes a common platform for operational visibility, resilience computation, and optimization—enabling systematic, auditable, and comparable measurement of infrastructure quality and adaptability across vendors, sites, and regulatory domains (Yeh et al., 11 Jan 2026).