What Is ASAM MDF? The Definitive Guide | Page: 4 of 4 | Previous: Page 3: What is new in ASAM MDF 4.3

Who uses ASAM MDF? ASAM MDF is used across the global automotive industry, from OEM test labs to Tier 1 supplier development centers to independent test service providers. The format originated in ECU calibration at Vector and Bosch in the early 1990s and has since expanded to cover every major testing domain. The twenty organizations that contributed to MDF 4.3 include automotive OEMs (Audi, BMW, Mercedes-Benz, Porsche), measurement tool vendors (dSPACE, ETAS, IPETRONIK, Kistler, Vector Informatik), data management providers (HighQSoft, Peak Solutions), automation and diagnostics companies (Accurate Technologies, iASYS, RA Consulting), and test system integrators (AVL, ViGEM). Their participation in the standard's development is itself evidence of MDF's production relevance; these organizations contribute because their customers demand MDF support.

Adoption extends well beyond the contributing organizations. Every major ECU measurement and calibration tool either uses ASAM MDF as its native recording format or provides importers and exporters. ASAM MDF has become the de facto standard for measurement and calibration systems, as ASAM describes it, but the format now serves far more than the ECU calibration niche where it began.

Powertrain test benches at automotive OEMs record engine performance data in MDF. NVH labs store accelerometer and microphone array data in MDF. Vehicle dynamics teams record steering, acceleration, and GPS trajectories in MDF. Crash and safety departments archive high-frequency sensor recordings in MDF. Durability teams store strain gauge data and classification results in MDF. ADAS development groups are now beginning to record radar, LiDAR, and camera data in MDF 4.3. The ASAM MDF format spans the entire testing lifecycle, from individual sensor measurements to full vehicle validation campaigns.

Organizations that manage their MDF data through ASAM ODS systems include BMW, Ford, Audi, Volkswagen, Honda, Bosch, and Cummins. The data volumes are substantial; test campaigns at large OEMs generate terabytes of MDF files per month, making efficient import, compression, and indexing essential for practical data management.

The ASAM MDF tools ecosystem is one of the format's strongest practical advantages for engineers evaluating measurement data formats. Engineers who adopt ASAM MDF gain access to a broad and mature set of commercial and open-source MDF tools spanning recording, analysis, validation, and programming. The table below lists the major MDF tools and libraries available as of Q1 2026.

As of early 2026, among the major MDF tools, only Vector (CANape, MDF4 Lib) and ETAS (MDA V8.7.7) explicitly market MDF 4.3 support with the new ZStandard and LZ4 compression algorithms. Other vendors contributed to the standard but have not yet announced MDF 4.3-specific features in their products. The asammdf Python library, which serves as the de facto open-source entry point for MDF work in Python, supports MDF 4 generically but does not yet confirm full MDF 4.3 support for the new block types (DSBLOCK, CLBLOCK, CVBLOCK, CUBLOCK). Engineers working with MDF 4.3-specific features (dynamic data, Raw Sensor Logging) should verify tool support on a case-by-case basis until the ecosystem matures.

The breadth of the MDF tools ecosystem is a practical differentiator when comparing ASAM MDF to alternative formats. A test engineer can record data with CANape, explore it with the free MDF Viewer, analyze it with MATLAB or Python (via asammdf), automate analysis with HighQSoft's Merlin Analysis Server, and archive it in an ODS system, all using the same MDF format throughout. This seamless toolchain is the result of thirty years of MDF tools ecosystem development and ASAM's governance model, which ensures that tool vendors implement the same specification.

HighQSoft integrates ASAM MDF into test data management as the management layer that receives MDF data from any recording tool, combines it with metadata from other sources, and makes the complete dataset searchable, governed, and analysis-ready. HighQSoft does not make recording tools or analysis frontends. This positions HighQSoft at the critical junction between data acquisition (where MDF excels) and data management (where ASAM ODS excels).

A central design principle is flexibility with MDF sources. HighQSoft's ModelMapper (MoMa) handles MDF4 files from any tool, any version, and any domain. Whether the MDF file was recorded by Vector CANape during an ECU calibration session, by ETAS INCA during emissions testing, by an IPETRONIK mobile logger during a durability campaign, or by a custom ADAS data logger during autonomous driving validation, ModelMapper imports the data into ASAM ODS using the same rule-driven ETL framework. Approximately 455 built-in rules across fourteen packages handle the transformation from MDF channels and metadata to ODS entities, adapting to the target ODS application model. Custom Java rules extend the framework for organization-specific requirements.

ModelMapper combines MDF mass data with external metadata (test orders, project assignments, calibration records, ambient conditions) during import, creating fully contextualized ODS records that are findable through structured queries and compliant with governance requirements. HighQSoft's Merlin Analysis Server can trigger ModelMapper imports automatically, then execute analysis jobs on the imported data using Python, MATLAB, Java, or Spark, and store the results back into ODS. This creates a closed loop from MDF recording to managed, analyzed, governed data, running without manual intervention.

The three integration patterns (import, reference, and storage) accommodate different organizational needs. Import converts MDF data fully into ODS entities for active analysis and governance. Reference mode creates ODS metadata pointing to external MDF files, making archived recordings findable without copying mass data. Storage mode manages MDF files as attachments within ODS. In practice, organizations combine these patterns: full import for actively analyzed data, and reference mode for archived recordings that need to be findable but are accessed infrequently.

Imported MDF data becomes accessible through HQL queries, Python (via pyHQL), MATLAB (via the ASAM ODS Toolbox), or the ASAMCommander web portal. The ASAM ODS Toolbox for MATLAB provides direct MATLAB connectivity to MDF data imported into ODS, a capability no other TDM vendor offers, used in production at BMW, Bosch, Ford, and Cummins.

HighQSoft has provided test data management solutions to automotive OEMs for over 25 years, with production deployments at BMW, Ford, Audi, Volkswagen, Bosch, Cummins, and Honda. As a contributor to ASAM MDF 4.3, HighQSoft brings direct standards expertise to organizations implementing or upgrading their MDF data workflows.

To discuss how HighQSoft integrates ASAM MDF into your test data management infrastructure, request a live demonstration of ModelMapper, Merlin Analysis Server, or ASAMCommander, or explore the existing HighQSoft MDF overview at https://www.highqsoft.com/standardization/standards/asam-mdf4/.

HighQSoft provides test data management solutions for automotive OEMs with over 25 years of production deployments at BMW, Ford, Volkswagen, Bosch, Cummins, and Honda. As a contributor to ASAM MDF 4.3, HighQSoft bridges the gap between measurement data acquisition and enterprise data management.