A consensus-based guideline that identifies the onboard datasets that should be openly available to equipment owners in a real-time, read-only format.

Mine operators are looking for advanced services to support the ongoing health, condition, and performance of equipment, and the modern mine environment is making this possible. New technologies and systems generate huge volumes of source data related to the real-time and historical performance of mining equipment. These data-related capabilities can influence decision-making around equipment investment. 

Further, to ensure the safety of their operations and extract maximum value from these data, operators need to be able to access them. At the same time, original equipment manufacturer (OEM) intellectual property rights must also be protected. Therefore, there is a pressing need for consensus on the topic.

The guideline represents a consensus between operators and OEMs that identifies onboard datasets that should be openly available to equipment owners in a real-time, read-only format. 

Since the publication of the first edition in 2016, increased digitalization and adoption of technologies such as autonomous systems have made the issues surrounding open data even more complicated while also making their resolution more pressing. The project group is now working on a second edition.


  • List of onboard datasets for surface mines – including haul trucks, drills, loaders, dozers, hydraulic diesel excavators, graders, electric rope shovels and scrapers. 
  • List of onboard datasets for underground mines – LHD trucks, drills, scoops, trams, loaders, rock bolters, shotcrete trucks, lifts/forks lifts, chargers and longwalls.
  • Launched

  • Content Development

    2nd edition

  • Editing

  • Review

  • Published


2016 Apr| Mobile Equipment Open Data Consensus Guideline

The guideline provides access to onboard data from mobile equipment, representing a consensus between operators and OEMs. It addresses industry concerns about data access and determines commonly agreed-upon data availability.