railML.org is proud to announce that railML3.1 is officially released after three years of development work. railML3.1 was developed completely from scratch and is the result of over 10 years of experience coordinators, stakeholder and railML.org partners gained with railML, as well as the continuously changing requirements of the railway sector. It was developed use case based and integrates, amongst others, the use cases:

• Schematic Track Plan (SCTP, lead by IS),
• Network Statement (NSTM, lead by IS) and
• Routes for timetable simulation (RSIM, lead by IL)

railML 3.1 is the first railML version to contain an interlocking scheme and has focused on the requirements of the new infrastructure model. The implementation work of the establisehd timetable schema, as well as vehicle schemes and other infrastructure and interlocking use cases will begin in spring 2019.

The following documents describing the schema are currently available for download:

• UML documentation (HTML derived from Enterprise Architect)
• XSD (HTML derived from XML Spy)
• Use case documentation (PDF)
• Changelog (TXT)

As a next step the railML 3.1 tutorial will be updated and training documents prepared. Furthermore, an entirely new wiki is currently developed, which will document the schema in the usual form containing descriptions of the elements and attributes, best practice, source code examples and semantic constraints. However, the backend is a lot more sophisticated than the current railML2.x wiki and will allow an automatic content generation derived from the XSD. Please see the corresponding news article for more information about the new railML3.x wiki. Especially the new railML wiki will require quite some work in near future. railML.org is therefore very thankful for contributions from community side, financially or in-kind.

We would like to thank all involved parties for supporting the developments of railML 3.1 and with this new standard mutually enhancing the exchange of railway data throughout the sector. We are looking forward to the future collaboration and will start focussing on railML 3.2. Please, let us know about your experience with railML 3.1, so that this can be brought into railML 3.2!