Data Standards Hackathon

Project name: Data Standards Hackathon

Project leaders: Martin Maiers

Detailed project description:

We would like to invite everyone interested to attend the online DaSH 12 on February 17 & 18 2022, full details at Please contact for an invitation.

Historically, there have been few standards regarding HLA and KIR genotyping data, and associated meta-data, and very few public tools for the management of these data. Recognizing the tremendous potential of NGS for immunogenomics, and the need for coordinated consolidation of the data for such a broad field, we have organized a series of collaborative software-development events (“hackathons”) focused on the creation of novel tools, standards and services that will maximize the utility of immunogenomic data for clinical and basic research science. These meetings have been supported by the National Marrow Donor Program (NMDP) and several commercial vendors.

During previous Data Standards Hackathon events, participants helped finalize specifications for MIRING, worked on tools implementing it (e.g., HML 1.0, HL7-FHIR), and considered ways how to express novel polymorphisms without human curation (e.g., Gene Feature Enumeration).

Suggested topics for this event include

  • Development of tools for translating between proprietary formats and open standards; specifically: HL7-FHIR for better integration with electronic medical records
  • Automated annotation and curation of sequence variation
  • Validation of population genetics tools
  • Support for incorporation of HLA into smartphone apps
  • Software for analysis of MHC and KIR region genomics

Milestones in years:


  • Data standards Hackathon: WMDA Office, Ledien, Mar 23-24, 2019
  • Data standards Hackathon, Denver, Colorado May 30-31, 2019
  • HL7-FHIR development at HL7-working group meetings and connectathons



  • Virtual Data standards hackathon February 17-18, to again be hosted at gathertown
  • Data standards hackathon during IHIW

Patient/sample description (if applicable, details, inclusion/exclusion criteria):


Data/Samples/Reagents required (number, type of data, inclusion/exclusion criteria):


Data infrastructure required:

  • AWS resources (EC2, S3)