gms | German Medical Science

Background: ?Enabling secondary use of medical routine data requires general understanding of given information. As a common practice, this understanding is achieved through metadata and its interconnections. Metadata can be stored in so-called metadata repositories (MDR) to store, manage, and allocate meta information about data. More advanced functionalities are matching and mapping. Matching: The discovery of related or equivalent metadata; Mapping: The relationship between data elements such as conversion rules. These rules are difficult to determine and often require manual effort. Therefore, there is a great need for advanced data analysis techniques promoting the definition of matchings and mappings.

Mapping challenge: As preparation for this workshop a healthy hackathon takes place. Scientific challenges offer the evident comparison of different approaches and occur regularly in the field of medical informatics, e.g. image processing or connected healthcare. This workshop aims to adjust the principle of a challenge to the research community in eHealth. Our Mappathon is a metadata mapping challenge with the aim to find corresponding data elements within a set of (similar) metadata sets and to correlate data elements among each other. For our challenge, metadata sets of routine documentation and clinical research are provided by the Portal of Medical Data Models [1]. Training data sets will be curated and made available for download in different formats like FHIR questionnaires or CDISC ODM. Suitable mappings, manually determined by an expert committee as well as the evaluation matrix, according to FHIR ConceptMaps relations [2], are transparently published. Participants are invited to download the training set, including data sets and eCRFs as well as the corresponding expert mapping of related data elements. This will allow validating and optimizing the algorithms and methods. Any automatic method that predicts the valid mapping is of great interest. There is no restriction on new, innovative or unpublished methods and no limitations on including external information like terminologies. Participants are invited to use coding systems and any terminology server. During the training phase the organizers will enable an automated evaluation service for checking on results.

Mappathon: During the workshop a set of test cases will be released of which participants will be asked to run their algorithm on and upload their mapping results. To complete a successful participation, participants will need to submit a short abstract, describing the applied method. Each team will be asked to give a brief presentation detailing their approach within the workshop. The organizers will then evaluate each case and establish a ranking of the participating teams. All results will be presented during the workshop and will be discussed with invited experts and all workshop attendees.

Varying data sets and the related heterogeneity make it nearly impossible to compare different approaches in a fair way. By providing a high-quality data set publicly as well as pre-defined evaluation rules, this challenge aims to overcome these limitations and to create a common framework for the comprehensible and adequate comparison of results.

All relevant information, the registration and metadata sets can be accessed here: http://www.mappathon.de

The authors declare that they have no competing interests.

The authors declare that an ethics committee vote is not required.