Pan-European Data Harmonization for Biobanks in ADOPT BBMRI-ERIC

Appl Clin Inform. 2019 Aug;10(4):679-692. doi: 10.1055/s-0039-1695793. Epub 2019 Sep 11.

Abstract

Background: High-quality clinical data and biological specimens are key for medical research and personalized medicine. The Biobanking and Biomolecular Resources Research Infrastructure-European Research Infrastructure Consortium (BBMRI-ERIC) aims to facilitate access to such biological resources. The accompanying ADOPT BBMRI-ERIC project kick-started BBMRI-ERIC by collecting colorectal cancer data from European biobanks.

Objectives: To transform these data into a common representation, a uniform approach for data integration and harmonization had to be developed. This article describes the design and the implementation of a toolset for this task.

Methods: Based on the semantics of a metadata repository, we developed a lexical bag-of-words matcher, capable of semiautomatically mapping local biobank terms to the central ADOPT BBMRI-ERIC terminology. Its algorithm supports fuzzy matching, utilization of synonyms, and sentiment tagging. To process the anonymized instance data based on these mappings, we also developed a data transformation application.

Results: The implementation was used to process the data from 10 European biobanks. The lexical matcher automatically and correctly mapped 78.48% of the 1,492 local biobank terms, and human experts were able to complete the remaining mappings. We used the expert-curated mappings to successfully process 147,608 data records from 3,415 patients.

Conclusion: A generic harmonization approach was created and successfully used for cross-institutional data harmonization across 10 European biobanks. The software tools were made available as open source.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Biological Specimen Banks / standards*
  • Colorectal Neoplasms
  • Europe
  • Humans
  • Reference Standards

Grants and funding

Funding The present work has been co-funded by ADOPT BBMRI-ERIC supported by EU Horizon 2020, grant agreement no. 676550. It was performed in (partial) fulfillment of the requirements for obtaining the degree “Dr. rer. biol. hum.” from the Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU) (SM).