A behind-the-scenes tour of the IEDB curation process: an optimized process empirically integrating automation and human curation efforts.
Nima SalimiLindy EdwardsGabriele FoosJason A GreenbaumSheridan MartiniBrian ReardonDeborah ShackelfordRandi VitaLeora ZalmanBjoern PetersAlessandro SettePublished in: Immunology (2020)
The Immune Epitope Database and Analysis Resource (IEDB) provides the scientific community with open access to epitope data, as well as epitope prediction and analysis tools. The IEDB houses the most extensive collection of experimentally validated B-cell and T-cell epitope data, sourced primarily from published literature by expert curation. The data procurement requires systematic identification, categorization, curation and quality-checking processes. Here, we provide insights into these processes, with particular focus on the dividends they have paid in terms of attaining project milestones, as well as how objective analyses of our processes have identified opportunities for process optimization. These experiences are shared as a case study of the benefits of process implementation and review in biomedical big data, as well as to encourage idea-sharing among players in this ever-growing space.