Annual Meeting of the NCI Cohort Consortium (Abstract Submission): Submission #1

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data:
  additional_authors:
    - add_author_degree: 'M.D. M.P.H.'
      add_author_first_name: Konrad
      add_author_last_name: Stopsack
      add_author_middle: H.
      add_author_organization: 'Leibniz Institute for Prevention Research and Epidemiology – BIPS'
    - add_author_degree: M.S.
      add_author_first_name: Hannah
      add_author_last_name: Guard
      add_author_middle: E.
      add_author_organization: 'Harvard T.H. Chan School of Public Health'
    - add_author_degree: Ph.D.
      add_author_first_name: Caroline
      add_author_last_name: Himbert
      add_author_middle: ''
      add_author_organization: 'Huntsman Cancer Institute'
    - add_author_degree: Ph.D.
      add_author_first_name: Yuliya
      add_author_last_name: Leontyeva
      add_author_middle: ''
      add_author_organization: 'Harvard T.H. Chan School of Public Health'
    - add_author_degree: M.S.
      add_author_first_name: LeeAnn
      add_author_last_name: Lucas
      add_author_middle: ''
      add_author_organization: 'Harvard T.H. Chan School of Public Health'
    - add_author_degree: M.S.
      add_author_first_name: 'Colleen '
      add_author_last_name: McGrath
      add_author_middle: B.
      add_author_organization: 'Harvard T.H. Chan School of Public Health'
    - add_author_degree: M.P.H.
      add_author_first_name: Jane
      add_author_last_name: Vaselkiv
      add_author_middle: B.
      add_author_organization: 'Harvard T.H. Chan School of Public Health'
  degree_s_: 'MD MPH'
  email: stopsack@leibniz-bips.de
  first_name: Konrad
  last_name: Stopsack
  organization: 'Leibniz Institute for Prevention Research and Epidemiology – BIPS'
  poster_title: 'An R Package for the Health Professionals Follow-up Study to Increase Accessibility and Reusability of Legacy Data Structures'
  short_biography_: |-
    Background: With long-term follow-up of prospective cohorts, not just participants but also data structures and data pipelines age. Accessibility and reusability of such legacy data can be major barriers to analysis projects, compounded by analytic software with vendor lock-in. 

    Methods and Results: One approach to improving accessibility and reusability is the creation of open-source software that leaves the original data storage intact and provides well-documented, transparent translations of legacy data structures into modern data objects, which are then directly usable in reproducible analytic pipelines. The test case, presented here, is the R package {hpfs} for loading and reshaping data from the Health Professionals Follow-up Study. This software has been developed with a team-based approach, fully online and with collaboration and quality control supported by a version control system. This effort has required a deep understanding of the cohort data as well as emphasis on consistent software design. Initial application experience suggests that this approach eliminates some common pitfalls in analyses and provides major efficiency gains.

    Conclusion: Transparent translations of legacy data by open-source software are one approach to substantially improve accessibility and reusability of valuable cohort data.
  title: Professor