NCI Office of Data Sharing (ODS) Data Jamboree (Abstract Submissions): Submission #14

serial: '14'
sid: '144985'
uuid: 95bef776-54b2-4760-a5b5-db791c147a09
uri: /nci/ods-data-jamboree/abstractsubmissions
created: '1750273595'
completed: '1750273720'
changed: '1750273720'
in_draft: '0'
current_page: ''
remote_addr: 10.208.28.250
uid: '0'
langcode: en
webform_id: nci_office_of_data_sharing_abstr
entity_type: node
entity_id: '2107'
locked: '0'
sticky: '0'
notes: ''
metatag: meta
data:
  category: 'Methods to enable data interoperability'
  degree_s_: Ph.D.
  email: james.tanis@nih.gov
  first_name: James
  keywords_abstracts: ''
  last_name: Tanis
  middle_initial: H
  organization: 'Essential Software Inc'
  organization_address:
    address: ''
    address_2: ''
    city: 'Gaithersburg, MD'
    country: ''
    postal_code: ''
    state_province: ''
  other_please_specify_: ''
  summary: |-
    Attributing the data model of the Cancer Clinical Data Commons (C3DC) with Common Data Elements (CDEs) provides significant value.  It enables 
    •	Standardization and interoperability
    •	Enhanced data quality and reproducibility
    •	Improved efficiency and cost-effectiveness
    •	Facilitates data sharing and collaboration
    •	Supports advanced analytics and AI applications
    Regularly updating the C3DC data model is crucial for its usefulness because CDEs can become outdated.  Due to its time-consuming nature, manually reviewing the multitude of data elements and CDEs required for this update is a challenge.  To significantly reduce human effort, we propose to develop a LLM tool to automatically match CDEs to C3DC data elements.  Humans will only verify the tool’s suggestions in the final step.  
  title: 'Senior Bioinformatician'
  ttile: 'Semi-Automatic Mapping of CDEs to the C3DC Data Model'
  upload_abstract: '65541'