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Project Organization

Project Organization

Owned by Brian Lee
Last updated: Mar 20, 2018

Collecting together different collaboration items temporarily.


Deliverable:

  • Evaluation Metric - pick
    • Site usage - unique monthly visitors, monthly sessions, time on site
    • #Data sets
    • %Data sets
    • #Programs participating
    • Quality of data sets - easier to use, higher applicability (eg multiple years into single data set) - lower user burden
  • Collecting baseline data
  • Acquisition plan for 2019
  • Updated web site look and feel
  • OPHSS program web site created - web site presence on cdc.gov
  • One pager
  • System transition - ESC, security
  • Project charter
  • Road show
  • /wiki/spaces/OpenData/pages/109084691
  • Long Quality Report
  • Linda's quality spreadsheet (exists for injury) for every org in CDC
  • Onboarding packet
    • Current stewards
    • New stewards
  • FAQ / Howtos (look how easy it is)
  • known unknowns data (all the data sets not in Data.CDC.gov)
  • User profile (stewards, researcher, vizzers) - expanding on Fred's R script


Activities:

  • Road show (needs OPHSS site, needs new look and feel, quick quality report)

Tasks

  • Adding Analytics
    • Adding Adobe Analytics (LR)
    • Adding Google Analytics (testing BL)
  • Changing MMWR to NNDSS (LR)

Questions:

  • What's quality? What metrics track quality?

Timeline

Draft Organizational Structure

  • Communications
    • Data steward relationship management
    • Web site redesign for usability
    • Roadshow to support new and existing data steward to share data sets
    • Promotion of service and service impact
  • Acquisition planning for flexibility and scalability
  • Security planning for non-public web service
  • IT coordination for system assets and capital planning
  • Data Quality
    • Data.gov metadata
    • Old, unupdated data sets - Can they be refreshed or replaced?
    • Incorrect data sets - wrong metadata
    • Missing
  • Onboarding
    • Federal Register analysis for potential data sets
    • Identifying high impact, high use data sets
  • Evaluation
  • Project Management

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