1. NutriGen Data Requests Discovery to Delivery

2. Data discovery tools Now Future  NutriGen Dictionary  Cohort-specific schema  Your friendly neighbourhood data manager  NutriGen Dictionary  Cohort-specific schema  Your friendly neighbourhood data manager  Online variable database  Searchable by topic/subject, time point, participant type  Variable recommendation

3. Dictionary

4. Dictionary (cont’d)

5. Data request to receipt 1. You create data request, get it approved 2. I receive approved data request 3. Determine necessary variables using dictionary and own knowledge of cohorts 4. If needed, request data from cohorts 5. Assemble requested (harmonized) data into.csv or excel file 6. Put file in respective folder on server for analysis and communicate completion of request 7. File data request

6. Data requests  WHEN: Time point(s)  WHO/WHERE: Cohort(s) in question  WHO: Participant type(s)  WHAT: Subject – as detailed as possible  “Do you have allergy data?”  “Do you have data on if the child has any food allergies by 1 year?”

7. Request format Now: Paper Future: Online  Researcher comes in or is sent a request by email  Receive approved request in hand  File with rest of researcher’s requests  Sign confidentiality agreement with every request  Request link sent to researcher  Receive approved request via email  Update data request database with latest request  Sign confidentiality agreement for initial request, carries over to future requests

8. Developing harmonization algorithms  See what is available in each cohort  Research what the experts consider relevant or important  Compare data, balancing detail and number of participants

9. Harmonized Definition everbfed1y: Infant was breastfed at least once by 1 year. Data type = Yes/No  ABC: If breastfeeding=1 or 3 or everbfed6m=yes, then yes. Else if breastfeeding=2, then no. Else “”  CHILD: If NUTR1YQ4=0, then no. Else if NUTR1Y<89 or everbfed6m=yes, then yes. Else “”  FAMILY: If everbfed6m=yes, then yes. Else “”  START: If inbfed=1 or 2 or everbfed6m=yes or any of y1bmilk0to14=1, then yes. Else if inbfed=2 or all of y1bmilk0to14=0, then no. Else “”

10. Computing harmonized variables Now: csv and excel files Future: online data portal  Harmonization algorithms recorded  Data stored in static tables  Harmonizations computed when processing request  Harmonization algorithms stored  Data stored in regularly updated database  Data harmonized “on the fly” when data is accessed

11. Data Storage and Access  Data stored on secure PGPstore server  Data remains on server before, during, and after analysis

12. Accessing and analysing data Now: static.csv and excel files Future: online data portal  Data accessed via secure folder on server  Analysis completed on file of requested data using own tools  Data accessed via secure intranet site  Researchers gain access to requested data and analysis tools available on portal