Sharing Biomedical Research Data. Michael F. Huerta, Ph.D. Associate Director National Library of Medicine, NIH

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1 Sharing Biomedical Research Data Michael F. Huerta, Ph.D. Associate Director National Library of Medicine, NIH

2 Sharing Research Data Benefits of sharing data include: Transparency Reanalysis Integration or reaggregation with other data Provides bases for algorithm development, modeling, etc.

3 Sharing Research Data Benefits of sharing data include: Transparency Reanalysis Integration or reaggregation with other data Provides bases for algorithm development, modeling, etc. Costs of sharing data include funds, time, & effort

4 Sharing Research Data Benefits of sharing data include: Transparency Reanalysis Integration or reaggregation with other data Provides bases for algorithm development, modeling, etc. Costs of sharing data include funds, time, & effort Sharing data is a good thing, but sharing all data is probably not

5 Should the Data Be Shared?

6 Should the Data Be Shared? Considerations in Deciding

7 Should the Data Be Shared? Considerations in Deciding Maturity of the science Exploratory vs well understood science

8 Should the Data Be Shared? Considerations in Deciding Maturity of the science Exploratory vs well understood science Maturity of the means of data collection Via unique vs ubiquitous technology

9 Should the Data Be Shared? Considerations in Deciding Maturity of the science Exploratory vs well understood science Maturity of the means of data collection Via unique vs ubiquitous technology Amount and complexity of the data

10 Should the Data Be Shared? Considerations in Deciding Maturity of the science Exploratory vs well understood science Maturity of the means of data collection Via unique vs ubiquitous technology Amount and complexity of the data Utility of the data To research community To the public

11 Should the Data Be Shared? Considerations in Deciding Maturity of the science Exploratory vs well understood science Maturity of the means of data collection Via unique vs ubiquitous technology Amount and complexity of the data Utility of the data To research community To the public Ethical considerations For example, were human subjects properly consented?

12 Should the Data Be Shared? Considerations in Deciding Maturity of the science Exploratory vs well understood science Maturity of the means of data collection Via unique vs ubiquitous technology Amount and complexity of the data Utility of the data To research community To the public Ethical considerations For example, were human subjects properly consented? Policy considerations For example, conditions set by funders

13 Data Sharing Plan Key Elements Important Questions to Address What is the purpose or goal of sharing the data? What data will be shared? Who will have access to the data? Where will the data be located? When will the data be shared? How will researchers locate and access the data?

14 Data Sharing Plan Key Elements Important Questions to Address What is the purpose or goal of sharing the data? Answer to this question determines regime, e.g.: Allow aggregation across studies, labs, etc. Requires standards, protocols, enforcement, etc. Must be adopted by community Provide deeper understanding of a paper Requires explicit description of data, analytics, etc. Can be idiosyncratic

15 Data Sharing Plan Key Elements Important Questions to Address What data will be shared? Domain type (e.g., genetic, behavioral) File type (e.g., numeric, image) Format type QA, QC methods Raw and/or processed Individual and/or summary Vocabularies, other standards Metadata, descriptors, documentation

16 Data Sharing Plan Key Elements Important Questions to Address Who will have access to the data? Public at-large Research community More restricted (due to law or regulation)

17 Data Sharing Plan Key Elements Important Questions to Address Who will have access to the data? Public at-large Research community More restricted (due to law or regulation) Where will the data be located? Existing database New database Maintenance and support

18 Data Sharing Plan Key Elements Important Questions to Address When will the data be shared? With respect to collection With respect to publication Incremental release for longitudinal study

19 Data Sharing Plan Key Elements Important Questions to Address When will the data be shared? With respect to collection With respect to publication Incremental release for longitudinal study How will researchers locate and access the data? Availability announced via registry, publication, etc. Technical protocol Administrative protocol

20 NIH Data Sharing: Success Stories Data Resources

21 NIH Data Sharing: Success Stories Data Resources National Library of Medicine Genbank dbgap (Database of Genotype and Phenotype) PubChem ClinicalTrials.gov

22 NIH Data Sharing: Success Stories Data Resources National Library of Medicine Genbank dbgap (Database of Genotype and Phenotype) PubChem ClinicalTrials.gov NIH Blueprint for Neuroscience Research NITRC (neuroimaging informatics tools & data) NIF (access to neuroscience databases) Human Connectome Project (brain connectivity)

23 NIH Data Sharing: Success Stories Data Resources National Library of Medicine Genbank dbgap (Database of Genotype and Phenotype) PubChem ClinicalTrials.gov NIH Blueprint for Neuroscience Research NITRC (neuroimaging informatics tools & data) NIF (access to neuroscience databases) Human Connectome Project (brain connectivity) NIH National Database for Autism Research All autism research data from human subjects Federated with other public & private data resources