The NIH Data Commons - BD2K All Hands Meeting 2015
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Presentation given at the BD2K All Hands meeting in Bethesda, MD, USA in November 2015 https://datascience.nih.gov/bd2k/events/NOV2015-AllHands Video cast of this presentation: http://videocast.nih.gov/summary.asp?Live=17480&bhcp=1 talk starts at 2hrs 40min (its about 55mins long) - includes video! Document describing the Commons : https://datascience.nih.gov/commons
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The NIH Data Commons - BD2K All Hands Meeting 2015
- 1. The Commons Vivien Bonazzi ADDS Office (OD) George Komatsoulis (NCBI) BD2K AHM - Nov 12, 2015
- 2. Why do we need a Commons?
- 8. What are the PRINCIPLES of The Commons? Supports a digital biomedical ecosystem Treats products of research – data, software, methods, papers etc. as digital research objects Digital research objects exist in a shared virtual space Find, Deposit, Manage, Share and Reuse data, software, metadata and workflows Digital objects need to conform to FAIR principles: Findable Accessible (and usable) Interoperable Reusable
- 9. What is The Commons Framework:? Exploits new scalable computing technologies - Cloud Provides physical or logical access to data Simplifies access, sharing and interoperability of digital research objects such as data, software, metadata and workflows Makes digital research objects indexable and findable: FAIR Provides understanding and accounting of usage patterns Is potentially more cost effective given digital growth Gives currency to digital objects and the people who develop and support them
- 10. The Commons Framework Compute Platform: Cloud or HPC Services: APIs, Containers, Indexing, Software: Services & Tools scientific analysis tools/workflows Data “Reference” Data Sets User defined data DigitalObjectCompliance App store/User Interface
- 11. The Commons Framework Compute Platform: Cloud or HPC Services: APIs, Containers, Indexing, Software: Services & Tools scientific analysis tools/workflows Data “Reference” Data Sets User defined data DigitalObjectCompliance App store/User Interface IaaS PaaS SaaS
- 12. Commons: Digital Object Compliance Attributes of digital research objects in the Commons Initial Phase Unique digital object identifiers of resolvable to original authoritative source Machine readable A minimal set of searchable metadata Physically available in a cloud based Commons provider Clear access rules (especially important for human subjects data) An entry (with metadata) in one or more indices Future Phases Standard, community based unique digital object identifiers Conform to community approved standard metadata for enhanced searching Digital objects accessible via open standard APIs Are physically and logical available to the commons
- 13. Commons PILOTS
- 14. Commons Pilots - current The Cloud Credits Model Infrastructure building blocks: IaaS: accessing cloud services for NIH grantees Eventual portal for academic and commercial PaaS and SaaS Commons Supplements – Data, analysis tools, APIs, containers BD2K Centers MODs (Model Organism Databases) Interoperability (some) HMP (Human Microbiome Project) NIH Affiliated Commons projects NIAID/CF/ADDS - Microbiome/HMP Cloud Pilot NCI Cloud Pilots & Genomic Data Commons
- 15. Cloud credits model (CCM) Compute Platform: Cloud or HPC Services: APIs, Containers, Indexing, Software: Services & Tools scientific analysis tools/workflows Data “Reference” Data Sets User defined data DigitalObjectCompliance App store/User Interface Mapping pilots to the Commons framework: Cloud Credits Model: George Komatsoulis IaaS PaaS SaaS
- 16. Drivers of the Cloud Credits Model Scalability Exploiting new computing models Cost Effectiveness Simplified sharing of digital objects FAIR: Findable, Accessible, Interoperable and Reusable Cloud computing supports many of these objectives
- 17. The Cloud Credits Model The Commons Cloud Provider A Cloud Provider B Investigator NIH Provides credits Enables Search Discovery Index Uses credits in the Commons IndexesOption: Direct Funding HPC Provider
- 18. Supports simplified data sharing by driving science into publicly accessible computing environments that still provide for investigator level access control Scalable for the needs of the scientific community for the next 5 years Democratize access to data and computational tools Cost effective Competitive marketplace for biomedical computing services Reduces redundancy Uses resources efficiently Advantages of this Model
- 19. Novelty: Never been tried, so we don’t have data about likelihood of success Cost Models: Assumes stable or declining prices among providers True for the last several years, but we can’t guarantee that it will continue, particularly if there is significant consolidation in industry Service Providers: Assumes that providers are willing to make the investment to become conformant Market research suggests 3-5 providers within 2-3 months of launch Persistence: The model is ‘Pay As You Go’ which means if you stop paying it stops going Giving investigators an unprecedented level of control over what lives (or dies) in the Commons Potential Disadvantages of this Model
- 20. Minimum set of requirements for Business relationships (reseller, investigators) Interfaces (upload, download, manage, compute) Capacity (storage, compute) Networking and Connectivity Information Assurance Authentication and authorization A conformant cloud is not necessarily a provider of Infrastructure as a Service (IaaS) although all providers must provide IaaS What does it mean for a provider to be conformant?
- 21. NIH intends to run a 3 year pilot to test the efficacy of this business model in enhancing data sharing and reducing costs. Pilot will not directly interact with the existing grant system, rather, it is being modeled on the mechanisms being used to gain access to NSF and DOE national resources (HPC, light sources, etc.) The only required qualification for applying for credits will be that the investigator has an existing NIH grant A major element will be the collection of metrics to assess effectiveness of this model Pilot of the Commons Cloud Credits Business Model
- 22. NIH recently completed a contract with the CAMH Federally Funded Research and Development Center (FFRDC) to act as the coordinating center for this effort. We need you to: Identify what capabilities will be useful to investigators Provide guidance on the conformance requirements Help identify good metrics Define the criteria that are used to decide if credit requests are selected Status and requests
- 23. Co-moderated by Victor Jongeneel (UIUC), Valentina di Francesco (NHGRI) & George Komatsoulis (NCBI) FRIDAY 10:45 AM – 12:30 PM Cloud Credits Model Breakout Session Tomorrow!
- 24. BD2K Centers, MODS, HMP & Interoperability Supplements Compute Platform: Cloud or HPC Services: APIs, Containers, Indexing, Software: Services & Tools scientific analysis tools/workflows Data “Reference” Data Sets User defined data DigitalObjectCompliance App store/User Interface Mapping pilots to the Commons framework: BD2K centers, HMP, MODs & Interoperability PaaS SaaS
- 25. Testing the Commons framework Facilitating connectivity, interoperability and access to digital research objects Interoperable (APIs, containers) Digital object compliant: FAIR Indexable Publishable Privacy/security (PHI) Available on cloud platforms Providing digital research objects to populate the Commons Commons Supplements: BD2K Centers, MODs, HMP & Interoperability
- 26. Moderated by Valentina di Francesco (NHGRI) & Vivien Bonazzi (ADDS) FRIDAY 2:00 – 3:30 PM Commons Supplements Program Session Tomorrow!
- 27. NCI & NIAID Cloud Pilots/GDC Compute Platform: Cloud or HPC Services: APIs, Containers, Indexing, Software: Services & Tools scientific analysis tools/workflows Data “Reference” Data Sets User defined data DigitalObjectCompliance App store/User Interface Mapping pilots to the Commons framework: NIAID and NCI Cloud Pilots/GDC : PaaS SaaS IaaS
- 28. Making Human Microbiome Project (HMP) data broadly accessible, computable, and usable. Moving ~20TB of HMP data to AWS Providing access to a suite of tools and APIs to facilitate data access and use Data and tools will follow FAIR principles (digital object compliance) * In collaboration with Owen White (UM) – HMP DCC NAID/CF/ADDS Microbiome* Cloud Pilot HMP data and tools in the AWS cloud
- 29. Making cancer genomics data broadly accessible, computable, and usable by researchers worldwide. Genomic Data Commons (GDC) will store, analyze and distribute ~2.5 PB of cancer genomics data and associated clinical data generated by the TCGA and TARGET (Therapeutically Applicable Research to Generate Effective Treatments) initiatives The NCI cloud pilots will make TCGA data available on the AWS and Google clouds, along with a suite of tools and APIs to facilitate their access and use NCI Cloud pilots and Genomic Data Commons
- 30. THURSDAY 2:00 – 4:00 PM Commons Pilots Poster Session Today!
- 31. Commons Pilots - proposed Indexing and Searching digital research objects in the Commons Leveraging indexing methods within BD2K e.g. BioCADDIE Accessing large, high value commonly used data sets in the cloud E.g 1000 genomes, HMP, modENCODE Co-location of data and computes Digital research objects are FAIR
- 32. BD2K Indexing e.g. BioCADDIE Compute Platform: Cloud or HPC Services: APIs, Containers, Indexing, Software: Services & Tools scientific analysis tools/workflows Data “Reference” Data Sets User defined data DigitalObjectCompliance App store/User Interface Mapping proposed pilots to the Commons framework : Indexing & Large Data Sets NIH + Community defined data sets
- 33. Commons Pilots - proposed Indexing and Searching digital research objects in the Commons Leveraging indexing methods within BD2K e.g. BioCADDIE Accessing large, high value commonly used data sets in the cloud E.g 1000 genomes, HMP, modENCODE Co-location of data and computes Digital research objects are FAIR
- 34. Thankyou ADDS Office Phil Bourne, Michelle Dunn, Jennie Larkin, Mark Guyer, Sonynka Ngosso NCBI: George Komatsoulis NHGRI: Valentina di Francesco, Kevin Lee CIT: Debbie Sinmao, Andrea Norris, Stacy Charland Trans NIH BD2K Executive Committee & Working groups NCI: Warren Kibbe, Tony Kerlavage, Lou Staudt, Tanja Davidsen NIAID: Nick Weber, Darrell Hurt, Maria Giovanni, JJ McGowan Many biomedical researchers, cloud providers, IT professionals
- 35. QUESTIONS? Come to the poster session!
Notas del editor
- There is not enough funding for every researcher to house all the data they need Analyzing the data is more expensive than producing it It can take weeks to download large datasets
- Mimimum Requirements: Business relationship is to allow distribution and billing of credits and to ensure that liability issues are resolved. Investigator that puts digital object in the commons is the one that retains the liability associated with its use. Interfaces – would need to be open, but not necessarily open-source. Requires support for basic operations. In addition, environment has to be open to all; so a private environment behind a university firewall won’t work. Identifiers and metadata: Tied together and together enable researchers to search for and find resources. Networking and Connectivity: Make sure that stuff is accessible, require connection to commodity internet and internet2, but key element from investigator point of view is a free egress tier for academics Environment is secure A&A: Must support inCommon because most NIH investigators have it. Minimizes hassle of granting access to collaborators across multiple platforms. Approval of clouds: Self certify vs. NIH certify vs. 3rd party certify. In early test cases, may simply say ‘FedRamped’ Cloud vs IaaS: Some IaaS (AWS comes to mind) may be uninterested in providing the ‘conformant’ layer but support other companies that provide these services using AWS backend. Already exemplars of this: Seven Bridges Genomics and the Cancer Genomics Cloud Pilots are all software layers over an IaaS provider.