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Data Provenance Community Meeting
September 11th, 2014
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Meeting Etiquette
Click on the “chat” bubble at the top of the meeting window to
send a chat.
• Please mute your phone when you are not speaking to prevent background noise.– All meetings are recorded.
• Please do not put your phone on hold. – Hang up and dial back in to prevent hold
music.• Please announce your name before
speaking• Use the “Chat” feature to ask questions or
share comments.– Send chats to “All Participants” so they
can be addressed publicly in the chat, or discussed in the meeting (as appropriate).
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Agenda
Topic Time Allotted
General Announcements 3 minutesData Provenance Initiative Overview 10 minutes Use Case Discussion 45 minutesNext Steps/Questions 2 minutes
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Thursday, September 18th meeting is cancelled due to HL7 Meetings
Next meeting:• Extended All Hands: Thursday September 25th, 2014 – 2:30-
4:00 pm ET• http://wiki.siframework.org/Data+Provenance+Initiative
• All meeting materials (including this presentation) can be found on the Past Meetings page:• http://wiki.siframework.org/Data+Provenance+Past+Meetings
General Announcements
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Review your status
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S&I Framework Phases outlined for Data Provenance
Phase Planned Activities Pre-Discovery Development of Initiative Synopsis
Development of Initiative Charter Definition of Goals & Initiative Outcomes
Discovery Creation/Validation of Use Cases, User Stories & Functional Requirements Identification of interoperability gaps, barriers, obstacles and costs Review of Candidate Standards
Implementation Creation of aligned specification Documentation of relevant specifications and reference implementations
such as guides, design documents, etc. Development of testing tools and reference implementation tools
Pilot Validation of aligned specifications, testing tools, and reference implementation tools
Revision of documentation and toolsEvaluation Measurement of initiative success against goals and outcomes
Identification of best practices and lessons learned from pilots for wider scale deployment
Identification of hard and soft policy tools that could be considered for wider scale deployments
We are Here
S&I Data Provenance InitiativePresentation to the HITSC on Data Provenance
September 10, 2014
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Why do we need data provenance standards?
• Health care providers need confidence in the authenticity and integrity of health data they review/access/receive.
• Ever expanding role for individuals to contribute data toward their health and care through the use of health IT.
• Trends away from documents and toward “atomizing” data.
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• While there are several existing efforts to address data provenance, no authoritative specification, standard, or model for provenance has been universally adopted to-date, within the context of HIT.
• The variability in how HIEs, EHRs, and PHRs currently capture, retain, and display provenance is problematic for the interoperable exchange, integration, and interpretation of health data.
Challenge
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• To establish a standardized way for capturing, retaining, and exchanging the provenance of health information.
• What will the community create?– Technical specifications to standardize data provenance:
• At creation (i.e., point of origin);• When its exchanged; and • When data is integrated across multiple health
information systems. – Guidance for handling data provenance in content
standards, including the level to which provenance should be applied.
– Establish the minimum set of provenance data elements and vocabulary.
Initiative Purpose and Goals
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• The scope of Data Provenance is broad and there are differing perspectives surrounding priorities and expectations for provenance capabilities.
• For Phase 1, we will tackle the following challenges:(1) When healthcare data is first created, what is the provenance information
that should be created and persisted? (2) Can a receiving system understand and trust that provenance information?(3) Do we need to know who touched it along the way?(4) When the receiving system combines this information with data received
from a third party, how do we persist the provenance from multiple sources?(5) When multi-sourced data is assembled and sent to another system, how do
we convey the provenance of the multiple data sources as well as for the system doing the assembly?
– Is this considered new data?– What if the assembling system “cherry picks” from multiple sources,
or adds some new health information of its own?
Data Provenance – Phase 1
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Pre-step : Creation of the data and associated provenance information
Initiative Activities:Use Case Scenarios (DRAFT)
(1) When healthcare data is first created, what is the provenance information that should be created and persisted?
Data Source A(e.g. Medical
Device, Lab, PHR, EHR, etc.)
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Pre-step : Creation of the data and associated provenance information
Initiative Activities:Use Case Scenarios (DRAFT)
(1) When healthcare data is first created, what is the provenance information that should be created and persisted?
(2) Can a receiving system understand and trust that provenance information?
Data Source A(e.g. Medical
Device, Lab, PHR, EHR, etc.)
End Point (e.g. EHR, PHR)
Data From Source A
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Pre-step : Creation of the data and associated provenance information
Initiative Activities:Use Case Scenarios (DRAFT)
(1) When healthcare data is first created, what is the provenance information that should be created and persisted?
(2) Can a receiving system understand and trust that provenance information?
(3) Do we need to know who touched it along the way?
Transmitter ONLY(HIE, other systems)
End Point (e.g. EHR, PHR)
Data From Source A
Data Source A(e.g. Medical
Device, Lab, PHR, EHR, etc.)
End Point (e.g. EHR, PHR)
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Data Source with pre-existing data
(e.g. EHR)
Pre-step : Creation of the data and associated provenance information
Initiative Activities:Use Case Scenarios (DRAFT)
Data Source A(e.g. Medical
Device, Lab, PHR, EHR, etc.)
(1) When healthcare data is first created, what is the provenance information that should be created and persisted?
(2) Can a receiving system understand and trust that provenance information?
(3) Do we need to know who touched it along the way?(4) When the receiving system combines this information
with data received from a third party, how do we persist the provenance from multiple sources?
Transmitter ONLY(HIE, other systems)
Data Source B(e.g. Medical
Device, Lab, PHR, EHR, etc.)
Transmitter ONLY(HIE, other systems)
Data From Source A
Data From Source B
End Point Start Point = Source C
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Pre-step : Creation of the data and associated provenance information
Initiative Activities:Use Case Scenarios (DRAFT)
(1) When healthcare data is first created, what is the provenance information that should be created and persisted?
(2) Can a receiving system understand and trust that provenance information?
(3) Do we need to know who touched it along the way?(4) When the receiving system combines this information with data
received from a third party, how do we persist the provenance from multiple sources?
(5) When multi-sourced data is assembled and sent to another system, how do we convey the provenance of the multiple data sources as well as for the system doing the assembly?
Data From Source A
Data From Source B
End Point
End Point Start Point = Source C
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Pre-step : Creation of the data and associated provenance information
Initiative Activities:Use Case Scenarios (DRAFT)
(1) When healthcare data is first created, what is the provenance information that should be created and persisted?
(2) Can a receiving system understand and trust that provenance information?
(3) Do we need to know who touched it along the way?(4) When the receiving system combines this information with data
received from a third party, how do we persist the provenance from multiple sources?
(5) When multi-sourced data is assembled and sent to another system, how do we convey the provenance of the multiple data sources as well as for the system doing the assembly?
Data From Source A
Data From Source B
End Point
- Is this considered new data?
End Point Start Point = Source C
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Pre-step : Creation of the data and associated provenance information
Initiative Activities:Use Case Scenarios (DRAFT)
(1) When healthcare data is first created, what is the provenance information that should be created and persisted?
(2) Can a receiving system understand and trust that provenance information?
(3) Do we need to know who touched it along the way?(4) When the receiving system combines this information with data
received from a third party, how do we persist the provenance from multiple sources?
(5) When multi-sourced data is assembled and sent to another system, how do we convey the provenance of the multiple data sources as well as for the system doing the assembly?
Data From Source A
Data From Source B
End Point
- Is this considered new data?- What if the assembling system “cherry picks” from multiple sources, or adds some new health information of its own?
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• Achieved Consensus on Charter• Working on Use Cases• Formed Tiger Team and proposed the Data Provenance project in HL7:
– HL7 Implementation Guide for CDA® Release 2: Data Provenance, Release 1 • Worked with other HL7 workgroups on vocabulary harmonization
Initiative Progress
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Initiative Activities:S&I Framework
Phase Planned Activities Pre-Discovery Development of Initiative Synopsis
Development of Initiative Charter Definition of Goals & Initiative Outcomes
Discovery Creation/Validation of Use Cases, User Stories & Functional Requirements Identification of interoperability gaps, barriers, obstacles and costs Review of Candidate Standards
Implementation Creation of aligned specification Documentation of relevant specifications and reference implementations
such as guides, design documents, etc. Development of testing tools and reference implementation tools
Pilot Validation of aligned specifications, testing tools, and reference implementation tools
Revision of documentation and toolsEvaluation Measurement of initiative success against goals and outcomes
Identification of best practices and lessons learned from pilots for wider scale deployment
Identification of hard and soft policy tools that could be considered for wider scale deployments
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Data Provenance –Use Case (Discovery)Ahsin Azim
Nisha Maharaja
Presha Patel
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Week Target Date (2014) All Hands WG Meeting Tasks
Review & Comments from Community via Wiki page
due following Tuesday by 8 P.M. Eastern
10 8/21Review: Scenario #1 and #2 Functional Requirements and Sequence DiagramsIntroduce: Scenario #3 Functional Requirements and Sequence Diagrams
Review Scenario #3 Functional Requirements and Sequence Diagrams
11 8/28Review :Scenario #3 Functional Requirements and Sequence DiagramsIntroduce: Dataset Requirements
Review Dataset Requirements
12 9/4 Review Dataset Requirements and Risks/Issues Review Data Set Requirements and Risks And Issues
13 9/11 Review Risks/IssuesBegin End to End Review End to End Review
14 9/25 End-to-End Comments Review & dispositionBegin Consensus Begin casting consensus vote
15 10/2 Address Consensus comments, if any
Proposed Use Case & Functional Requirements Development Timeline
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Agenda
Topic Time Allotted
General Announcements 10 minutes
Use Case Discussion
Discuss Timeline/Progress to Date 2 minutes
Review Risks and Issues 5 minutes
Comments and Dispositions 32 minutes
Overview of End to End Review 10 minutes
Next Steps 1 minutes
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Progress to DateUse Case Sections Status
In Scope
Out of Scope
Assumptions
Context Diagram
User Stories
Pre Conditions
Post Conditions
Actors & Roles
Activity Diagrams
Base Flows
Functional Requirements
Sequence Diagrams
Dataset Requirements
Risks & Issues
= section developed
= section under development(% completed)
= indicatesthere are 3 sections for development (1 for each of the scenarios identified)
Sections for Review
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Today we will be reviewing: 1. Review Risks & Issues2. Comments and
Dispositions3. Begin End to End Review
Double click the icon to open up the Word Document with the sections for review
Sections for Review
•1.0 Preface and Introduction
•2.0 Initiative Overview– 2.1 Initiative Challenge Statement**
•3.0 Use Case Scope– 3.1 Background**– 3.2 In Scope– 3.2 Out of Scope– 3.3 Communities of Interest
(Stakeholders)**
•4.0 Value Statement**
•5.0 Use Case Assumptions
•6.0 Pre-Conditions
•7.0 Post Conditions
•8.0 Actors and Roles
•9.0 Use Case Diagram
Use Case OutlineTailored for each Initiative
•10.0 Scenario: Workflow– 10.1 User Story 1, 2, x, …– 10.2 Activity Diagram
o 10.2.1 Base Flowo 10.2.2 Alternate Flow (if needed)
– 10.3 Functional Requirementso 10.3.1 Information Interchange Requirementso 10.3.2 System Requirements
– 10.4 Sequence Diagram
•11.0 Dataset Requirements
•12.0 Risks, Issues and Obstacles
•Appendices
– References
** Leverage content from Charter26
End to End Review of Use Case
• We are kicking off the “End to End” review process– Starts September 11th and goes through 8pm ET
September 18th
• End to End review is open to all members of the DPROV community– We encourage everyone to review the Use Case and
provide tangible, actionable comments– All comments will be dispositioned and discussed on the
All Hands call September 25th
End to End Review:1. Locate the Use Case and End To
End Review Comment Form: http://wiki.siframework.org/Data+Provenance+End+to+End+Review
2. Review the Posted Use Case
3. Complete the Comment Form4. Submit the Comment Form
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A look ahead: Data Provenance Next Week
• Begin End to End Review– The End to End Review comment period will end on Thursday,
September 18th, 2014 at 8:00 P.M. ET
• The next Data Provenance Community Meeting will be on September 25th, 2014– Note: The September 18th, 2014 meeting is cancelled due to
HL7
• Provide your comments on the bottom of this page http://wiki.siframework.org/Data+Provenance+Use+Cases
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Support Team and QuestionsPlease feel free to reach out to any member of the Data Provenance
Support Team:• Initiative Coordinator: Johnathan Coleman: [email protected] • OCPO Sponsor: Julie Chua: [email protected] • OST Sponsor: Mera Choi: [email protected]• Subject Matter Experts: Kathleen Conner: [email protected] and Bob Yencha:
[email protected] • Support Team:
– Project Management: Jamie Parker: [email protected] – Use Case Development: Presha Patel: [email protected], Ahsin
Azim: [email protected] and Nisha Maharaja: [email protected]
– Harmonization: Rita Torkzadeh: [email protected] – Standards Development Support: Amanda Nash:
[email protected] – Support: Lynette Elliott: [email protected] and Apurva Dharia:
