data provenance community meeting september 4 th, 2014
TRANSCRIPT
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Agenda
Topic Time Allotted
General Announcements 2 minutesUse Case Discussion 57 minutesNext Steps/Questions 1 minute
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Next meeting:• All Hands: Thursday September 11th, 2014 – 2:30-3:30 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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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
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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 Finalize Data Set Requirements and Risks/IssuesBegin End to End Review Review Risks/Issues
14 9/25 End-to-End Comments Review & disposition End-to-End Review ends
15 10/2 Finalize End-to-End Review Comments & Begin Consensus Begin casting consensus vote
Proposed Use Case & Functional Requirements Development Timeline
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Agenda
Topic Time Allotted
General Announcements 2 minutes
Use Case Discussion
Discuss Timeline/Progress to Date 2 minutes
Comments and Dispositions 15 minutes
Review Dataset Requirements 30 minutes
Introduce Risks and Issues 10 minutes
Next Steps 1 minutes
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Progress to Date
Use 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
= 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 Functional
Requirements and Sequence Diagram(s) for Scenarios 1, 2, and 3
2. Introduce Dataset Requirements
Double click the icon to open up the Word Document with the sections for review
Sections For Review
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Discussion Points/Comments
• Attest: In or Out of Scope?• Note: Attest is an important aspect, but not in scope
for this phase. Attestation is some something that could consider in next phase.
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Modifications to Data Source
• Modification of Data Source -> Start Point• Start Point (Data Source) - A role played by a system
that creates data (acting as the true source)• End Point - A role played by a system that creates data
(acting as the true source)
• Start point may not be the original source – Start point and end point maybe be points on
workflow that can be carried out by a variety of actors carrying out a variety of roles
Dataset Requirements Discussion
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• For the purposes of this Use Case, the Dataset Requirements will focus on the data elements pertaining to provenance for the clinical data, including the handling of that data, recognizing that it may contain data from multiple sources– Who, When, Where, Type, Routing Information, Integrity/Authenticity, Sources
• In order to capture the provenance data elements, we propose that we discuss the data elements within these categories: Data Source, Transmitter, Assembler, and Composer. We recognize there may be overlap across these categories.
• As a reminder: – The Dataset Requirements define data from a functional standpoint, not from a
technical perspective– We will use this section to figure out to what extent the standards can adhere to the
requirements (not specifications) – The Dataset Requirements for the Use Case are standards agnostic
• The following slides serve as a starter set to begin the discussion and brainstorming of Dataset Requirements; this will eventually be put into a structured format in the Use Case document
Dataset Requirements - Source
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• Who– Sending System; Sending System Organization; Author; Custodian; Role; etc.
• When– Create Date; Create Time; etc.
• Where– Address; State; Zip; etc.
• Type– Software; Device; etc.
Question for Community: What are the important attributes of
provenance that the dataset must contain?
Dataset Requirements - Transmitter
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• Who– Transmitter; Transmitter Organization; etc.
• When– Transmittal Date; Transmittal Time; etc.
• Where– Address; State; Zip; etc.
• Type– Software; Device; etc.
• Routing Information– Information sent to/from
• Integrity/Authenticity– In order to trust the data, do you need to know about how it was handled/who handled it/has
it been altered since it was created????
Dataset Requirements - Assembler
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• Who– Assembler System; Assembler Organization; etc.
• When– Assembly Date, Assembly Time, etc.
• Where– Address; State; Zip; etc.
• Type– Software; Device; etc.
• Integrity/Authenticity– In order to trust the data, do you need to know about how it was handled/who handled it/has
it been altered since it was created????
• Sources– What is the provenance of the information that was assembled????
Dataset Requirements - Composer
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• Who– Composer; Composer Organization; etc.
• When– Composition Date; Composition Time; etc.
• Where– Address; State; Zip; etc.
• Type– Software; Device; etc.
• Integrity/Authenticity– In order to trust the data, do you need to know about how it was handled/who handled it/has
it been altered since it was created????
• Sources– What is the provenance of the information that was assembled????
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A look ahead: Data Provenance Next Week
• September 11th, 2014 – All Hands Community Meeting (2:30-3:30)– Review Risks and Issues
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: