Thursday, 2:50 - 5:30
In this session, we will, through smaller group discussions, dive into some more specific questions of how the NDS addresses particular parts of the challenge. The goals of the break-outs are
- to identify the most important problems that will need to be addressed when building and or operating the NDS
- to identify key requirements or considerations when addressing these problems
- to identify existing tools, technologies, or development efforts that we think will be important to addressing these problems
- to identify any obvious holes in the technology space
- to identify those problems that can be easily tackled first
More info below
Schedule
Start | Duration | |
---|---|---|
2:50pm | Charge to Break-outs | 10 min |
3:00 | Break | |
3:30 | Break-outs discussions | 90 min |
5:00 | Lightning Reports: 5 minutes per break-out group | 30 min |
5:30 | Adjourn |
Process
- Pick a topic that matches your interest
- As a group, please identify 2 note takers
- Consider the questions below for your topic, or generate your own as appropriate
- Take the last 20-30 minutes of the discussion session to prepare a 5 minute report; identify a presenter
- Email your presentation and any additional notes to info@nationaldataservice.org
Topics
Organizing the Consortium
Questions to consider:
- What does it mean to be a member of the Consortium?
- What kind of structure is desired? necessary? (e.g. highly structured vs. loose)
- What are some key/required components of the Charter?
- Should a Charter come out quickly or do we need to take our time? Phases?
Discovery: Connecting mechanisms together
Questions to consider:
- How do we handle cross-disciplinary discovery
- How do we leverage community/discipline-specific tools/mechanisms
- Massive harvesting to a central index, vs.
- Live searches of community-specific tools, vs.
- Hybrid
- Where do community-specific metadata come in?
- How important (and where) are cross-discipline metadata standards? Are translators/semantic mappers important?
- How can the user smoothly transition into discipline specific tools
- How do we leverage community/discipline-specific tools/mechanisms
- Big results problem / Browsing problem: will new strategies be needed?
- Search granularity?
Repositories: technologies and federation
Questions to consider:
- What are the different classes of repositories that need to be integrated?
- preservation vs. access
- limited-lived data?
- dark data?
- What are some of the key APIs (generally)
- Who will be running repositories?
- What are the modes for funding repositories
Publishing: IDs, the publishing process, role of publishers, tools
Questions to consider:
- How does the research and publishing process need to evolve to incorporate data
- What are the key requirements (from publishers?) needed to preserve the quality of publications?
- Should we be able to cite data products just like literature? Data citation statistics?
- What are the key standards that need to be incorporated into the data publishing process?
- What tools are necessary to help authors prepare data for publication? How important are discipline-specific features (e.g. metadata)?