1. Joint DFIG – PWWG Meeting Amy Nurnberger, Lary Lannom, Peter Wittenburg

2. Agenda 14.00 welcome and goals (Peter)
Breakout 1: Discussion about Guidelines/Recommendations
Breakout 2: configuration building and Minimal PID Types
Breakout 4: DFIG Core Session
Breakout 5: Joint session with Brokering Group
Breakout 7: Joint meeting with Publishing Data Workflows
14.00 welcome and goals (Peter)
14.05 DFIG view on scientific data workflows (Peter)
14.20 PWWG view on scientific data and publishing workflows (Amy)
14.35 comparison, overlap and differences in views (Larry)
14.45 discussion (Larry and Amy)
15.30 end

3. Intentions and Goals
comparing core documents from DFIG and Publishing Workflow IG show that
there is much overlap despite different starting points
there are barriers in culture and terminology
there is some tradition to not talk to each other
RDA is about bridge building
this session is about building a bridge and get together
need to understand how we can integrate the approaches since we address overlapping issues
how to do this -> discussion

4. DFIG view on scientific data workflows
Peter

5. Lab Reality – slowly changing
EU survey: 75% of researcher’s time spent on DM/A
M. Brodie (MIT): 80 %
something is fundamentally wrong !!
far away from data publication considerations
are curiosity driven
research and chaos
twins?
is DIS different?
clear trends for all: data orientation, more and complex data
Automatic workflows would change, but
many exceptions, parameter choices, human interventions
lack of experts to create flexible software solutions
how can we help and change?
short term and long term solutions

6. An illustration Feature Sets Collection X Pattern Extractor CollectionY
Smart
Machine
Pattern
Extractor
Collection Z
Results
Iterations

7. An illustration Still lot of handwork, ad hoc scripting involved.
Feature
Sets
Collection X
Still lot of handwork, ad hoc scripting involved.
Also many iterations to find out optimal features.
It is not obvious whether evidences will be found.
Such research takes years.
When to register what?
When to refer to what?
When to create metadata for what?
When to publish and cite what?
Which components would improve?
Pattern
Extractor
Collection Y
Smart
Machine
Pattern
Extractor
Collection Z

8. Identify components that could improve (stepwise).
Data Fabric Cycle
Observations
Experiments
Simulations
etc.
This slide indicated the continuous cycle of creating raw data or derived data based on collections of existing data.
Identify components that could improve (stepwise).

9. From abstract fabrics to concrete compositions
Common
Components
& Services
Specific
Components
& Services
Closing
urgent gaps
t-repositories
PID system
MD schemas
MD editors
vocabularies
etc.
Global Digital Object Cloud

10. From abstract fabrics to concrete compositions
Common
Components
& Services
Specific
Components
& Services
Of course it would be useful to consider publication requirements while building these compositions.
Closing
urgent gaps
t-repositories
PID system
MD schemas
MD editors
vocabularies
etc.
Global Digital Object Cloud

11. Conclusions Collecting use cases and facts from many labs.
Understand from heterogeneous practices how to come to agreed components.
Addressing the data cycle in the labs where publication is often not an issue for quite some time.
However the requirements for data management, accessibility and publication are getting tighter.
So need to consider these requirements and map them with publication requirements.
Need to provide easy transitions.
Thus bridge conceptualisation & terminology.
Need to overcome social barriers.

12. RDA/WDS Data Publishing Workflows WG + Amy Nurnberger

13. DPWWG – Where we’ve been
What are the current data publishing workflow landscape across disciplines and institutions?

14. Data publishing entities
25 data publishing entities assessed in terms of discipline, function, data formats, and roles
The assignment of persistent identifiers (PIDs) to datasets, and the PID type used -- e.g. DOI, ARK, etc.
Peer review of data (e.g. by researcher and by editorial review)
Curatorial review of metadata (e.g. by institutional or subject repository)
Technical review and checks (e.g. for data integrity at repository/data centre on ingest)
Discoverability: was there indexing of the data, and if so, where?
Links to additional data products (data paper; review; other journal articles) or “stand-alone” product
Links to grant information, where relevant, and usage of author PIDs
Facilitation of data citation
Reference to a data life cycle model
Standards compliance

15. Key components of data publishing
Austin, C. C., Bloom, T., Dallmeier-Tiessen, S., Khodiyar, V., Murphy, F., Nurnberger, A., … Whyte, A. (2016). Key components of data publishing: using current best practices to develop a reference model for data publishing.

16. Workflows
Ibid

17. Workflows, cont.
Ibid

18. +
What’s missing?

19. What’s missing?
This stuff

20. What’s missing? This stuff
“…early interactions between researchers and a suitable data repository (or repositories), while data is processed and prepared for sharing.”
Dallmeier-Tiessen, S., Khodiyar, V., Murphy, F., Nurnberger, A., Raymond, L., Whyte, A. (DRAFT). Connecting data publication to the research workflow: a preliminary analysis

21. What’s missing?
Deliberate integration of sundry products from research process, e.g., software, code, models, etc.
Integration/Interoperability between data processing tools an platforms
Disciplinary difference in data conception, collection, & processing
Dallmeier-Tiessen, S., Khodiyar, V., Murphy, F., Nurnberger, A., Raymond, L., Whyte, A. (DRAFT). Connecting data publication to the research workflow: a preliminary analysis

22. What’s needed
Small, modular, shareable components that help ensure platforms offer sufficient flexibility to support variety,
Research workflow solutions that enable straightforward data and metadata generation in accordance with community defined and accepted standards
Commit to the use of PIDs and include versioning capabilities
Clear documentation that can offer direct benefits to repository depositors and users
Curators
Dallmeier-Tiessen, S., Khodiyar, V., Murphy, F., Nurnberger, A., Raymond, L., Whyte, A. (DRAFT). Connecting data publication to the research workflow: a preliminary analysis