[Rainer Stotzka]

Collaborative session notes: https://docs.google.com/document/d/1QwOeRHJsZ-GTq1KvPAS8yQn3iM6a7J76MPCErlwqR1U/edit?usp=sharing
 

Short introduction IG Data Fabric (5m) [Rainer Stotzka]
High Level Views on FDO (10m) [Christine Kilpatrick]
Up to 7 teasers (3-5m each) and discussions

FDO Use Case from Earth System Science [Ivonne Anders]
Computational Workflows as FAIR Digital Objects using RO-Crate [Stian Soiland-Reyes] 
FAIR Digital Objects in Materials Science and Engineering [Rossella Aversa, Zachary Trautt]
CAS Data Infrastructure [Xin Chen]
RPID [Rob Quick] 
A Concept towards a FAIR Photovoltaic System [Jan Schweikert]
Applying the FAIR DO Concept to a Humanities Use Case [Andreas Pfeil]

Collection of “other amazing super-duper application ideas”
Summarizing results, defining next steps (10m)

Additional links to informative material
European Commission (2018b). Turning FAIR into reality. Final report and action plan from the European Commission expert group on FAIR data. Luxembourg: European Commission. https://doi.org/10.2777/1524
RDA DFT Group: DFT Core Terms and Model; http://hdl.handle.net/11304/5d760a3e-991d-11e5-9bb4-2b0aad496318 
RDA DTR Group: Data Type Registry¸ https://www.rd-alliance.org/group/data-type-registries-wg/outcomes/data-type-registries
RDA PID Kernel Information Working Group: Recommendation on PID Kernel Information; https://www.rd-alliance.org/group/pid-kernel-information-wg/outcomes/recommendation-pid-kernel-information
IG Data Fabric:
https://www.rd-alliance.org/group/data-fabric-ig.html
https://www.rd-alliance.org/group/data-fabric-ig/wiki/rda-ig-data-fabric-fair-digital-objects
Collection of information about FAIR Digital Objects:  
FAIR DO Publications ((https://www.zotero.org/groups/2517421/fair_digital_objects/library )
FAIR DO: RDA Recommendations & Outputs
Project shares:
https://www.rd-alliance.org/group/data-fabric-ig/wiki/monthly-meetings 
 

Applicable Pathways
The FAIR Agenda, Other

Avoid conflict with the following group (1)
Research Data Management in Engineering IG

Brief introduction describing the activities and scope of the group
The Data Fabric IG (DFIG) identified that working with data in the many scientific labs and most probably also in other areas such as industry and governance is highly inefficient and too costly. Excellent scientists working on data-intensive science tasks are forced to spend about 75% of their time to manage, find, combine and curate data. What a waste of time and capacity. The DFIG is therefore looking at the data creation and consumption cycle to identify opportunities to optimize the work with data, to place current RDA activities in the overall landscape, to look at what other communities are doing in this area, and to foster testing and adoption of RDA outputs. The goal of DFIG finally is to identify common components and define their characteristics and services that can be used across boundaries in such a way that they can be combined to solve a variety of data scenarios such as replicating data in federations, developing virtual research environments, and automating regular data management tasks. Much important work is being done on data publishing and citation, but DFIG believes that we need to start at early moments in the “Data Fabrics” in the labs to organize, document, and manage data professionally if we want to meet the requirements of the coming decades.
 

Group chair serving as contact person
Rainer Stotzka

If “Other,” Please specify:
Data citation, machine actionability

Meeting presenters
Lori Chen, Rob Quick, Rainer Stotzka, + many others

Please indicate the breakout slot (s) that would suit your meeting
Breakout 1, Breakout 2, Breakout 7, Breakout 8, Breakout 10, Breakout 11, Breakout 13, Breakout 14

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