1. Data Fabric Interest Group Plenary 9 Core Session Barcelona

2. Agenda Welcome, Introduction (5 minutes)
Election of new Co-Chair (5 minutes)
Review of Activities (30 minutes)
Global Digital Object Cloud Update (15 minutes)
Discussion/Questions(20 minutes)
Gaps/Opportunities/Next Steps (15 minutes)

3. Co-Chair Election

4. DFIG Current Activities
Ecosystems and Core Components
Recommendations (
Aggregate slide deck (DF IG Documents RDA wiki page)
Common Governance and Operating Procedures
GEDE group
Metadata and PIDs
PID Kernel Subgroup -> PID Kernel WG proposal
Brokering Services
DFIG/Brokering Workflows
Training and Education
DFIG/ETHRD workshop planning session

5. Types of Data Fabrics We can differentiate between
user data fabrics to support discovery and access to published data
collaboration data fabrics that support processing of shared collections
repository data fabrics that are focusing on preserving data
Supported virtualized entities in these DFs are
data collections that include the context of DOs
workflows encapsulating analyses
data flows managing data transport
Essential capabilities are interoperability, federation, interaction control
* Source: Reagan Moore

6. Nature of a Data Fabric
Data Fabrics in the above sense are blueprints to create generic infrastructures that support virtualisation of collections, workflows and data flows
Instantiations of Data Fabrics will offer a set of services some of which are core and others are optional
Data Fabrics are NOT instantiations of a specific collection, workflow or data flow.

7. Defining Core Components
configuration A
configuration B
Task to solve:
Identify and specify Common Components (CoCo)
Recommend CoCo
Put CoCo in place
Not ONE architecture: Identify CoCos that could cooperate in specific configurations to solve a function (infra, VRE, etc.),
Common
Components
& Services
Specific
Components
& Services

8. Identifying Core Components
Core Data Type Definitions, Metadata Standards and Vocabularies
Trustworthy Data Repositories
Trustworthy, Machine-Actionable Registries of
Repositories, Data Types, Metadata Standards, Vocabularies, Authorization Records, Licenses
PID Services
Collection Services
Brokering Services
Common Governance and Operating Procedures
Training and Education

9. From Core Components to Data Fabrics
Configurations must be driven by workflows and use cases
Increasing scale requires moving away from Human Controlled Processing to Type-Triggered Automatic Processing
Component configurations should enable an ecosystem of tools and services

10. Human Controlled Processing (HCP)
Observations
Experiments
Simulations
etc.
Cycle can be manually controlled or semi-automatically via pre-set pipelines.
Even in case of semi-automatic pipelines humans are close-in "designers“

11. some kind of profile matching Researchers are not in direct control
Type-Triggered Automatic Processing (T-TAP)
Data Events
New feature: cycles run highly autonomously - precise steps depend on the types of data entering the workflow
exposing
new DOs
Structured
Data Markets
adding new data
some kind of profile matching
Researchers are not in direct control
Data Federation
Agents
Data Type Registry
Processing services
Brokering & Mediation
services
result
scripts

12. Use Cases
A neurologist wants to research the causal relation between Alzheimer phenomena and specific genes, proteins, neural activity, etc., using machine learning algorithms on confidential data from a federation of hospitals and labs.
A linguist researches theories about „economy of languages“ finding objective patterns that make languages more or less easy to process and learn by applying machine learning algorithms on open data from a variety of sources filtered by languages and feature
The data manager of a large data centre must continuously and asynchronously check the quality of new data of specific types, transform it according to certain rules, and create n replications in a federation

13. Recommendations Update
PID Focus Area work is progressing
GEDE Europe ( was highly active with f2f and virtual meetings
Result is a new report: Grouped List of Assertions (also uploaded to DFIG pages)
consultation of in total 25 reports and papers suggested by participants
extraction of <60 assertions from all documents
then classification of these assertions into sections (1. nature of PIDs and PID systems, 2. their relevance, 3. assigning PIDs, 4. using PIDs, 5. Handles and DOIs, 6. others)
much agreement in core assertions
some variety in way of assigning and using PIDs

14. Areas of discussion
PID in binding role, which type of attribute to add to PID record or to landing page
type of attributes need to be machine readable and specified
how to indicate versions
time of assignment of PIDs
granularity of PID assignment
role of repositories (trustworthy) in assigning
use of fragment indicators
how to add life cycle statements (deletion, splitting, merging, etc.)
when Handles and when DOIs

15. Next Steps
broad commenting on summary assertions by RDA/DFIG and GEDE people within April 17 via web pages and P9 sessions
virtual meeting in May (DFIG and GEDE groups)
f2f meeting in June/July to finish the main summary assertions
afterwards a final report on agreements and identifying areas of disagreements
start interacting about next topic area
primary areas of interest could be „repositories“ (tasks, interfaces, data organisation, etc.) and „data processing“ (workflows, type triggered, etc.)

16. PIDs remain central PID Record PID PID CKSM PID PID paths PID Metadata
Rights
data copies
Relations
Provenance

17. PID Kernel Update Worked started in Denver at P8
Working groups met over the last 6 months
Draft profile created
PID Kernel Working Group Case Statement Submitted
Work completes at P11

18. Global Digital Object Cloud (GDOC)
ID: 843… G
(object:publication)
Identifier Service
Identifier Service
ID: 987/…
Repo/Registry
Repo/Registry
Repo/Registry
Identifier Service
Repo/Registry
Repo/Registry
(object:dataset)
ID: 123…
ID: 876… A
ID: XZY…
ID: HGY…
(object:collection)
End users, developers, and automated processes
deal with persistently identified, virtually aggregated digital
objects, including collections
which are overlays on multiple network services
which in turn are
overlays on existing or future information
storage systems.

19. GDOC – Is it Real? Storage – not our problem, but Services
Latency is an issue
Changing interfaces can be a problem
Services
Identifier
Common resolution systems
PID Kernel, Profiles
Repo/Registry
Common APIs
Confusion: Repository not equal to Storage
Confusion: Registry is a Repository of metadata objects
Object Level
Common Object Interface must be provided by Repo/Registry
Collections ARE Objects
Clients
Good News / Bad News – web browser remains universal client

20. GDOC – Is it Real?
CONCLUSION: Evolution needed & inevitable; RDA can help drive it
DFIG, Brokering, PID Kernel, Collections, DTR, ….

21. Gaps/Opportunities Further progress on Machine-Actionable Registries
DFT for vocabulary - needs population and use
Have DTR for data types - needs testing and iteration
R3Data for Repositories - need a machine-actionable equivalent
Metadata Catalog - machine actionable catalog is a pending RDA WG
Not sure if anyone is working on Authorization and License registries
Governance and Operating Procedures
Need for this will become critical as soon as test beds and functional ecosystems are available
PIDs
Linked Open Data community needs
Recommendations for workflow vs publication