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WP2 introduction

Stimulate FAIR and reusable research

WP2 leader: UNIMAN

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This work is licensed under a �Creative Commons Attribution 4.0 International License.�Cite as: https://doi.org/10.5281/zenodo.7152762

2022-10-06 by Stian Soiland-Reyes, Carole Goble�EuroScienceGateway kickoff, Freiburg

Grant agreement 101057388

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WP2 Objectives

O2.1 Bringing FAIR workflows into EOSC through the EuroScienceGateway

O2.2 Support reusable and reproducible workflows

O2.3 Establish FAIR Digital Objects as citable exchange format for workflows for all EOSC services

O2.4 Establish FAIR Workflow Digital Objects as publishable scholarly objects

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Motivation & background

How to implement FAIR principles for software and workflows?
WorkflowHub and the EOSC-Life ecosystem
Research Objects
FAIR Digital Objects (FDO)
RO-Crate

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Annual reminder:�FAIR principles for sharing data

To be Findable:

F1. (meta)data are assigned a globally unique and persistent identifier

F2. data are described with rich metadata (defined by R1 below)

F3. metadata clearly and explicitly include the identifier of the data it describes

F4. (meta)data are registered or indexed in a searchable resource

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To be Accessible:

A1. (meta)data are retrievable by their identifier using a standardized communications protocol

A1.1 the protocol is open, free, and universally implementable

A1.2 the protocol allows for an authentication and authorization procedure, where necessary

A2. metadata are accessible, even when the data are no longer available

To be Interoperable:

I1. (meta)data use a formal, accessible, shared, and broadly applicable language for knowledge representation.

I2. (meta)data use vocabularies that follow FAIR principles

I3. (meta)data include qualified references to other (meta)data

To be Reusable:

R1. meta(data) are richly described with a plurality of accurate and relevant attributes

R1.1. (meta)data are released with a clear and accessible data usage license

R1.2. (meta)data are associated with detailed provenance

R1.3. (meta)data meet domain-relevant community standards

tl;dr: �- make data & metadata available

- use persistent identifiers!�- machine-readable metadata�- use standards

https://doi.org/10.1038/sdata.2016.18

FAIR Tulip by Meznah Aloqalaa

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FAIR for Research Software�(FAIR4RS)

Findable: Software, and its associated metadata, is easy to find for both humans and machines.

F1. Software is assigned a globally unique and persistent identifier

F1.1. Different components of the software are assigned distinct identifiers representing different levels of granularity

F1.2. Different versions of the same software are assigned distinct identifiers

F2. Software is described with rich metadata

F3. Metadata clearly and explicitly include the identifier of the software they describe

F4. Metadata are FAIR and are searchable and indexable

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Accessible: Software, and its metadata, is retrievable via standardized protocols.

A1. Software is retrievable by its identifier using a standardized communications protocol

A1.1. The protocol is open, free, and universally implementable
A1.2. The protocol allows for an authentication and authorization procedure, where necessary

A2. Metadata are accessible, even when the software is no longer available

Interoperable: Software interoperates with other software through exchanging data and/or metadata, and/or through interaction via application programming interfaces (APIs), described through standards.

I1. Software reads, writes and exchanges data in a way that meets domain-relevant community standards

I2. Software includes qualified references to other objects

Reusable: Software is both usable (it can be executed) and reusable (it can be understood, modified, built upon, or incorporated into other software).

R1. Software is described with a plurality of accurate and relevant attributes

R1.1. Software is given a clear and accessible license

R1.2. Software is associated with detailed provenance

R2. Software includes qualified references to other software

R3. Software meets domain-relevant community standards

https://doi.org/10.15497/RDA00068

https://doi.org/10.3233/DS-190026

Software is different from data!

Evolves over time, complexity, dependencies, �source vs binary, open source communities

More challenging to attribute, cite, archive, version

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FAIR Computational Workflows

Can workflows help with FAIR?

Reproducible and Reusable

Explain a computational method

Record detailed provenance of execution

FAIR+ASAP: �Automation, Scalable, Abstraction, Provenance

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https://doi.org/10.1162/dint_a_00033

https://workflows.community/groups/fair/

https://workflowhub.eu/workflows/372

Challenges:

Workflows simplify (but don’t hide) Research Software

Fully capturing workflow as digital objects

Too many workflow systems! (>324) -> interoperability suffers

Requirements by workflow engine (e.g. cloud infrastructure)

Usually not cited – how?

https://www.commonwl.org/

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FAIR Workflow Ecosystem: Hybrid Processual Objects

FAIR Method Object

FAIR Software Objects

FAIR Data

In and Out

FAIR Enabling Services

Carole Goble, Stuart Owen

Defragmentation training school for bioimaging workflows 2022-09-30

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FAIR Workflow registry

Workflow-system agnostic

Search for and discover workflows

Metadata standardization �(CWL, schema.org, custom tags, RO-Crate)

DOI publication, citation & credit

Collections

Teams, Organizations and Communities

Programmatic access: GA4GH TRS API, RO-Crate

Registry, not repository

Workflows can live elsewhere, e.g. GitHub

Integration with execution platforms (incl. usegalaxy.eu)

https://workflowhub.eu/

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EOSC-Life ecosystem

The services in the Workflow Collaboratory exchange digital objects as Workflow RO-Crates

Packaging workflow files & companion objects

Submission / download

Exchange between services & systems

Reproducibility & Testing

Citation

https://doi.org/10.5281/zenodo.4605654

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Using standards for workflow execution provenance

Renske de Wit https://doi.org/10.5281/zenodo.7113250

Simone Leo, Laura Rodríguez-Navas, et al.

https://www.researchobject.org/workflow-run-crate/

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Multiple platforms and repositories

Challenge: Digital Objects are deposited in different

repositories depending on their type and domain

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https://doi.org/10.1016/j.future.2011.08.004

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FAIR Digital Object (FDO) – conceptual view

Predictable implementation of FAIR for active objects – not just static data

PID Profile

Collection

FDO

PID�20.301/a

Metadata

Operation

�Attributes

20.123: “Alice”�20.789: <http://...>

20.456: 10.1234/ab

PID Record

Bytes

FDO

FDO Type

Distributed object architecture
Self-describing digital objects
Several types of metadata
Encapsulation of operations
Machine-actionable

FDO and RO highlighted in �EOSC Interoperability Framework

https://doi.org/10.2777/620649

Note: FDO is conceptual model + specifications�Can be realized with different implementations:

Handle + DOIPv2
URL + Linked Data Platform
DOI + RO-Crate

FAIR Digital Objects for Science: From Data Pieces to Actionable Knowledge Units: https://doi.org/10.3390/publications8020021

https://fairdo.org/

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CRUD
Extensible operations

FAIR Digital Object, conceptually speaking, is a data structure that describes a. A Persistent Identifier (PID) can be looked up to a PID Record, where we find a list of attributes of the FDO. These can be references, the most important one is the type, as that tells us the purpose of the FDO and what attributes to expect.

The PID Profile tells us how conceptual FDOs are realized with particular technologies, for instance using DOIs and a PID record in JSON.

For Data objects there are usually some bytes that can be requested through Operations like the familiar CRUD (Create-Read-Update-Delete), but also

Attributes can reference other FDOs, so you don’t need to squeeze it all into the PID Record but can have separate Metadata in different formats that describe this FDO further.

Now crucially all of these are FDOs, it’s turtles all the way down, so what I just said also apply to types, profiles, metadata and operations, and these are therefore can be distributed and re-used. A Collection is likewise just another FDO that points to the PIDs of other FDOs.

Distributed architecture
Rigid Persistent Identifiers
Self-describing digital objects
Data/metadata abstraction

Several types of metadata

Machine actionable
Encapsulation of operations

Data/metadata abstraction

Several types of metadata

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FAIR RO-Crate as a realization of FDO Research Objects

FAIR Signposting – HTTP headers for PID, metadata, ++

Common types from schema.org

Multiple metadata files incl. JSON-LD, DataCite XML

Domain-specific profiles (e.g. Workflow Crate)

Conforming to existing Community APIs (e.g. GA4GH)

Implementing FDO with current web standards

Updating Linked Data practices for FAIR Digital Object principles

& Creating lightweight FAIR Digital Objects with RO-Crate. �Research Ideas and Outcomes 8:e93937 , 1st Intl Conf on FAIR Digital Objects

PID Profile:�RO-Crate

PID�https://doi.org/...

ro-crate-metadata.json

Operation

HTTP GET

�<…schema.org/dataset>; rel=type

<https://doi…>; rel=cite-as

<…crate.zip>; rel=item�<ro-crat…>; rel=describedby;� profile=…ro-crate

PID Record

zip

FDO Type:

Dataset

FAIR Signposting�https://signposting.org/FAIR/

...

FDO Type:

ComputationalWorkflow

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Now let’s look at how we realize FDO using RO-Crate and the existing Web.

I’m looking now at an FDO in our registry WorkflowHub, so when you resolve the DOI you get a nice HTML landing page. This is what regular users normally expect from identifiers, not some mystic JSON. We’ll keep those under the hood for now.

But to be an FDO we need machine readability, right? So here we use the Web standards.

FAIR Signposting allows a computer program to look up related links, which we in FDO terms can call the PID Record.

This gives the high level FDO aspects we saw before: We have a type, from schema.org and bioschemas

We have the PID itself, a downloadable ZIP, and a metadata file that we can parse.

This is then the PID Profile for RO-Crate, the program can get straight at the download if it so wants, using regular HTTP operations.

But we want to know more! And that is why we use JSON-LD in the RO-Crate Metadata file, where you can extend to your heart’s delight. For instance in this case we can find out it’s a Workflow RO-Crate, a profile of RO-Crate that describes workflows, a Galaxy workflow, some ORCID identifiers of people who contributed.

So here we see that we don’t need to invent new Digital Object protocols to implement FDO, the Web can do it perfectly, as long as we put in the right links for signposting.

Now some of you may be Linked Data experts already and say, hey, we always did this, but with some magic content-negotiation or embedded statements. I don’t want to open that can of worms now, but suffice to say that is very fragile for consumers. Here we have declared explicitly what metadata you can get to which profile – and you can have many of these. In fact in WorkflowHub we also link to Datacite XML as alternative metadata. So that is realization of the FDO principles to allow full predictable machine actionability. Next for us now, in projects like EuroScienceGateway, we will expand the green bits on operations, how to do other active things with the object. We use GA4GH APIs for instance to launch a workflow in UseGalaxy, these operations to “wake up” the object we will also add to the FDO with RO-Crate.

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Structured self-describing, machine readable, metadata objects

RO-Crate Metadata file

Archive file format / packaging system

id

type

description

datePublished

…

license

author

organisation

https://github.com/o/script

files

links to web resources

RO-Crate Content

directories

id

type

description

datePublished

creator

size

format

…

https://doi.org/10.5281/zenodo.5841615

Structured metadata about the RO-Crate and content

https://www.researchobject.org/ro-crate/

https://doi.org/10.3233/DS-210053

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Spec

via Zip, Bagit and OCFL Objects

@type: MUST be Dataset

@id: MUST end with / and SHOULD be the string ./

name: SHOULD identify the dataset to humans well enough to disambiguate it from other RO-Crates

description: SHOULD further elaborate on the name to provide a summary of the context in which the dataset is important.

datePublished: MUST be a string in ISO 8601 date format and SHOULD be specified to at least the precision of a day, MAY be a timestamp down to the millisecond.

license: SHOULD link to a Contextual Entity in the RO-Crate Metadata File with a name and description. MAY have a URI (eg for Creative Commons or Open Source licenses). MAY, if necessary be a textual description of how the RO-Crate may be used.

ro-crate-metadata.json

This document specifies a method, known as RO-Crate (Research Object Crate), of organizing file-based data with associated metadata, using linked data principles, in both human and machine readable formats, with the ability to include additional domain-specific metadata.

The core of RO-Crate is a JSON-LD file, the RO-Crate Metadata File, named ro-crate-metadata.json. This file contains structured metadata about the dataset as a whole (the Root Data Entity) and, optionally, about some or all of its files. This provides a simple way to, for example, assert the authors (e.g. people, organizations) of the RO-Crate or one its files, or to capture more complex provenance for files, such as how they were created using software and equipment.

While providing the formal specification for RO-Crate, this document also aims to be a practical guide for software authors to create tools for generating and consuming research data packages, with explanation by examples.

At the basic level, an RO-Crate is a collection of files and resources represented as a Schema.org Dataset, that together form a meaningful unit for the purposes of communication, citation, distribution, preservation, etc. The RO-Crate Metadata File describes the RO-Crate, and MUST be stored in the RO-Crate Root.

While RO-Crate is well catered for describing a Dataset as files and relevant metadata that are contained by the RO-Crate in the sense of living within the same root directory, RO-Crates can also reference external resources which are stored or accessed separately, via absolute URIs. This is particularly recommended where some resources cannot be co-hosted for practical or legal reasons, or if the RO-Crate itself is primarily web-based.

It is important to note that the RO-Crate Metadata File is not an exhaustive manifest or inventory, that is, it does not necessarily list or describe all files in the package. Rather it is focused on providing sufficient amount of metadata to understand and use the content, and is designed to be compatible with existing and future approaches that do have full inventories / manifest and integrity checks, e.g. by using checksums, such as BagIt and Oxford Common File Layout OCFL Objects.

The intention is that RO-Crates can work well with a variety of archive file formats, e.g. tar, zip, etc., and approaches to capturing file manifests and file fixity, such as BagIt, OCFL and git (see also appendix Combining with other packaging schemes). An RO-Crate can also be hosted on the web or mainly refer to web resources, although extra care to ensure persistence and consistency should be taken for archiving such RO-Crates.

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A little bit of packaging goes a long way

Familiar, developer friendly Lo-Tek – web native, off-the-shelf, machine and human readable, search engine accessible: PIDs + JSON-LD + Schema.org + BagIT/Zip/OCDL.

Infrastructure independent to overcome repository and service silos: Practical, lightweight, robust.

One size does not fit all – embrace diversity, legacy, unknowns – open-ended, multi-interpretation, self-describing. Extensible metadata + pre-existing ontologies: Duck type profiling.

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WP2 Aims

Support FAIR practices for and by workflows.

Realize FAIR Digital Objects (FDOs) as RO-Crates

Exchanging, publishing, archiving and citing workflows and their companion data, provenance logs and associated resources

Publish FDOs in EOSC catalogues (e.g. OpenAIRE)

Mature WorkflowHub to TRL-9 status EOSC service

Promote WorkflowHub as registry of choice for all workflow system types and for all disciplines in EOSC

Reach out to computational researcher communities and publishers

Align with EOSC’s PID and metadata schema frameworks

…in collaboration with FAIR-IMPACT

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Task T2.1: Integration of EuroScienceGateway in EOSC

Integrate workflows in existing EOSC services (Findability, Accessibility)

Use WorkflowHub as workflow registry in ESG & EOSC �→ mature to TRL-9 EOSC service

← Working with WP5 for new user requirements

Catalogue of workflows adhering to best practices (MS3, MS4)

← ..from use cases (WP5) and for training (WP1)

WorkflowHub to integrate execution through EuroScienceGateway (T3.4)

Register in EOSC catalogues/aggregators (e.g. OpenAIRE)

M7-M36: UNIMAN, VIB, BSC, EGI

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Goal: Establish EuroScienceGateway as new EOSC service

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Task T2.2: Reproducible and reusable FAIR Digital Objects

Workflows as first class objects in the �EOSC Interoperability Framework

Harvest metadata from Galaxy and other WMS

Mature RO-Crate Profiles: �Workflow Crate Profile. Workflow Run Profile.

ESG analytics over provenance �→ inform optimisation of meta-scheduling (WP4)

M1-M26: UNIMAN, VIB, EPFL, BSC

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Formalize FAIR Digital Object profile using RO-Crate.

Collaborations: FAIR Digital Object Forum, RDA Data Fabric IG, EOSC Core

Collaborating with FAIR-IMPACT: �PID practices, metadata requirements for citing workflows (T2.4), FAIR Research Software

Goal: Mature FAIR Digital Object RO-Crate approach

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Task T2.3: Using and enriching workflow FDOs

Ensure deposition in long term archives (e.g. Zenodo, Software Heritage)

Use & contribute to EOSC scholarly metadata services �..and scholarly aggregation catalogues (e.g. OpenAIRE)

Include in scholarship Knowledge Graphs (KG) (e.g. OpenAIRE Research Graph, DataCite PID graph).

Make EuroScienceGateways metadata suitable for other EOSC services

M15-M36: UNIMAN, EPFL, UP, UiO

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Figure by Roderic Page�https://doi.org/10.3897/rio.2.e8767�(CC BY 4.0)

Fenner, M., & Aryani, A. (2019). �Introducing the PID Graph. �https://doi.org/10.5438/JWVF-8A66 �(CC BY 4.0)

Accumulate additional workflow metadata

Explore metadata extraction from publications, use Knowledge Graph services (MS5, MS6)

Provide guidance and workflow discovery for the user communities (WP5)

Inform EuroScienceGateway infrastructure decision making (WP4)

(appropriate workflow choice, Pulsar integration and meta-scheduling (T4.3).

Goal: Exchange workflow FDOs between EuroScienceGateway and EOSC, improve discovery by combining knowledge graphs

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Task T2.4: FAIR workflows as scholarly objects �in scientific publishing

Linking of workflows and their metadata to research publications

Supplement workflow metadata with information on publications

🡪 Extract such crosslinks from existing publications

Link publishing services used in research communities (WP5):

rapid communication services �(e.g. Astronomer’s Telegrams) 🡪 T5.2

preprint publishing services (e.g. arXiv.org)

public research output databases such as OpenAIRE

specialist journals for software publications �(e.g. Journal of Open Source Software, GigaByte)

traditional publishers and their services.

M1-M36: EPFL, VIB, UP, UNIMAN

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Establish WorkflowHub as a registry authority

Encourage workflow citations (e.g. DOI to WorkflowHub, DockStore, Zenodo) in journal articles

Extend research software citation practices and initiatives (e.g. RDA FAIR4RS, Workflows Community Initiative)

Establish FAIR workflow recommendations

Establish peer review assessment of workflows

Collaborate w/ FAIR-IMPACT (INFRA-2021-EOSC-01-05)

Goal: Incorporate workflow FDOs into the �scholarly communication landscape as �first class publishable objects

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WP2 partners and allocation

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Partner	Effort	Personnel [TBD]	Responsibilities and contributions
UNIMAN	23 PM	Stian, Finn, ++	WP2 leader, WorkflowHub, FDO, RO-Crate, FAIR workflows PIDs
EPFL	18 PM	Gabriele, Andrii, Volodymyr	Link to publications (T4.4), use-case-tester, astronomy perspective, external view �
VIB	11 PM	Ignacio, Paul	Galaxy provenance, connecting with WP4
BSC	8 PM	JM Fernández, Maria, ++	Main WP3 link, workflow engines, GA4GH. WP4 link to other projects (Spanish IMPaCT-Data, not related to ELIXIR IMPACT). Workflow scheduling improvements.
EGI	5 PM	Catalin, Gwen	Main EOSC link, EOSC-Portal, EOSC-Future, EOSC catalogue. EGI leading WP4. Perhaps Gwen on comms.
UiO	2 PM	Sveinung, ++	FAIR data aspects more than workflows (but also data workflows). Also connected to Galaxy community, GA4GH, and RDA. �Can also be a link to ELIXIR Norway efforts on workflows (non-sensitive mainly in Galaxy, sensitive probably not)

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Deliverables and milestones

D2.1 Reproducible FAIR Digital Objects for workflows�(lead: UNIMAN) M24

Report: FAIR Digital Objects (FDOs), for exchanging, publishing, archiving and citing workflows and their companion data, provenance logs and associated resources, will be realized as RO-Crates.

D2.2 Publishing workflow enriched FDOs to EOSC�(lead: UNIMAN) M30

Report: Publishing workflow enriched FDOs to EOSC

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MS3 Initial EuroScienceGateway workflows registered�(lead: VIB/UNIMAN) M18

Collection in WorkflowHub

MS4 EuroScienceGateway workflows registered as FDOs�(lead: VIB/UNIMAN) M36

Zenodo Data Deposit

MS5 Initial EuroScienceGateway knowledge graph�(lead: VIB/UNIMAN) M24

Zenodo Data Deposit

MS6 Integrated EuroScienceGateway knowledge graph�(lead: VIB/UNIMAN) M36

Zenodo Data Deposit; Report of integrations and queries

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Existing and potential collaborations

Link to the other projects

ELIXIR Europe: many of ESG partners are also in: �EOSC-Life, BY-COVID, EOSC4Cancer
RO-Crate – FAIR data packaging using Web standards:�schema.org, Bioschemas and EDAM ontology
FAIR Digital Object Forum (FDO Forum)
ELIXIR tools registry bio.tools
Synthesys+: Digitizing using Galaxy workflows, FDOs, RO-Crate
BioDT: biodiversity workflows on HPC, Lumi supercomputer
FAIR IMPACT: FAIR Research Software / Workflows
FAIR-EASE: Interoperable Earth Science & Environmental Services
HDR UK: Bringing federated analytics across trusted research environments
EOSC Task Forces: �Semantic Interoperability (UNIMAN), Infrastructure for Quality Research Software (BSC), Technical Interoperability of Data and Services (VIB)

…with other EOSC projects and initiatives

Previous links with Galaxy

WorkflowHub integration in UseGalaxy.eu with GA4GH TRS API (EOSC-Life, FR UNIMAN)
Workflow Run Crate support in Galaxy (VIB)
BioCompute Object support in Galaxy (ELIXIR-UK)
Common Workflow Language support and galaxy2cwl (VIB, UNIMAN)
ro-crate-py library (CRS4, VIB, UNIMAN)
FAIRtracks integration in Galaxy (UiO, BSC)

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Engagement with other work packages

WP1

Sustaining WorkflowHub as TRL-9 EOSC service (T1.4)
Training for FAIR Workflow FDOs (T1.6)

WP3

GA4GH APIs as Workflow FDO operations (T3.2)
Workflow FDO RO-Crate in TRS API (T3.2)
WfExS RO-Crate/provenance support (T3.4)

WP4

Workflow provenance to inform smart scheduling (T4.3)

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WP5

Biodiversity 🡪 FDO work with BioDT, DiSSCO, Synthesys+ (T5.1)
Climate Science 🡪 RO-Crate work in RELIANCE project (T5.1)
Materials Science 🡪 FDO work with NIST on Material Schema (T5.2)
Astrophysics 🡪 Workflows in Astronomer’s Telegrams, Galaxy in SKA, early Research Object adopters (Wf4Ever), (T5.3)
Outreach to workflow communities (T5.4)

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Open questions

How should we collect “just enough” metadata at different times? (workflow design, workflow run, workflow publishing)
Where to publish Workflow Run FDOs with potentially large or sensitive data ? (WP4)
Can WorkflowHub initiate Pulsar execution of non-Galaxy workflows, e.g. CWL, Nextflow? (T3.4)
How should we handle job submission with mixture of data, some of which may not leave a particular node? (T4.2)
How do we give users workflow discoverability aspects from enriched knowledge graphs? (WP5)
… your questions!

For discussions

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