COPO - Collaborative Open Plant Omics, by Rob Davey

COPO: Collaborative Open Plant Omics

Rob DaveyData Infrastructure and Algorithms Group Leader

[email protected]@froggleston

Acknowledgements

Oxford eResearch Centre

Susanna Sansone

Alejandra Gonzalez-Beltran

Philippe Rocca-Serra

Warwick

Jim Beynon

Katherine Denby

Ruth Bastow

EMBL-EBI

Paul Kersey

TGAC

Vicky Schneider

Tanya Dickie

Emily Angiolini

Matt Drew

Toni Etuk Felix Shaw

COPO

• Recently awarded BBSRC grant

• TGAC, Univ. Oxford, Univ. Warwick, EMBL-EBI

• Supported by GARNet, iPlant, Eagle Genomics

• Empower bioscience plant researchers to:

1. Enable standards-compliant data collection, curation and

integration

2. Enhance access to data analysis and visualisation pipelines

3. Facilitate data sharing and publication to promote reuse

• Train plant researchers in best practice for data sharing and

producing citable Research Objects

COPO

• (Good) Science is founded on reproducibility

• Reproducibility depends on:

• reducing reinvention (“friction”)*

• describing methods and data

• maximising benefit to the researcher

• Papers are seen as the typical way of distributing information

• Data description sorely under-represented and used

• Benefits are often opaque

• Fear of being scooped, loss of control, reputation, etc* http://cameronneylon.net/blog/network-enabled-research/

COPO

• What prevents plant scientists from openly depositing their data

and metadata?

• Lack of interoperability between:

• metadata annotation services

• data repository services

• data analysis services

• data publishing services

• Researchers might not:

• be aware that the services exist

• have the expertise to use them

• see the value in properly describing their data

COPO


and metadata?










5% TECHNICAL

COPO


and metadata?










5% TECHNICAL

95% CULTURAL

COPO

• Data:

• Sample, Sequence, Genome, Proteome, Metabolome, Phenotyping

• Code:

• GitHub, BitBucket, Zenodo

• Analysis:

• Galaxy, iPlant, Bioconductor, Taverna, local code/services

• Publication:

• figshare, Scientific Data, Dryad, F1000, PeerJ, Gigascience

• Beyond the PDF:

• Utopia, GitHub

• Training:

• Materials, examples, workshops, bootcamps

COPO

• It's not because these services don't exist!

• Clearly, barriers exist between the scientist and the service

• Infrastructure can help by:

• wiring existing services together

• improving access to services

• making consistent metadata attribution easier

• facilitating collaboration

• raising profile of the benefits of open science

• How do we collaborate successfully to make this happen?

• Mapping services with Application Programming Interfaces

COPO

COPO

• Single-sign on (SSO), e.g. ORCID

• Deposit multi-omics data in one go

• Genomics, metabolomics, proteomics, and so on

• No context-switching between services

• Brokering of research data

• Wizard systems guide users based on selected semantic terms

• Selecting options at given points informs the path

• Intuitive and less time intensive

• Mix of required repository metadata and extra descriptors

• Building knowledge graphs of linked data

INTEROPERABILITY

COPO• Run and deposit analytical workflows

• Describe software used, versions

• Data IO between platforms, e.g. Galaxy, iPlant

• Support virtualisation, e.g. iPlant Atmosphere, Docker, Amazon AWS

• Data is well-described, open, and DOIs will be minted

• Finding and integrating data improved greatly

• Make suggestions to users based on their metadata/data/workflows

• Users get recognition for sharing well-described data

• Data citation

• Programmatic access to all layers

REPRODUCIBILITY

COPO

COPO

COPO

COPO

• Build graphs of interconnected data, analyses and outputs

• Searches hitting any part of the graph will allow retrieval of

the rest

• Including any citations, data or text

COPO

• Not just raw/processed data is valuable

• COPO supports submission of supplementary data to Figshare

• PDFs (posters, papers)

• CSV/Excel

• movies/images (size permitting)

• Zenodo/Github releases for code DOIs

• e.g. ENCODE Digital Curation Center’s software metadata

descriptors

• EDAM/Software ontology

COPO

• What have we achieved so far?

• TGAC infrastructure to support brokering of data

• iRODS and web server virtual machines

• High speed transfer Aspera links to EBI

• Prototype user interface for multi-omics data submissions

• Oauth2 support (“sign in with” ORCiD, Google, Twitter)

• Moving to OpenID Connect?

• Profiles and collections for managing metadata

• Metadata for sequencing

• Tracking data uploads and accession status

COPO

• What have we achieved so far?

• Developing JSON specification for COPO objects

• Easily stored in document-based databases, e.g. MongoDB

• Interconversion between ISA formats

• ISATab (TSV based) to JSON, and vice versa

• Linked Data specifications

• Community interactions

• First user requirements workshop at TGAC

• F1000, GigaScience

• This meeting!

COPO• COPO will:

• Facilitate easy relevant data description

• Intuitively submit data and metadata to multiple public repositories

• Integrate with other research data management platforms

• Wheat Information System, iPlant, …

What are the barriers for plant research data?

5% technical, 95% cultural

• Work with other infrastructure builders to provide truly open connected

ecosystems for data?

• How can we help researchers realise the benefits of sharing data?