Consultant, Honorary Academic Editor
Associate Director, Principal Investigator
!
Better Data = Better Science !
Susanna-Assunta Sansone, PhD!!!
@biosharing!@isatools!
!
NC3Rs Publication Bias Workshop, London, 24-25 February, 2015
http://www.slideshare.net/SusannaSansone
Plagued by selective reporting of data and methods
Why? For example:
• Researchers still lack of or insufficient motivations
o Focus on big discovery and impact; because they “have to”
• Hypothesis-confirming results get prioritized
o Difficulties with reviews of other results
• Agreements, disagreements and timing
o Unclear or lack of data sharing agreements and timing of disclosure
• Loose requirements and monitoring by journals and funders
o Publish and release just enough; keep the rest, move to next grant
Are open data and methods understandable, reusable?
Not always…
• Outputs are multi-dimensional, diverse, not always well cited / stored
• Software, codes, workflows etc.; hard(er) to get hold of
• Data often distributed and fragmented to fit (siloed) databases
o Not contain enough information for others to understand it
• Uneven level of details and annotation across different databases
o Specialized, generalist, public and institutional
• Data curation activities are perceived as time consuming
o Collection and harmonization of detailed methods and experimental
steps is done/rushed at publication stage
Role of data papers / data journals
• Incentive, credit for sharing!• Data-focused peer review!• Value of data vs. analysis, results!• Support of the FAIR concept!
market research (2011)
• What do researchers want from a data publications? o 96% - increased visibility and discovery o 95% - increased usability of their research data o 93% - credit mechanism for deposit of data o 80% - peer review of content/datasets
Respondent characteristics 387 respondents (329 active researchers Physics (24%) Earth and environmental science (21%) Biology (20%) Chemistry (19%) Others (16%)
Because of importance of formal publications in the academic !
incentive structure!
Publishers occupy a leverage point
"!!
Helping you publish, discover and reuse research data
Credit for sharing your data
Focused on reuse and reproducibility
Peer reviewed, curated
Promoting community data and code repositories
Open Access
• Currently covering life, natural and environmental sciences!
• Big and small data!o power of small data are in their aggregation and
integration with other datasets!
• New and previously published individual datasets, curated collections and citizen science!
o a fuller, more in-depth look at the data processing steps, additional data files, codes etc!
o tutorial-like information for scientists interested in reusing or integrating the data with their own!
Methods and technical analyses supporting the quality of the measurements:"What did I do to generate the data?"How was the data processed?"Where is the data?"Who did what when"How can the data be used or reused?"
Introducing a new content type: Data Descriptor
Designed to make data more FAIR Focused mainly on: • Methods • Technical Validation • Data Records • Usage Notes
""""""""Scientific hypotheses:"Synthesis"Analysis"Conclusions"
Methods and technical analyses supporting the quality of the measurements:"What did I do to generate the data?"How was the data processed?"Where is the data?"Who did what when"How can the data be used or reused?"
Relation with traditional article - content
AFTER: expand on your research articles, adding further information for reuse of the data
AT THE SAME TIME: publish your Data Descriptor(s) alongside research article(s)
OR BEFORE
Relation with traditional article - time
Publish Data!
Evaluation is not be based on the perceived impact !or novelty of the findings or size of the data!
!
• Experimental rigour and technical data quality!o Methodologically sound!o Technical validation experiments and statistical analyses!o Depth, coverage, size, and/or completeness of data sufficient for the types
of applications!• Completeness of the description!
o Sufficient details to allow others to reproduce the results, reuse or integrate it with other data!
o Compliance with relevant minimum information or reporting standards!• Integrity of the data files and repository record!
o Data files match the descriptions in the Data Descriptor!o Deposited in the most appropriate available databases!
Peer review process focused on quality and reuse!
"""
Experimental metadata or "structured component"
(in-house curated, machine-readable formats)"
Article or "narrative component"
(PDF and HTML) !
Data Descriptor: narrative and structure
Sections:!• Title"• Abstract"• Background & Summary"• Methods"• Technical Validation"• Data Records"• Usage Notes "• Figures & Tables "• References"• Data Citations"!
Focus on data reuse"Detailed descriptions of the methods and technical analyses supporting the quality of the measurements.!Does not contain tests of new scientific hypotheses!
Joint Declaration of Data Citation Principles by the Data Citation Synthesis Group
Data Descriptor: narrative
In-house editorial curator assists authors via !• Excel spreadsheet
templates"• internal authoring tool!
to create the structured component, also performing value-added semantic annotation
analysis !method! script!
Data file or !record in a database!
Data Descriptor: structure (CC0)
…how not to report the experimental information!
• L!S1 ! !liver sample 1!• C2 ! !compound 2!• LD ! !low dose!• TP2 ! !time point 2!
• P1 ! !protocol 1!• file1-fastq.gz !compressed data file for sequence !! ! !information corresponding to this sample!
Sample name (?!)" Data file"
LS1_C2_LD_TP2_P1! file1-fastq.gz!
Structured component: key information from narrative
Seven week old C57BL/6N mice were treated with low-fat diet.
Liver was dissected out, hepatocytes prepared…
Age value Unit
Strain name Subject of the experiment
Type of diet and experimental condition Anatomy part
Seven week old C57BL/6N mice were treated with low-fat diet.
Liver was dissected out, hepatocytes prepared …
From natural language to ‘computable’ concepts
Type of protocol – cell preparation
Type of protocol - sample treatment
Type of protocol – liver preparation
25
What does a structured component add? • Supplements the scientific discourse!
o natural language has a degree of ambiguity!• Brings clarity in reporting research methods and procedures!
o no trimming, no cooking!o clear samples to data files links and relation to methods!
• Provides the basis for search and discovery features!
SciData DD
Structured content SciData DD
Structured content
SciData DD
Structured content
SciData DD
Structured content
SciData DD
Structured content
SciData DD
Structured content
SciData DD
Structured content
SciData DD
Structured content
SciData DD
Structured content
SciData DD
Structured content
Same tissue
Same organism
Same assay
Community Data
Repositories
Res
earc
h pa
pers
D
ata
reco
rds
Dat
a D
escr
ipto
rs
We currently recognize over 60 public data repositories!!
Helping the authors to find the right place for the data
Big data | CSE 2014 28
Repositories criteria!
1. Broad support and recognition within their scientific community !
2. Ensure long-term persistence and preservation of datasets!
3. Provide expert curation !
4. Implement relevant, community-endorsed reporting requirements !
5. Provide for confidential review of submitted datasets !
6. Provide stable identifiers for submitted datasets !
7. Allow public access to data without unnecessary restrictions !
~ 156
~ 70
~ 334
Source: BioPortal
Databases !implementing !
standards!
miame!MIAPA!
MIRIAM!MIQAS!MIX!
MIGEN!
ARRIVE!MIAPE!
MIASE!
MIQE!
MISFISHIE….!
REMARK!
CONSORT!
MAGE-Tab!GCDML!
SRAxml!SOFT! FASTA!
DICOM!
MzML !SBRML!
SEDML…!
GELML!
ISA-Tab!
CML!
MITAB!
AAO!CHEBI!
OBI!
PATO! ENVO!MOD!
BTO!IDO…!
TEDDY!
PRO!XAO!
DO
VO!
Progressively refine guidance to authors and reviewers
Nature 515, 312 (20 November 2014) doi:10.1038/515312a http://www.nature.com/news/data-access-practices-strengthened-1.16370
Key part of NPG data access & reproducible research policies
Responsibilities lie across several stakeholder groups
Understand the benefits of sharing FAIR datasets and enact them
Engage and assist researchers to enable them to share FAIR datasets
Release or endorse practices and polices, but also incentive
and credit mechanisms for researchers, curators and
developers
Acknowledgements!
Visit nature.com/scientificdata
Email [email protected]
Tweet @ScientificData
Honorary Academic Editor Susanna-Assunta Sansone, PhD
Managing Editor Andrew L Hufton, PhD Editorial Curator Varsha Khodiyar
Publisher Iain Hrynaszkiewicz Advisory Panel and Editorial Board including senior researchers, funders, librarians and curators
and our Advisory Boards and Collaborators
Funds: Philippe Rocca-Serra, PhD Senior Research Lecturer
Alejandra Gonzalez-Beltran, PhD Research Lecturer
Eamonn Maguire, Dphil Contractor
Milo Thurston, PhD Senior Bioinfomatician
Allyson Lister, PhD Knowledge Engineer
Alfie Abdul-Rahman, PhD Research Software Engineer