data publication: discover, explore, visualise

Data Publication:Discover, Explore, Visualise

Alejandra Gonzalez-Beltran, PhDResearch Lecturer

Oxford e-Research CentreUniversity of Oxford

Data Visualisation and the Future of Academic PublishingUniversity of Oxford and Oxford University Press

June 10th 2016@alegonbel

Philippe Rocca-Serra, PhDSenior Research Lecturer

AlejandraGonzalez-Beltran, PhDResearch Lecturer

Milo Thurston, DPhDResearch Software Engineer

MassimilianoIzzo, PhDResearch Software Engineer

Peter McQuilton, PhDKnowledge Engineer

Our main areas of research and activity:

• Enabling reproducible research through…

• Data collection, curation, representation etc.• Data publication• Data provenance • Development of software, infrastructure• Open, community ontologies and standards• Semantic web / linked data• Training

Communities we work with/for:Allyson Lister, PhDKnowledge Engineer

EamonnMaguire, DPhilSoftware Engineer contractor

David Johnson, PhDResearch Software Engineer

Susanna-Assunta Sansone, PhDPrincipal Investigator, Associate Director

OutlineOutline

• Challenges associated to scholarly data

• Importance of all research outputs / metadata

• Reproducibility crisis• Experiments description• Data availability

• Data publication• Springer Nature Scientific Data

• Discover, Explore, Visualise Scholarly Data• Scientific Data ISA-explorer






Credit to: https://www.digital-science.com/blog/news/five-top-reasons-to-protect-your-data-and-practise-safe-science/

Challenges related to scholarly dataChallenges related to scholarly data

• Outputs are multi-dimensional, diverse, not always well cited / storedo Software, codes, workflows etc.; hard(er) to get hold of

• Data often distributed and fragmented to fit (siloed) databaseso Without enough information for others to understand it

• Uneven level of details and annotation across different databaseso Specialized, generalist, public and institutional

• Data curation activities are perceived as time consumingo Collection and harmonization of detailed methods and experimental

steps is done/rushed at publication stage

But… shared data is not always understandable, reusable

But… shared data is not always understandable, reusable

Importance of- avoid selective reporting- experimental design- statistical power- statistical analysis- code/methods availability- data availability

Importance of- avoid selective reporting- experimental design- statistical power- statistical analysis- code/methods availability- data availability

• Incentive, credit for sharingo Big and small datao Unpublished datao Long tail of datao Curated aggregation

• Peer review of data• Value of data vs. analysis• Discoverability and reusability

o Complementing community databases

Growing number of data papers and data journalsGrowing number of data papers and data journals

nature.com/scientificdataHonorary Academic Editor Susanna-Assunta Sansone, PhD

Managing EditorAndrew L Hufton, PhD

Editorial CuratorVarsha Khodiyar

PublisherIain Hrynaszkiewicz

A new open-access, online-only publication for descriptions of scientifically valuable datasets

Supported by

Research

papers

Data

records

Data

Descriptors

Value added: complement between traditional articles & repositories

Value added: complement between traditional articles & repositories

Scientific hypotheses:SynthesisAnalysisConclusions

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

Relation with traditional articles – contentRelation with traditional articles – content

Citation of and links to data files and databasesCitation of and links to data files and databases

Citation of and links to data files and databasesCitation of and links to data files and databases

Credit for data producersCredit for data producers

A new article typeA new article type

A new category of publication that provides detailed descriptors of scientifically valuable datasets

Mandates open data, without unnecessary restrictions, as a condition of submission

Summary Table

Web app to discover, explore, visualise data descriptors

http://scientificdata.isa-explorer.org/

Browse

Keyword search

Filter

Filtering options

Summary Table

Filtering options

See annotations and number ofassociated data descriptors

Filtering options

Combination of filters

Visualise the samples’ characteristics

Publication date

Open associated data descriptor

Download Metadata

Licensing

Links to data repositories to access the data

Assays details

SummarySummary











Philippe Rocca-Serra, PhDSenior Research Lecturer

AlejandraGonzalez-Beltran, PhDResearch Lecturer

Milo Thurston, DPhDResearch Software Engineer

MassimilianoIzzo, PhDResearch Software Engineer

Peter McQuilton, PhDKnowledge Engineer

Communities we work with/for:Allyson Lister, PhDKnowledge Engineer

EamonnMaguire, DPhilSoftware Engineer contractor

David Johnson, PhDResearch Software Engineer

Susanna-Assunta Sansone, PhDPrincipal Investigator, Associate Director

Our main areas of research and activity:

• Enabling reproducible research through…

• Data collection, curation, representation etc.• Data publication• Data provenance • Development of software, infrastructure• Open, community ontologies and standards• Semantic web / linked data• Training

data publication: discover, explore, visualise

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