Data Publication: Discover, Explore, Visualise Alejandra Gonzalez-Beltran, PhD Research Lecturer Oxford e-Research Centre University of Oxford Data Visualisation and the Future of Academic Publishing University of Oxford and Oxford University Press June 10 th 2016 @alegonbel
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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
• 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
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
• 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
• 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
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