...how licensing can change the way we do research
Scott EdmundsA*STAR, 18th April 2013
Open-DataOpen-Source
Open-Review Open-Access
www.gigasciencejournal.com
Journal, data-platform and database for large-scale data
Editor-in-Chief: Laurie GoodmanExecutive Editor: Scott Edmunds
Commissioning Editor: Nicole NogoyLead Curator: Chris Hunter
Data Platform: Peter Li
in conjunction with
Open-Review Open-Access
Open-DataOpen-Source
Why? How?
What can be achieved?
Its all about the re-use
To do this everything needs to be free and accessible to be read by humans & machines*
* See: http://www.biomedcentral.com/about/datamining
Take home message:
?Why
Big-Data BonanzaData is the new oil?
"Information is the currency of the future world”
William Gibson
Era of Data-Driven Science
Using networking power of the internet to tackle problems
Can ask new questions & find patterns & connections hidden in others data
Build on each others efforts quicker & more efficiently
More collaborations across more disciplines
Harness wisdom of the crowds: crowdsourcing, citizen science, crowdfunding
Enables:
Enabled by:Removing silos, standards/formats, open-access/data
Good for a field:Genomics/Bioinformatics
Long term sharing infrastructure:
Strong use of standards/policies:
Plummeting cost/explosion in volumes:
19961997
19981999
20002001
20022003
20042005
20062007
20080
100
200
300
400
500
600
700rice wheat
Rice v Wheat: consequences of publically available genome data.
Sharing aids specific communities…
Papers
Sharing aids individuals…
Piwowar HA, Day RS, Fridsma DB (2007) PLoS ONE 2(3): e308. doi:10.1371/journal.pone.0000308
Sharing Detailed Research Data Is Associated with Increased Citation Rate.
Every 10 datasets collected contributes to at least 4 papers in the following 3-years.Piwowar, HA, Vision, TJ, & Whitlock, MC (2011). Data archiving is a good investment Nature, 473 (7347), 285-285 DOI: 10.1038/473285a
Growing Issue: unrepeatability of scientific results
Ioannidis et al., 2009. Repeatability of published microarray gene expression analyses.Nature Genetics 41: 149-155.
Out of 18 microarray papers, resultsfrom 10 could not be reproduced
Growing Issue: increasing number of retractions>15X increase in last decade
Strong correlation of “retraction index” with higher impact factor
1. Science publishing: The trouble with retractions http://www.nature.com/news/2011/111005/full/478026a.html2. Retracted Science and the Retraction Index ▿ http://iai.asm.org/content/79/10/3855.abstract?
?How
GigaSolution: deconstructing the paper
Provide infrastructure and mechanisms of reward for:
• Data availability
• Metadata/curation
• Interoperability
• Availability of workflows
• Transparent analyses
Data
Metadata
Methods
Analyses
GigaSolution: deconstructing the paper
www.gigadb.orgwww.gigasciencejournal.com
Worlds largest genomics organisation with: 17PB storage, 20.5K cores, 212TFlops, >1000 bioinformaticians
Utilizes big-data infrastructure and expertise from:
Combines and integrates:
Open-access journal
Data Publishing Platform
Data Analysis Platform
Open-Access
Why/what/how?Where does licensing fit?
Importance of licensing: ability to mine & reuse content
“By “open access” to [peer-reviewed research literature], we mean its free availability on the public internet, permitting any users to read, download, copy, distribute, print, search, or link to the full texts of these articles, crawl them for indexing, pass them as data to software, or use them for any other lawful purpose, without financial, legal, or technical barriers other than those inseparable from gaining access to the internet itself. The only constraint on reproduction and distribution, and the only role for copyright in this domain, should be to give authors control over the integrity of their work and the right to be properly acknowledged and cited.”
=
=
Needs to be:
SA, NC, ND put unnecessary restrictions and are not counted as “true OA”
CC0 better than CC-BY for datasets to prevent “attribution stacking”
Budapest Open Access Initiative:
Importance of licensing: ability to mine & reuse content
=
Prevents translations, incompatibility issues mixing other licenses, some combinations illegal (e.g. CC-NC-SA & CC-BY-SA), hinders non-profits and mixed-collaborations, practically unenforceable, dealing with requests more trouble than its worth.
Further reading:http://www.nature.com/nature/journal/v495/n7442/full/495440a.htmlhttp://blogs.ch.cam.ac.uk/pmr/2011/11/29/scientists-should-never-use-cc-nc-this-explains-why/
Use of non CC-BY by publishers = “double dipping” (selling content, reprints, etc.)
• Gives authors control over the integrity of their work and the right to be properly acknowledged and cited.
• Does not grant publicity rights, and attribution can be used to clearly disclaim endorsement
• Restrictions rarely benefit author, but do inhibit reuse
Open-DataData PublishingWhy/what/how?
?
New incentives/credit
Credit where credit is overdue:“One option would be to provide researchers who release data to public repositories with a means of accreditation.”“An ability to search the literature for all online papers that used a particular data set would enable appropriate attribution for those who share. “Nature Biotechnology 27, 579 (2009)
Prepublication data sharing (Toronto International Data Release Workshop)“Data producers benefit from creating a citable reference, as it can later be used to reflect impact of the data sets.” Nature 461, 168-170 (2009)
?
New incentives/credit
“increase acceptance of research data as legitimate, citable contributions to the scholarly record”.
“data generated in the course of research are just as valuable to the ongoing academic discourse as papers and monographs”.
= Data Citation?
Anatomy of a Publication
Data
Idea
Study
Analysis
Answer
Metadata
Anatomy of a Data Publication
Data
Idea
Study
Analysis
Answer
Metadata
• Data availability• Content re-use• …
= Credit}
GigaDB is a new database integrated with the GigaScience journal to meet the needs of a new generation of biological and biomedical research as it enters the era of “big-data”… (see more)
BGI Datasets Get DOI®s
PLANTSChinese cabbageCucumberFoxtail milletPigeonpeaPotatoSorghumWheat A+B
Microbe/metagenomicsE. Coli O104:H4 TY-2482T2D gut metagenomeBulk pooled insects
Cell-LinesChinese Hamster OvaryMouse methylomes
Human Asian individual (YH) - DNA Methylome - Genome Assembly v1+2- TranscriptomeCancer (14TB)Single cell bladder cancerHBV infected exomesAncient DNA - Saqqaq Eskimo - Aboriginal Australian
VertebratesDarwin’s FinchGiant panda Macaque -Chinese rhesus -Crab-eatingMini-PigNaked mole rat Parrot, Puerto Rican Penguin - Emperor penguin- Adelie penguinPigeon, domesticPolar bearSheepTibetan antelope
InvertebrateAnt - Florida carpenter ant- Jerdon’s jumping ant- Leaf-cutter antRoundwormSchistosomaSilkwormParasitic nematodePacific oyster
Released pre-publicationPaper Published in GigaScience
Open-Source
The new way of doing science?
Why/what/how?
Open-Source: the source of it all
• Transparent, fast, collaborative
• Long history, large community
• Many licenses
• Many repositories
• Many users/platforms
Software community understands benefits
Open-Review
Why/what/how?
New & more transparent peer-review:Pre-publication: pre-prints
New & more transparent peer-review:During-publication: open-review
BMC Series Medical Journals
New & more transparent peer-review:Post-publication review
Open content lets you do interesting things post-publication:
New pub models:
Altmetrics:
Comments, blogs, online journal clubs
Examples
The Peoples Parrot: Amazona vittata Puerto Rican Parrot Genome ProjectRarest parrot, national bird of Puerto Rico
Community funded from artworks, fashion shows, crowdfunding…
Genome annotated by students in community college as part of bioinformatics education
Paper and Data published in GigaScience and GigaDB
Taras K Oleksyk, et al., (2012) A Locally Funded Puerto Rican Parrot (Amazona vittata) Genome Sequencing Project Increases Avian Data and Advances Young Researcher Education. GigaScience 2012, 1:14Steven J. O’Brien. (2012): Genome empowerment for the Puerto Rican parrot – Amazona vittata. GigaScience 2012, 1:13Oleksyk et al., (2012): Genomic data of the Puerto Rican Parrot (Amazona vittata) from a locally funded project. GigaScience. http://dx.doi.org/10.5524/100039
How are we supporting data reproducibility?
Data sets
Analyses
Linked to
Linked to
DOI
DOI
Open-Paper
Open-Review
DOI:10.1186/2047-217X-1-18~8000 accesses
Open-Code
8 reviewers tested data in ftp server & named reports published
DOI:10.5524/100044
Open-PipelinesOpen-Workflows
DOI:10.5524/100038Open-Data
78GB CC0 data
Code in sourceforge under GPLv3: http://soapdenovo2.sourceforge.net/~4000 downloads
Enabled code to being picked apart by bloggers in wiki http://homolog.us/wiki/index.php?title=SOAPdenovo2
SOAPdenovo2 workflows implemented in
galaxy.cbiit.cuhk.edu.hk
SOAPdenovo2 workflows implemented in
galaxy.cbiit.cuhk.edu.hk
Implemented entire workflow in our Galaxy server, inc.:
• 3 pre-processing steps
• 4 SOAPdenovo modules
• 1 post processing steps
• Evaluation and visualization tools
Also available to download by >25K Galaxy users in
New & more transparent peer-review:The GigaScience way:
8 referees downloaded & tested data, then signed reports
New & more transparent peer-review:The GigaScience way:
Post publication: bloggers pull apart code/reviews in blogs + wiki:
SOAPdenov2 wiki: http://homolog.us/wiki1/index.php?title=SOAPdenovo2Homologus blogs: http://www.homolog.us/blogs/category/soapdenovo/
New & more transparent peer-review:The GigaScience way:
Real-time open-review = paper in arXiv + blogged reviews
To maximize its utility to the research community and aid those fighting the current epidemic, genomic data is released here into the public domain under a CC0 license. Until the publication of research papers on the assembly and whole-genome analysis of this isolate we would ask you to cite this dataset as:
Li, D; Xi, F; Zhao, M; Liang, Y; Chen, W; Cao, S; Xu, R; Wang, G; Wang, J; Zhang, Z; Li, Y; Cui, Y; Chang, C; Cui, C; Luo, Y; Qin, J; Li, S; Li, J; Peng, Y; Pu, F; Sun, Y; Chen,Y; Zong, Y; Ma, X; Yang, X; Cen, Z; Zhao, X; Chen, F; Yin, X; Song,Y ; Rohde, H; Li, Y; Wang, J; Wang, J and the Escherichia coli O104:H4 TY-2482 isolate genome sequencing consortium (2011) Genomic data from Escherichia coli O104:H4 isolate TY-2482. BGI Shenzhen. doi:10.5524/100001 http://dx.doi.org/10.5524/100001
Our first DOI:
To the extent possible under law, BGI Shenzhen has waived all copyright and related or neighboring rights to Genomic Data from the 2011 E. coli outbreak. This work is published from: China.
Downstream consequences:
“Last summer, biologist Andrew Kasarskis was eager to help decipher the genetic origin of the Escherichia coli strain that infected roughly 4,000 people in Germany between May and July. But he knew it that might take days for the lawyers at his company — Pacific Biosciences — to parse the agreements governing how his team could use data collected on the strain. Luckily, one team had released its data under a Creative Commons licence that allowed free use of the data, allowing Kasarskis and his colleagues to join the international research effort and publish their work without wasting time on legal wrangling.”
1. Citations (~140) 2. Therapeutics (primers, antimicrobials) 3. Platform Comparisons
4. Example for faster & more open science
1.3 The power of intelligently open dataThe benefits of intelligently open data were powerfully illustrated by events following an outbreak of a severe gastro-intestinal infection in Hamburg in Germany in May 2011. This spread through several European countries and the US, affecting about 4000 people and resulting in over 50 deaths. All tested positive for an unusual and little-known Shiga-toxin–producing E. coli bacterium. The strain was initially analysed by scientists at BGI-Shenzhen in China, working together with those in Hamburg, and three days later a draft genome was released under an open data licence. This generated interest from bioinformaticians on four continents. 24 hours after the release of the genome it had been assembled. Within a week two dozen reports had been filed on an open-source site dedicated to the analysis of the strain. These analyses provided crucial information about the strain’s virulence and resistance genes – how it spreads and which antibiotics are effective against it. They produced results in time to help contain the outbreak. By July 2011, scientists published papers based on this work. By opening up their early sequencing results to international collaboration, researchers in Hamburg produced results that were quickly tested by a wide range of experts, used to produce new knowledge and ultimately to control a public health emergency.
Changing the way we publish:
“Deconstructed”Journal
“Regular”Journal
“Conscientious” Online Journal
“Deconstructed”Journal
“Regular”Journal
“Conscientious” Online Journal
“Deconstructed”Journal
“Regular”Journal
“Conscientious” Online Journal
Image Source: http://commons.wikimedia.org/wiki/File:System-Mechanic-California.jpg
“Deconstructed”Journal
“Regular”Journal
“Conscientious” Online Journal
Ultimate Goal: Executable papersData
Papers
Executable (Methods)
Papers
Analysis Papers
www.gigasciencejournal.com
Give us your data, papers & pipelines*
Help us make it happen!
[email protected]@[email protected]
Contact us:
* APC’s currently generously covered by BGI
Ruibang Luo (BGI/HKU)Shaoguang Liang (BGI-SZ)Tin-Lap Lee (CUHK)Huayen Gao (CUHK)Qiong Luo (HKUST)Senghong Wang (HKUST)Yan Zhou (HKUST)
Thanks to:
@gigasciencefacebook.com/GigaScienceblogs.openaccesscentral.com/blogs/gigablog/
Peter LiChris HunterJesse Si ZheNicole NogoyTam SneddonAlexandra BasfordLaurie Goodman
Follow us:www.gigadb.org
galaxy.cbiit.cuhk.edu.hkwww.gigasciencejournal.com
CBIIT
Funding from:Our collaborators:team:
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