Adventures in Data Citation: deadly E. coli outbreaks, Sorghum and RNA-editomes provide examples for the future.

www.gigasciencejournal.com

DataCite Summer meeting 14th June 2012, CopenhagenScott Edmunds

doi:10.5524/100012

Overview

Introduction

/ Genomics #101Data-Sharing Issues

Adventures in Data Citation

Our Examples

How it’s working…

Downstream consequences…

My two RMB/what is still needed…

A brief history of genomics…

Source: http://www.genome.gov/Images/press_photos/highres/38-300.jpg

Human Genome Project: 1990-2003. 1 Genome = $3 Billion

A brief history of genomics…

Source: http://www.genome.gov/sequencingcosts/ (with apologies)

A brief history of genomics…

Source: http://www.genome.gov/sequencingcosts/ (with apologies)

1st Gen 2nd (next) Gen

3rd (next-next) Gen?

A brief history of genomics…

Source: http://www.genome.gov/sequencingcosts/ (with apologies)

3rd (next-next) Gen?

BGI Introduction

• Formerly known as Beijing Genomics Institute• Founded in 1999 (1% of HGP)• Not-for-profit research institute funded by commercial

sequencing-as-a-service• Now the largest genomic organization in the world• Goal

– Use genomics technology to impact the society– Make leading edge genomics highly accessible to the global research community

Global, with HQ in Shenzhen

Global, with HQ in Shenzhen

Global Sequencing Capacity

Data Production 5.6 Tb / day

> 1500X of human genome / day

Multiple Supercomputing Centers 157 TB Flops

20 TB Memory

14.7 PB Storage

BGI Sequencing Capacity

Data Production 5.6 Tb / day

> 1500X of human genome / day

Multiple Supercomputing Centers 157 TB Flops

20 TB Memory

14.7 PB Storage

137

Sequencers137 Illumina/HiSeq 200027 LifeTech/SOLiD 41 454 GS FLX+2 Illumina iScan1 Illumina MiSeq1 Ion Torrent

M+M+M: Million Genome Projects• Plant and Animal Genomes: G10K, i5K...

• Variation Genomes: 10K rice resequencing....

• Human Genomes: Ancient, Population, Medical

• Cell Genomes: cancer single cell

• Micro Ecosystems: Metahit, EMP, etc.

• Personal Genomes

Goal – “Just sequence it.”

BGI Goes Denmark

BGI Goes Denmark

V

Genomics: the data-sharing success story?:

Sharing/reproducibility helped by stability of:

1. Platforms

2. Repositories

3. Standards

1st Gen 2nd Gen

:

Genomics Data Sharing Policies…

1. Automatic release of sequence assemblies within 24 hours.2. Immediate publication of finished annotated sequences.3. Aim to make the entire sequence freely available in the public domain for

both research and development in order to maximise benefits to society.

Bermuda Accords 1996/1997/1998:

1. Sequence traces from whole genome shotgun projects are to be deposited in a trace archive within one week of production.

2. Whole genome assemblies are to be deposited in a public nucleotide sequence database as soon as possible after the assembled sequence has met a set of quality evaluation criteria.

Fort Lauderdale Agreement, 2003:

The goal was to reaffirm and refine, where needed, the policies related to the early release of genomic data, and to extend, if possible, similar data release policies to other types of large biological datasets – whether from proteomics, biobanking or metabolite research.

Toronto International data release workshop, 2009:

(A) Cumulative base pairs in INSDC over time, excluding the Trace Archive.

Karsch-Mizrachi I et al. Nucl. Acids Res. 2012;40:D33-D37Published by Oxford University Press 2011.

(B) Base pairs in INSDC, broken down into selected data components.

Challenges for the future…

1. Data Volumes (transfer, backlogs, funding issues)

2. Compliance

3. Lack of interoperability/sufficient metadata

4. Long tail of curation (“Democratization” of “big-data”)

Challenges for the future…

?

?

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?

www.gigasciencejournal.com

Large-Scale Data Journal/Database

Editor-in-Chief: Laurie Goodman, PhDEditor: Scott Edmunds, PhDAssistant Editor: Alexandra Basford, PhDLead Curator: Tam Sneddon D.Phil

In conjunction with:

First issue next month…

www.gigaDB.org

Associated Database

Papers in the era of big-data

Analysis Data

Tools/Workflows

Compute

goal: Executable Research Objects

Citable DOI

Adventures in Data Citation

doi:10.5524/100001

For data citation to work, needs:

1. Proven utility/potential user base.

2. Acceptance/inclusion by journals.

3. Data+Citation: inclusion in the references.

4. Tracking by citation indexes.

5. Usage of the metrics by the community…

Datacitation 1: utility/user base.

Shackleton NJ, Hall MA, Vincent E (2001): Mean stable carbon isotope ratios of Cibicidoides wuellerstorfi from sediment core MD95-2042 on the Iberian margin, North Atlantic. PANGAEA - Data Publisher for Earth & Environmental Science. http://doi.pangaea.de/10.1594/PANGAEA.58229

Pahnke K, Zahn R: Southern Hemisphere Water Mass Conversion Linked with North Atlantic Climate Variability. Science 2005, 307:1741 -1746.

Cited in:

Andreeva A, Howorth D, Chandonia J-M, Brenner SE, Hubbard TJP, Chothia C, Murzin AG: Data growth and its impact on the SCOP database: new developments. Nucleic Acids Res. 2008, 36:D419-425.

Nocek B, Xu X, Savchenko A, Edwards A, Joachimiak A. 2007. PDB ID: 2P06 Crystal structure of a predicted coding region AF_0060 from Archaeoglobus fulgidus DSM 4304. 10.2210/pdb2p06/pdb.

Cited in:

Establishment of data DOIs and use by databases:

BGI Datasets Get DOI®s

doi:10.5524/100004

PLANTSChinese cabbageCucumberFoxtail milletPigeonpeaPotatoSorghum

MicrobeE. Coli O104:H4 TY-2482

Cell-LineChinese Hamster Ovary

Human Asian individual (YH) - DNA Methylome - Genome Assembly- TranscriptomeCancer (14TB)Ancient DNA - Saqqaq Eskimo - Aboriginal Australian

VertebratesGiant panda Macaque - Chinese rhesus - Crab-eatingMini-PigNaked mole rat Penguin - Emperor penguin- Adelie penguinPigeon, domesticPolar bearSheepTibetan antelope

InvertebrateAnt - Florida carpenter ant- Jerdon’s jumping ant- Leaf-cutter antRoundwormSchistosomaSilkworm

Many released pre-publication…

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. Therapeutics (primers, antimicrobials) 2. Platform Comparisons (Loman et al., Nature Biotech 2012)

3. Speed/legal-freedom

Data Citation 2: acceptance by journals

Data Citation 2: acceptance by journals

Data+Citation 3: inclusion in the references

• Data submitted to NCBI databases:

• Submission to public databases complemented by its citable form in GigaDB (doi:10.5524/100012).

- Raw data SRA:SRA046843 - Assemblies of 3 strains Genbank:AHAO00000000-AHAQ00000000 - SNPs dbSNP:1056306 - CNVs- InDels dbVAR:nstd63 - SV

}

In the references…

Is the DOI…

And now in Nature Biotech…

And in more journals…

Hodkinson BP, Uehling JK, Smith ME: Lepidostroma vilgalysii, a new basidiolichen from the New World. Mycological Progress 2012. Advance Online Publication.

Hodkinson BP, Uehling JK, Smith ME (2012) Data from: Lepidostroma vilgalysii, a new basidiolichen from the New World. Dryad Digital Repository. doi:10.5061/dryad.j1g5dh23

Cited in:

Roberts SB, Hauser L, Seeb LW, Seeb JE (2012) Development of Genomic Resources for Pacific Herring through Targeted Transcriptome Pyrosequencing. PLoS ONE 7(2): e30908. doi:10.1371/journal.pone.0030908

Cited in:

Roberts SB (2012) Herring Hepatic Transcriptome 34300 contigs.fa. Figshare. Available: hdl.handle.net/10779/084d34370fbda29bbc6 7b3c5ecb02575. Accessed 2012 Jan 20.

For data citation to work, needs:

1. Proven utility/potential user base.

2. Acceptance/inclusion by journals.

3. Data+Citation: inclusion in the references.

4. Tracking by citation indexes.

5. Usage of the metrics by the community…

✔

✔

✔

Datacitation 4: tracking?

DataCite metadata in harvestable form (OAI-PMH)

Datacitation 4: tracking?

✗FAIL

- lists some DataCite DOIs, but says:

Datasets listed are the “result of approximations in the indexing algorithms.”

“Google Scholar's intended coverage is for scholarly articles. At this point, we don't include datasets. “

…the final challenge?

DataCite metadata in harvestable form (OAI-PMH)

Datacitation 4: tracking?

✗FAIL

✗ Working on it. Coming soon?

“As a result of diverse practices and tool limitations, data citations are currently very difficult to track.”

Datacitation 5: metrics?

I’m afraid we are making promises to data creators about attribution and reward that we can’t keep. ”Make your data citeable!” is the cry. Ok. So citeable is step one. Cited is step two. But for the citation to be useful, it has to be indexed so that citation metrics can be tracked and admired and used.

Who is indexing data citations right now? As far as I can tell: absolutely no one.

Research Remix, 29th May 2012: http://researchremix.wordpress.com/2012/05/29/dear-research-data-advocate-please-sign-the-petition-oamonday/

Datacitation 5: metrics?✗FAIL

Where data citation is in 2012:

1. Proven utility/potential user base.

2. Acceptance/inclusion by journals.

3. Data+Citation: inclusion in the references.

4. Tracking by citation indexes.

5. Usage of the metrics by the community…

✔

✔

✔

✗✗

Minor quibbles: export to citation managers

Zheng L-Y ; Guo X-S ; He B ; Sun L-J ; Peng Y ; Dong S-S ; Liu T-F ; Jiang S ; Ramachandran S ; Liu C-M ; Jing H-C: Genome data from sweet and grain sorghum (Sorghum bicolor). 2011.

Zheng, L-Y (2011). Genome data from sweet and grain sorghum (Sorghum bicolor). GigaScience. Retrieved from http://dx.doi.org/10.5524/100012

Zheng, L-Y; Guo, X-S; He, B; Sun, L-J; Peng, Y; Dong, S-S; Liu, T-F; Jiang, S; Ramachandran, S; Liu, C-M; Jing, H-C; (2011): Genome data from sweet and grain sorghum (Sorghum bicolor); GigaScience. http://dx.doi.org/10.5524/100012

DCC/DataCite recommended format:

formatting:

Mendeley formatting:

Rules for versioning/where do you set granularity?

Experiment(e.g. ACRG project)

Datasets(e.g. cancer type)

Sample(e.g. specimen xyz)

e.g. doi:10.5524/100001

e.g. doi:10.5524/100001-2

e.g. doi:10.5524/100001-2000or doi:10.5524/100001_xyz

Smaller still?

Minor quibbles: clearer guidelines

Papers

Data/Micropubs

NanopubsFacts/Assertations (~1013 in literature)

Papers in the era of big-datagoal: Executable Research Objects

July 2012 Wilson GA, Dhami P, Feber A, Cortázar D, Suzuki Y, Schulz R, Schär P, Beck S: Resources for methylome analysis suitable for gene knockout studies of potential epigenome modifiers. GigaScience 2012, 1:3. (in press)

GigaDB hosting all data + tools (84GB total): doi:10.5524/100035+

Partial (~80%) integration of workflow into our data platform.(all the data processing steps, but not the enrichment analysis)

Data in ISA-Tab compliant format

Next stage… Papers fully integrating all data + all workflows in our platform.

Do you have interesting large-scale biological data sets?

Interested in Reproducible Research?Take part in our session on: “Cloud and workflows for reproducible bioinformatics”

• Rapid review/Open Access/High-visibility• Article Processing Charge covered by BGI• Hosting of any test datasets/workflows in GigaDB

Submit to:

www.gigasciencejournal.com

Thanks to:

scott@gigasciencejournal.com

editorial@gigasciencejournal.com

@gigascience

facebook.com/GigaScience

blogs.openaccesscentral.com/blogs/gigablog/

Contact us:

Laurie Goodman Alexandra BasfordTam Sneddon Shaoguang LiangTin-Lap Lee (CUHK) Qiong Luo (HKUST)

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