BGI training lecture: Scott Edmunds - Science 2.0, why new developments on the web will make you a better scientist!Presentation Transcript
Scott Edmunds Science 2.0 and beyond: how new developments on the web will make you a better scientist! ? (“Everything you wanted to know about social networks but were too afraid to ask…”)
What is? “Science 2.0 uses the technologies of web 2.0 to conversations between researchers, let them discuss the data and connect it with other data that might be relevant. Blogs, wikis and such permit users to make information available in ways that create a conversation. Web 2.0 permits scientists to create digitized conversations that provide context for the data.” (+ Semantic Web)
Open-Science For Against Allows crowdsourcing. Better for Science. Fairer (public money). More use (=citations) Scooping? Patents/publications? Time/effort. Data deluge?
Open-Science Sharing Detailed Research Data Is Associated with Increased Citation Rate. Piwowar HA, Day RS, Fridsma DB (2007) PLoSONE 2(3): e308. doi:10.1371/journal.pone.0000308
Daphnia Genome Consortium wFleabase: Mar 2006 Genome release: July 2007 Genome Published: Feb 2011 >58 companion papers https://daphnia.cgb.indiana.edu/Publications
Open Lab Notebooks
Faster scientific communication FUTURE PAST
Why is it important for Chinese research?
Online sources of scientific information Databases/portals of traditional media Blogs (networks/aggregators) Social Networks: Open Notebook Science Wikis Forums/Other
Traditional media 2.0 Science databases: general Subject specific Journal content: browse eTOCs RSS
Science Blogs Some good examples: Tree of Life (Jonathon Eisen): http://phylogenomics.blogspot.com/ Bad Science (Ben Goldacre):http://www.badscience.net/ A Blog around the Clock (Bora Zivkovic): http://blog.coturnix.org/ Not Exactly Rocket Science (Ed Yong): http://blogs.discovermagazine.com/notrocketscience/ Genetic Future (Daniel MacArthur): http://www.wired.com/wiredscience/geneticfuture OMICS, OMICS! (Keith Robison): http://omicsomics.blogspot.com/ Bacpathgenomics (Kat Holt): http://bacpathgenomics.wordpress.com/
Science Blogs Blog Aggregators: Science Blogging: http://scienceblogging.org/ Research Blogging: http://researchblogging.org/ Honorable Mention: NCBI ROFL: http://blogs.discovermagazine.com/discoblog/category/ncbi-rofl/ Urologe A. 2005 Dec;44(12):1473-5. Inappropriate use of a titanium penile ring. An interdisciplinary challenge for urologists, jewelers, and locksmiths. Wiedemann A, Müller H, Rabs U. Psychol Rep. 2011 Feb;108(1):43-4. National anthems and suicide rates. Lester D, Gunn JF 3rd.
Social Media Good for events Good for networking Good for groups
Using Twitter for Science James Darcy: “Researchers need to get themselves onto Twitter pronto because it is fast becoming the place to find out the breakthroughs in your research field.” Jonathan Eisen:“To do science, you have to know what’s going on…I found Twitter…most useful for becoming informed of what other people are doing in science.” “Twitter and other social networks such as FriendFeedenable real-time highlighting and ranking and tracking of what’s going on in the world of science.” “Twitter is also useful for networking and finding collaborators.” http://deepseanews.com/2010/08/what-is-twitter-and-why-scientists-need-to-use-it/
Using Twitter for Science Twitter is: Microblog: max 140 characters (“The SMS of the Internet”) Global: 200m users, 190m tweets (1.6b searches)/day. Fast: 2,200 new tweets/s! (can fluctuate 3-4x) Instant: view global trends/keywords with hashtags #
Using Twitter for Science Twitter is good for: Eavesdropping: follow informative people to get information and learn Dialogue: exchange, discuss, and debate information Broadcast: used by news organizations and businesses to inform audience about news or products/services Data collection: e.g. using Tweeting fishermen to monitor fish populations. Accidental journalism: e.g. landing on Hudson river, Michael Jackson death, Japan Earthquake Mindcasting: following a single story or topic, with links, for a period of time, e.g. like my ongoing coverage of the #Ecoliat @BGI_Events
Using Twitter for Science Twitter is not so good for:
Using Twitter for Science How it works (‘twetiquette’): People will only read your messages if you have followers or RT’s (re-tweets), so: Keep it interesting. Keep it short (<140 characters) Use links and link-shorteners (bit.ly/t.co/owl.ly) Keep it interactive (2-way). Use hashtags and twitter ID’s (@xxx) Have regular content (RT’s). Intersperse tweets. Think about timezones (Europe=late afternoon, US=night).
Further reading: Twitter: A gentle introduction to Twitter for the apprehensive academic http://deevybee.blogspot.com/2011/06/gentle-introduction-to-twitter-for.html What is Twitter and Why Scientists Need To Use It. http://deepseanews.com/2010/08/what-is-twitter-and-why-scientists-need-to-use-it/ Science journalism: Breaking the convention? http://www.nature.com/news/2009/090624/full/4591050a.html Analysing the ISMB 2010 meeting using R http://nsaunders.wordpress.com/2010/07/20/analysing-the-ismb-2010-meeting-using-r/ Sharing slides from a presentation plus how to do this w/ Slideshare http://www.microbe.net/2011/06/15/sharing-slides-from-a-presentation-plus-how-to-do-this-w-slideshare/ Slideshare:
Why is this important to BGI? Flickr cc: opensourceway
We produce data. (LOTS) 1 IlluminaHiSeq 2000 (+Truseq upgrade) = 600Gb/run (12 days) X 128 Hiseq= 6Tb/day = >2Pb/year = ~ 2000 Human Genomes/day
Coming soon… Large-Scale Data Journal/Database In conjunction with: Editor-in-Chief: Laurie Goodman, PhD Editor: Scott Edmunds, PhD Assistant Editor: Alexandra Basford, PhD www.gigasciencejournal.com
Our first DOI: 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 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.
E. Coli #crowdsourcing: the first tweenome? “On 2 June, Chinese scientists announced that they had deciphered the microbe's entire 5.2-million-base-pair genome and immediately made the DNA sequence available for researchers to download. Scores of scientists all over the world started poring over the data, assembling sequence fragments generated by BGI into a coherent genome, and comparing it to reference genomes for E. coli and other bacteria.” “The two announcements came on the second day of a U.K. meeting on applied bioinformatics and public health microbiology. Speakers and other attendees immediately started working on annotating the bacterial sequence provided by BGI. “In less than 24 hours we got the reads, the assembly, and the annotation. A good case study,” blogged Marina Manrique of era7 bioinformatics, a Spanish company that quickly did an automated analysis of the E. coli's genome.“
E. Coli #crowdsourcing: the first tweenome?
E. Coli #crowdsourcing: the first tweenome?
E. Coli #crowdsourcing: the first tweenome?
E. Coli #crowdsourcing: the first tweenome? “The way that the genetic data of the 2011 E. coli strain were disseminated globally suggests a more effective approach for tackling public health problems. Both groups put their sequencing data on the Internet, so scientists the world over could immediately begin their own analysis of the bug's makeup. BGI scientists also are using Twitter to communicate their latest findings.” “German scientists and their colleagues at the Beijing Genomics Institute in China have been working on uncovering secrets of the outbreak. BGI scientists revised their draft genetic sequence of the E. coli strain and have been sharing their data with dozens of scientists around the world as a way to "crowdsource" this data. By publishing their data publicy and freely, these other scientists can have a look at the genetic structure, and try to sort it out for themselves.”