A Cabinet of Web 2.0 Scientific Curiosities
Ian Mulvany, Product Development Manager, Nature Publishing Group
This talk takes a tour through science related web 2.0 efforts and discussesareas of the practice of science that can be impacted through web 2.0 approaches.
A video of this presentation will be posted at http://videolectures.net/
• Timo Hannay - Director Nature.com
• Jason Wilde - Publisher Physical Sciences
• Amanda Ward - Head of Platform Technologies
• Tony Hammond - Applications Architect
• Alf Eaton - Product Development Manager
• Euan Adie - Product Development Manager
• Gavin Bell - Product Development Manager
• Hilary Spencer - Product Development Manager
• Ian Mulvany - Product Development Manager
Some of the people involved
• Publishing Industry Facts & Figures
• Nature
• (Some) Issues that Web 2.0 can impact
• Identity and Authority
• Content Discovery
• Citizen Science
• Google Wave
• Ongoing Challenge
• The Future
Publishing Industry facts & figures
Funding sources Source: Research Information Network
Costs of research Source: Research Information Network
A significant contribution to the total cost of research is the timerequired for researchers to find the appropriate material for reading.There is an opportunity here to decrease such costs through creationof better tools for information discovery.
source http://www.rin.ac.uk/
Nov 4, 1869
• "It is intended, first, to place before the general public the grand results of scientific work and scientific discovery"
• "to aid scientific men ... by affording them an opportunity of discussing the various scientific questions that arise from time to time"
Norman Lockyer
Nature is principally a scientific communication company.We have to engage with the methods of communication that are important for science.
If we started today our starting point would naturally be the web, and not a print journal.
(Some) Publishing Milestones
• 1896, Wilhelm Röntgen, X-Rays
• 1925, Raymond Dart , Australopithecus africanus
• 1938, P Kapitza, Superfluidity
• 1953, J D Watson and F H C Crick, DNA
• 1985, J C Farman, B G Gardiner and J D Shanklin, Ozone Hole
• 1995, Michel Mayor and Didier Queloz, Extra Solar Planets
• 2001, Human Genome
Journal Evolution•1869 Journal Founded
•1899 Journal Makes a Profit
•1967 Peer Review
•1971 First Expansion (until 1974)
•1992 Nature Genetics
•1995 Holzbrink Ownership
•1995 Nature.com
•2004 Connotea
•2007 Nature Network
Peer review only introduced in 1967 in orderto deal with a backlog of about 3000 manuscripts.
Our current list of publications:http://www.nature.com/siteindex/index.html
Going beyond journals slide credit: Timo Hannay
2.0Web 2.0 is about getting and using data.There are two aspects, one is about lowering the barrier for participation, and the second is about data mining the resultant information in order to provide better services or tools.
This can also lead to a strong first mover advantage, as the network of dataor participation gets bigger the value in the network gets bigger
Web 1.0
DoubleClick Ofoto Akamai mp3.com Britannica Online personal websites evite domain name speculation page views screen scraping publishingCMSdirectories (taxonomy) stickiness
Web 2.0Google AdSenseFlickrBitTorrentNapsterWikipediabloggingupcoming.org and EVDBsearch engine optimizationcost per clickweb servicesparticipationwikistagging (folksonomy)syndication
photo: flickr keso
Google data mined the link structure of the web,
eBayʼs value comes from having such a large market. There is a buyer and sellerfor everything.
photo: flickr Dystopos
Wall mart uses realtime data for logistics.
DataTags, blogs, wikiʼs are incidental. They are tools for enabling the creationof more data.
image credit sam brown, explodingdog
Should be aware not to focus on just the technology
" " Building for Machines:" " " Semantic Markup" " " Well documented API's" " "" " Building for Humans:"" " " reduce the barrier to participation" " " increase the usefulness of serendipity and recommendation
http://panelpicker.sxsw.com/ideas/view/3691?return=%2Fideas%2Findex%2Finteractive%2Fq%3Abuilding+respectful
Stay Classy, SXSW: Building Respectful Software
make your software respectful http://panelpicker.sxsw.com/ideas/view/3691?return=%2Fideas%2Findex%2Finteractive%2Fq%3Abuilding+respectful
“ While scientists have gloried in the disruptive effect that the Web is having on publishers and
libraries, with many fields strongly pushing open publication models, we are much more resistant to letting it be a disruptive force in
the practice of our disciplines.”
Jim Hendler
Scientists resistAlthough the idea of a data driven approach should have an appeal to scientists,science changes slowly. There are a lot of implicit norms that are hard to change.
} 70% of scientists can’t
even be bothered to say
”yes”}
NIH requests all fundholders deposit their
manuscripts in PubMed Central
archive
4% compliance
}Nature offers to
upload to PubMed Central on behalf of authors with their permission
30% compliance
Scientists resistAn example of low participation in open data models is the low uptake of deposition of articles into pubmed.
Some Issues Where Web 2.0 May Help in Science
• Identity and Reputation
• Content Discovery
• Citizen Science
Humans
Machines
AcademicPublic
This is the framework that Iʼm going to be using to think about the topics in this talk. These are just two dimensions against which one can look at things, there are many other ways of looking at these issues. When putting together these slides I got interested in the tension between machine oriented efforts and human oriented efforts on the web. In addition web 2.0can have a big impact on public engagement with science, so I wanted to see if I could line up these two trends together.
Who am I?
Identity on the web is a fractured thing. It makes it difficult to manage all of the accounts that a person has, but on the other hand it makes it easyto present different personas to different online communities.
100, 000
Identity is a significant and growing issue in science. Each year India produces100, 000 postdocs.
Full names are often not revealed owing to caste discrimination.http://www.nature.com/nature/journal/v452/n7187/full/452530d.html
1.1 Billion > 129photo: Szymon Kochanski
129 surnames are shared by 1.1 billion people, 85% of the chinese population.
Generally identity is a self enforcing protocol.
Works most of the time, but ... Surgeon Liu Hui, padded his CV with publications by another researcher who shared his surname and initial, rose to become an assistant dean at Tsinghua University. Discrepancies were noticed and he was dismissed by the university in March 2006
Scopus Author ID
http://www.mluvany.net
Thompson Researcher ID
CrossRefContributor ID
6603325879
B-2805-2008
62.1000/182
These are currently the most commonly discussed options for managing identity within an academiccontext, each has pros and cons, and none has gained enough momentum to be universally adopted.
Nature is currently taking a wait and see approach, but we would like to see an open system gaining adoption.
Why is the issue of identity important, for reputation!
1619 - 1677
Henry Oldenburg, first secretary of the Royal Society, invented the practice of peer review with the Transactions of the Philosophical Society.
His own reputation suffered, he was jailed for being a potential dutch spy and thrown in the tower of london for a while.
Impact FactorTM
IF (year) = A/B
A = # of articles published in (year -1) + (year - 2)
B = # of citations to journal in year
Impact factor measures an average statistic of a single journal.80% of citations into a journal come from 20% of articles. General agreement that IF is a poor measure of individual article quality.
The citation network can be used to look at the relationship between journals.
doi/10.1371/journal.pone.0004803.g007Other metrics can also reveal the connections between the sciences,Bollen et al. used website access data from publisherʼs http logs to look at how people browed the literature. This gave a more rounded picturethan just looking at citations.
There is a move to now look instead of at journal level metrics rather
time
Citations
One thing that fascinates me about citations is that they are unidirectional.
Also there must be more citations than papers, and yet 85% of papers receive at most 1 citation.
time
Ideas
They can be used to study the flow of ideas forward in time.
Main-path analysis and path-dependent transitions in HistCite™-based historiograms Journal of the American Society for Information Science and Technology (forthcoming) Diana Lucio-Arias1 & Loet Leydesdorff2 Amsterdam School of Communications Research (ASCoR), University of Amsterdam Kloveniersburgwal 48, 1012 CX Amsterdam, The Netherlands.
This is the Main-Path Analysis technique, but as yet such analysis tends to be done on a case by case basis.
1 Cox, D.R. (1972) Regression models and life-tables. J. Roy. Statist. Soc. B 34:
21 000
Some papers act as a kind of black hole for citations, they get into the literatureand get cited and cited and cited.
This paper has over 21 000 citations.
The mis-citations to this paper have a h-index of 12, a level that Hirsch had concluded “…might be a typical value for advancement to tenure…”
http://network.nature.com/people/boboh/blog/2008/06/24/outdone-by-mis-prints
foto: flickr Naveen Roy
Weaving in more value
easy
easy
easy
hard mining
cont
ribu
ting
Semantic Web
plain text, emailsTwitter
academic papers
MicroFormatsmicroformats
hyperlinks
tagsviews
citations?
(semantic web)
PDF sucks, academic papers are hard to create and PDF is hard to extractany useful information from in a programatic way.
Humans
Machines
AcademicPublic
Peer Review
Article Writing
Author Identification
Article Publishing
This is where most of the academic publishing workflow currently lives,it is manual work that can only be done by highly trained experts.
XML
At nature we are consolidating all of our article content into a sigle XMLdatabase.
Building a delivery infrastructure
http://www.flickr.com/photos/zhzheka/
We then deliver this content via print, RSS, paper, search queries, to a host of endpoints.
XML
Blue - DoneGreen - Done within the last yearYellow - coming to completionRed - depreciated
http://www.flickr.com/photos/cherieking/
Extensible ContainersWe want to be able to extend the data that we deliver.
Medline
XML
+ MESH
We pull in MESH terms for our articles from medline post-publication.
Case Study: Nature Chemistry
We have started extracting entities from our Nature Chemistry journal, andwe hope to roll this program out to other journals.
NH NH2
HO
Serotonin
CAS – 50-67-9
SMILES – Oc1cc2c(cc1)ncc2CCN
InChI – 1S/C10H12N2O/c11-43-7-6-12-10-2-1-8(13)5-9(7)10/h1-2,5-6,1 2-13H,3-4,11H2
InChIKey – QZAYGJVTTNCV MB-HFFFAOYSA-N
Chemistry is a visual science! moleculescas #s first appeard in 1907, is owned by ACS, contains no semanticssmiles 1987, not unique to a compoundInchi/Inchikey 200/2005
Author fileAuthor file
CDXCDX
GIF/PNGGIF/PNG
Compound Data
3D
Enhanced compound pages offer:Chemdraw fileCML fileView structure in 3DSynonymsChemical formulaMolecular WeightElemental AnalysisInChI and InChIKeySMILES stringLinks to external databases
InChi
PubChem
ChemSpider
We can start to link from articles into databases, and vice versa.
XML
Medline
+ MESH
PubChem
ChemSpider
TXT
UIMA
xpath
Schematic of our current entity extraction workflow,
Initially we are extracting chemical and compound names form Nature Chemistry articles.
We have a bespoke interface that allows editorial curation of the annotations.
<dl class="meta"> <dt>InChI</dt> <dd class="inchi">InChI=1/C10H14N5O7P.2Na/c11-8-5-9(13-2-12-8)15(3-14-5)</dd>
</dl>
Making the markup of the bold numbers makes the onlineversion of the paper more semantic,
Organise metadata: create good architecture so generated data can be easily reused across a range of applications.
http://www.flickr.com/photos/timecollapse/
We hope to be able to extended the types of entities thatwe are extracting from our articles.
Expanding the annotation of journal articles from Nature Chemistry to Nature Chemical Biology and then to all NPG journals
Creating a central NPG database of compounds and related journal articles
InChI=1S/C32H16N8.Cu/c1-2-10-18-17(9-1)25-33-26(18)38-28-21-13-5-6-14-22(21)30(35-28)40-32-24-16-8-7-15-23(24)31(36-32)39-29-20-12-4-3-11-19(20)27(34-29)37-25;/h1-16H;
Cu
N
N
N
N
N
NN
N
This then makes the article a more integrated object, withlinks to databases, entities and the products of scientific research.
There are many curated databases that look for information about domain specific results in the literature. An example is flybase that collects information about results using the model organism Drosophila.
Wormbase does the same for C. elegans.Both require a large amount of human curating. Having the body of scientificliterature be semantically annotated should help with this kind of curation.
Site such as Chemspider and Crystal Eye demonstrate what can be done though data mining the literature.
So we have moved into a situation in which our scholarly networkcan now connect to entity databases, rather than just to articles.
Humans
Machines
AcademicPublic
Peer Review
Article Writing
Author Identification
Article Publishing
Entity Extraction
Article publishing hopefully becomes enriched through semantic markup andentity extraction.
Getting Socialphoto credit: flickr mcgeez
We can go beyond published articles and entities and look at both other published artefacts and the social annotation thatis associated with them.
The amount of grey literature available in physics has grown steadily, as displayed by submissions to the Physics ArXiVe.
Nature Precedings was the first preprint server for the life sciences.It also includes the ability to vote and comment on submissions and provides each submission with a unique identifier.
PLoS have launched PloS Currents: Influenza, based on top of Google Knol.Both Preceedings and Currents have editorial curation of content, and alloweasy publication of objects such as posters, proceedings papers and white papers.
Connotea is Natureʼs social bookmarking service for academics.
It can extract citation information form a range of online resources, savingthe author the effort of manually entering this information.
Title
DateAuthor
PMID/DOITags
The Kind of Information that we can capture with Connotea includes full citation informationUsage patterns, (when did an item get added to our DB, how many times has it been added)Extra meta-data such as tagsPotentially social network information, how many of my friends have added this item?
Total number of tags
Total number of unique tags
Growth in usage of the service has been steady
And it displays the characteristic power law behaviour of an online network.
11032
It supports data export via txt, rdf, BibTex, RIS, and EndNote
RDF HTML
RSS TXT
http://www.connotea.org/user/IanMulvany
http://www.connotea.org/users/tag/scifoo
http://www.connotea.org/user/IanMulvany/tag/scifoo
http://www.connotea.org/user/IanMulvany/tag/science2.0+citation
http://www.connotea.org/user/IanMulvany/tag/science
Example of calls to query the data, html output
http://www.connotea.org/data/user/IanMulvany
http://www.connotea.org/data/users/tag/scifoo
http://www.connotea.org/data/user/IanMulvany/tag/scifoo
http://www.connotea.org/data/user/IanMulvany/tag/science2.0+citation
http://www.connotea.org/data/user/IanMulvany/tag/science
Example of API calls
There are plenty of other such services currently available.Interestingly Fuzzy has the most semantically enabled technology, but is one of the least used.
A few start-ups are redefining the academic paper management space, Papers is a mac based “iTunes” for Pdfs.
Mendeley provides the same kind of features, with a Last FM metadata scrobbling model.
This allows one to see data on what is being read in Mendeley libraries.This starts to open up a new layer of information about the impact of papersthat goes beyond what can be captured by the impact factor.
Nature Network
Online social communities also allow us to begin to capture conversations about science.NPG launched Nature Network in 2009 and is one of the most active online forums forthe discussion of science.
It has specific features to allow members to track the conversations that they have participated in.
There are 3 main local hubs, but we track the geographic location of members,and try to connect people with other members in their neighbourhood.
Bringing things together
photo: flickr Thomas HawkQ: How do you manage all of these streams of information?A: Aggregation is one answer (probably not the only answer).
PostGenomic aggreagtes science blogs and picks out popular items.
Nature blogs finds blog posts that discuss scientific articles.Science Blogs and researchblogging.org do much the same.
Scinitalla is another Nature product that creates recommendations based on a users reading habits.
Friend Feed aggregates discussions around resources from difference sources.It has seen widespread adoption by the scientific digerati, the life scientistsroom is one of the most active.
People are using these rooms to have real-time conversations around real-timeevents. This broadcasts an event and the conversions around an event to the web. It enables real time distant participation.
streamosphere.nature.com/preview.php is an aggregator for discussions on twitter, friendfeed some other lightweight user signals. It again aggregates over a curated list of sources.
So now we can see a world in which the article is no longer theonly digital artefact of note. Much more of the process of scienceis becoming visible through online engagement of scientists.
Humans
Machines
AcademicPublic
Peer Review
Article Writing
Author Identification
Article Publishing
Entity Extraction
Science Blogging/Tweeting/Social Communities
SIOC
Social media as it exists now is problematic- effervescent- closed- siloed- unstructured
Tools like SioC, an ontology for social media, can help draw this layer of informationto the machine.
Citizen Science
Seti@home
Folding@home
“Thinking@home”
One kind of participatory science is getting users to donate their hardware.
10 000 sheep, Aaron Koblin, 2006
You can also build interfaces to people, e.g. the Mechanical Turk.The sheep market created by Aaron Koblin in 2006 by getting 10 000 turks to draw sheep.
+ =Cheap Sentiment Analysis
http://blog.doloreslabs.com/2009/05/the-programming-language-with-the-happiest-users/
Two people checking a subset of tweets can data mine twitter for you.We used crowdsourcing to analyse all of the comments to PlOS articles.
But another more interesting version is to get people in interact directly with your data!" stardust at home" http://stardustathome.ssl.berkeley.edu/about.php" http://folding.stanford.edu/" http://fold.it/portal/" citizen science blog" http://citizensci.com/" great backyard bird count" http://www.birdsource.org/gbbc/
You need to make it engaging, like the Fold it Project, or Galaxy Zoo.Even if machines and machine learning could answer some of these questions(like image analysis of galaxy rotation), humans can do it now. You get the scientificbenefit now, you engage the public with science now.
Humans
Machines
AcademicPublic
Peer Review
Article Writing
Author Identification
Article Publishing
Entity Extraction
Science Blogging/Tweeting/Social Communities
Seti at HomeFolding at home
Galaxy ZooStardust at home
Peer to Patent
Fold it
RDFTurk SIOC
Now we have an interesting picture, but most of the arrows in this picturepoint down. Where are the efforts to make computers more friendly to people?One pointer to how that will happen in the future is Google Wave.
Google Wavephoto credit: flickr prgibbs
New product from Google, launching in September 09
For the definitive guide to google wave look at:http://www.youtube.com/watch?v=v_UyVmITiYQ
wave
Currently there is a lot of hype, and not much access to the product.
Robot
Gadget
Embed
App Engine
html5
Container(blogger)
Of interest for developers are the APIʼs the wave exposes.
Naively one can think of Robots as allowing two way communication witha wave, Gadgets for pulling content into a wave, and the Embed gadget as a tool for pushing waves into other contexts, such as blogs or wikis.
Importantly Google intends to open source the server code allowing anyone to run a wave server, much as anyone canrun an email server.
Email Thread?Document?
IM? Gallery?Group?
Game Server?
? ? ? ?
The metaphors for what wave is have not settled down yet.
This is a consequence of the current interface, new interfaces will be possible.
The key is that Wave enables exposing 3rd party APIʼs to the user in a totally opaque way. It hides the details, and makes it easier for peopleto interact with computers.
image credit sam brown, explodingdog
Finally we can live in a a world where computers and humans can be friends.
WAVE
Humans
Machines
AcademicPublic
Peer Review
Article Writing
Author Identification
Article Publishing
Entity Extraction
Science Blogging/Tweeting/Social Communities
Seti at HomeFolding at home
Galaxy ZooStardust at home
Peer to Patent
Fold it
RDFTurk SIOC
• http://code.google.com/p/helpmeigor/
• http://github.com/cameronneylon/ChemSpidey/tree/master
• http://github.com/IanMulvany/janey-robot/tree/master
Some scientific robots have already been created.
Visualisation
photo credit: flickr mrcthepcInsight requires good visualisation techniques.
Eigenfactor.orgAn example of great visualisation of the relationships between journals.
Stamen.com have created some of the best data visualisations on the web.
Map tube is an interesting project allowing the mashup of geo-data.
http://iphylo.blogspot.com/2009/08/mammal-tree-from-wikipedia.html
Good visualisation provides insight, such as these visualisations of the phylogenic nodes present in wikipedia.Avian flu maps http://declanbutler.info/blog/?p=58 is another great example.
Text
biological pathways
http://www.reactome.org/
Itʼs a hard problem, some data sets are big and complicated. http://www.reactome.org/ tries to visualise pathways in thehuman genome.
The FutureWhere are we heading to?
Final thoughts
• Publishers will continue to exist but will become communication companies
• They must learn to treat the web as a network, not a distribution channel
• Journals should be more like databases, and vice versa
• Publishing and broadcasting are merging (or colliding?); to some extent, he same goes for publishing and software
• The disruptive forces include new economics, lower barriers to entry, and a complex competitive environment
Some predictions for scientific publishing.
Final thoughts
• Mobile devices as sensors e.g. noisetube.net
• Rich web applications building on HTML 5 will be a real competitor to the desktop
• The problem of scientific identity will be solved
• We will have a scientific recommendation engine that works
• Frameworks for programming genetic code, much like we now program computer code, will be available
• Computers will do much of the heavy lifting of science
• http://www.nature.com/nature/focus/arts/futures
Some predictions for science.
“The future is already here. It's just not very evenly distributed” - William GibsonSci Foo is an annual weekend un-conference that brings together people doing interesting things at the interface between science, technology and culture. Looking at what these people are doing gives us a hint of things to come.
http://www.nature.com/scifoo/index.html
http://www.connotea.org/user/IanMulvany/tag/active-ss
@IanMulvany
http://www.slideshare.net/IanMulvany
http://blogs.nature.com/wp/nascent/
Extra image Acknowledgements
• http://www.flickr.com/people/matthewfield/ Matthew Field, Lots Of People
• http://www.flickr.com/people/garthimage/ Garth Burgess, Southampton Docks
• http://13c4.wordpress.com/ Pamela Bumstead, 50 reasons not to • http://www.flickr.com/people/mayeve/ clock• http://www.flickr.com/people/sublimelyhappy/ Sarah Gerke, Rolodex• http://www.flickr.com/people/thedepartment/ Kate Andrews, Library• http://www.flickr.com/people/sirstick/ Alexander Hauser, new mail• http://commons.wikimedia.org/wiki/User:CJ The Thinker• Gavin Bell, helpful discussions about OpenID
http://www.flickr.com/people/marcelgermain/The End
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