Data sharing and Quixote meeting (Zaragoza)

I am talking an a few minutes to a group of chemists, other scientists, computational scientists, informatics specialist, IR managers, etc. in ZCAM (computational chemistry) in Zaragoza. This is a very exciting project and we hope to not only talk, but actually do things today.

Rather than use Powerpoint I blog my materials. A lot is present in previous blog posts, but this adds an overview of what I might say, and some of the materials I might use. What I actually say depends as always on what has already been said, and not said and the interests of the people present.

My motivation

[With ChEBI, Christoph Steinbeck] Compute properties (spectra, conformations, reactivity) of compounds in the human metabolome.

Quixote…

• Open to all – no central ownership (cf. Wikipedia). Not my project, but OUR
  
• Very cost-effective with a high potential for success
  
• A long-tail discipline, with discrete data.
  

Data Sharing

• Must be driven by scientists (researchers, editors)
  
• Should be domain-specific
  

Why share data?

• To promote MY work and receive credit (data citation)
  
• To save MY work
  
• To share MY datasets with ME (i.e. look for paterns, correlation)
  
• To share MY datasets with MY colleagues
  
• To share MY datasets with the world
  
• To improve methodology
  
• To validate science
  

What are the problems?

• People want to use their results as intellectual capital
  
• People can sell their data for money
  
• It takes effort and money
  
• It challenges established interests (priesthood, market)
  
• Chemists are more conservative than many disciplines
  

Why/how will it happen?

• Because individuals (e.g. grad students) find it useful
  
• Because groups find it useful
  
• Because journals find it useful enough to mandate
  
• Because funders require it
  
• Because developers (e.g. programs)find it useful
  

What should we do today?

• Make a wish list for compchem data sharing
  
• What is possible right now?
  

Resources related to Data Sharing

Recent blogs by PMR

• criteria-for-datasharers/
  
• data-repositories-for-long-tail-science-setting-the-scene/
  
• data-publication-some-replies/
  
• publishing-data-the-long-tail-of-science/
  

  Data repositories
  

• Dryad A repository for data, especially biosciences
  
• 2011/07/28/uk-parliament-report-supports-dryad-and-data-access/
  
• JISC and Dryad
  

  
  

• How to deposit in Dryad
  
• FigshareMark Hahnel’s commuity for sharing figures and data
  
• Dataverse – publicly visible (not fully open) datasets in social science
  
• dataverse deposit-terms
  
• Authors in Figshare
  
• Figures in Figshare
  
• An author in Figshare
  
• Proliferation_of_PBMCs,_expressed_as_stimulation_indices_ in Figshare
  
• Polymerase_chain_reaction_data_from_matrix_metalloproteinase in Figshare
  

  Validation of Science requires data
  

• http://pubs.acs.org/doi/suppl/10.1021/jo200117p
  
• Spectral data should be digital Mestrec blog (NMR software) argues that if the data were digital potential fraud would have been detected
  
• The PDF of controversial data This data cannot be easily understood by machines so validation is impossible
  

  CML, Quixote and Crystaleye Data sharers
  

• Crystaleye home page
  
• Crystaleye2 data sharer
  
• Quixote data sharer
  
• CML resources (dictionaries and conventions)
  
• COMO Chem Eng knowledgebase
  

SPARQL query for Crystaleye2

[This will be used interactively with crystaleye2. Try it under SPARQL. It’s very new. If it works, congratulate Sam.

If it fails maybe the server is down, or blame me.]

Report only structures with R values less than 0.02:

PREFIX cif: <http://www.xml-cml.org/dictionary/cif/>

SELECT ?uri ?rfactor {

?uri cif:refine_ls_r_factor_gt ?rfactor

FILTER (?rfactor < 0.02)

}