Successfully reported this slideshow.
We use your LinkedIn profile and activity data to personalize ads and to show you more relevant ads. You can change your ad preferences anytime.

Research Data Alliance March 19, 2013

735 views

Published on

Description of best practices as developed through work with the Protein Data Bank and the Public Library of Science

Published in: Education
  • Be the first to comment

  • Be the first to like this

Research Data Alliance March 19, 2013

  1. 1. Best Practices for Data: A Biologists View Philip E. Bourne UCSD pbourne@ucsd.eduResearch Data Alliance March 19, 2013 1
  2. 2. My Perspective is Drawn from Being: A data producer and a data user* An overseer of data curation efforts A database provider (PDB & IEDB) Suspicious of workshop reports, data standards bodies … A supporter of data publication An open access journal founder Opinionated Research Data Alliance March 19, 2013 2
  3. 3. PLoS Biology October, 2003 PLoS Medicine October, 2004PLoS Community Journals October, 2007June-September, 2005 PLoS ONE December, 2006 Research Data Alliance March 19, 2013 3
  4. 4. The RCSB Protein Data Bank Its a global community Its 42 years old It’s a diverse set of users Single international archive for all information about the structure of large Depositors biological molecules 300,000 unique IP’s per month 300 simultaneous users Users 7 structures (data objects) downloaded every second Research Data Alliance March 19, 2013 4
  5. 5. PDB Data AreImportant Structure Summary page activity for H1N1 Influenza related structures Jan. 2008 Jul. 2008 Jan. 2009 Jul. 2009 Jan. 2010 Jul. 2010 3B7E: Neuraminidase of A/Brevig Mission/1/1918 H1N1 strain in complex with zanamivir 1RUZ: 1918 H1 Hemagglutinin * http://www.cdc.gov/h1n1flu/estimates/April_March_13.htm 5
  6. 6. Agenda Trends we are seeing What we have learned What needs to change re data* What we are planning to facilitate change * Personal opinion Research Data Alliance March 19, 2013 6
  7. 7. Worldwide Protein Data Bank www.wwpdb.orgSo What Are the Trends? Research Data Alliance March 19, 2013 7
  8. 8. Trends – Data Access Trend Action  Constant demand for  Attention to SEO, better performance memcache, (damn Google) denormalization, query interfaces  Use of Web services increasing (dropped SOAP and now all  All data exposed RESTful)  Limited use of widgets Will Widgets and Semantic Tagging Change Computational Biology? PLoS Comp. Biol. 6(2) e1000673So what are the trends? Research Data Alliance March 19, 2013 8
  9. 9. Guiding Users to Specific Results Search Suggestions Smart Suggestions Sequence SMILES stringMouse over for more details Link to Advanced Search
  10. 10. Trends - General: Mobile Devices  Mobile devices well suited to deploy educational materials (Molecule of the Month)  Mobile device users expected to exceed desktop users by 2014 http://www.morganstanley.com/institutional/techresearch/pdfs/Internet_Trends_041210.pdfSo what are the trends? Research Data Alliance March 19, 2013 10
  11. 11. Trends PDB: Support for PDB MobileBrowseMolecule of Browse iPadthe Month Simple iPhone Interactive searcharticles search iPod 3D viewer* resultsSo what are the trends? *NDKMol, Takanori Nakane, Kyoto University
  12. 12. Trends: Follow the Social Networks 12So what are the trends?
  13. 13. Trends: Reduced Footprint and VM  Legacy Hardware – Deploy on the Open Science Grid SDSC Rutgers Old Old New NewSo what are the trends? Research Data Alliance March 19, 2013 13
  14. 14. Trends: Global Load Balancing  Why is it important? – Enables us to better serve our users by providing increased reliability and quicker results  How will it be done? – By more evenly allocating our resources at Rutgers and UCSD – By directing users to the closest siteSo what are the trends? Research Data Alliance March 19, 2013 14
  15. 15. Trends: Complexity Begats Use Number of released entries Year We manage to handle Usage increases, increased volume and community broadens, complexity at a lesser cost applications expandSo what are the trends? 15
  16. 16. Worldwide Protein Data Bank www.wwpdb.orgSo What Have we Learnedthat is Relevant to RDA? Research Data Alliance March 19, 2013 16
  17. 17. Its All About Trust Trust in the data is perhaps our biggest achievement PDBSo what have we learned? Research Data Alliance March 19, 2013 17
  18. 18. Its All About Trust  Trust is like compound interest  Comes from listening  Comes from engaging the community in every aspect of the process  Comes from data consistency and level of annotation  Comes from responsiveness  Comes from the quality of the delivery serviceSo what have we learned? Research Data Alliance March 19, 2013 18
  19. 19. Data Quality Begats Trust  About 25% of our budget has been spent on data remediation  Support for versioning hence the copy of record  Our ontology/data model has been a critical component of our workflow and data accuracy  Until recently the same data model was too complex to facilitate wide adoption by others that use our dataSo what have we learned? Research Data Alliance March 19, 2013 19
  20. 20. Its All About People Curators are the Unsung Heroes • They really should do more to promote themselves • Institutions must do more to respect their effortsSo what have we learned? http://collections.plos.org/ploscompbiol/biocurators.php 20
  21. 21. Its All About People The Users  Constantly striving to have the user distinguish raw from derived data  All data are not created equal but the user thinks soSo what have we learned? Research Data Alliance March 19, 2013 21
  22. 22. Its All About People The Global Personalities 22 Research Data Alliance March 19, 2013So what have we learned?
  23. 23. Its NOT All About Institutions  As far as I am aware no data standards body has directly influenced anything we have done in 15 years of running the PDB  The structural biology community created a very successful data sharing plan long before funding bodies didSo what have we learned? Research Data Alliance March 19, 2013 23
  24. 24. It is About Openness  There are no restrictions on the usage of the data beyond attribution  The PDB runs exclusively on open source software  We maintain and contribute to the Biojava repository  We need to be transparent about data usageSo what have we learned? Research Data Alliance March 19, 2013 24
  25. 25. Worldwide Protein Data Bank www.wwpdb.orgSo What Needs to Change re Data? Research Data Alliance March 19, 2013 25
  26. 26. That All Data Are Created Equal Must End  We need to understand how data are used  Sustainability is not more money from the funding agencies its about business models  Reductionism is not a dirty word  We need to do more On the Future of Genomic Data Science 11 February 2011: with the long tail vol. 331 no. 6018 728-729So what needs to change? Research Data Alliance March 19, 2013
  27. 27. Institutions That Generate Data Must Play a Greater Role  We need institutional data sharing plans  We need data scientists to be better recognized by institutions – its not all about papers – this implies new metricsSo what needs to change? Research Data Alliance March 19, 2013 27
  28. 28. The {Lack of} Distinction Between Data and Knowledge Needs to be Better Appreciated • The PDB paper has been cited 14,000 times • No one has ever read it • Some PDB datasets have 1,000’s of downloads • These data are not associated with publications 28So what needs to change?
  29. 29. We Need to Think More About the Questions We Wish to Answer Rather than Simply Being Able to Retrieve The Data  Data are stove piped – Broad questions are difficult to answer  Usage alone can be used to answer questionsSo what needs to change? Research Data Alliance March 19, 2013 29
  30. 30. Worldwide Protein Data Bank www.wwpdb.orgWhat Will We Contribute GoingForward? Research Data Alliance March 19, 2013 30
  31. 31. 0. Full text of PLoS papers stored 4. The composite view has The Knowledge and Data in a database links to pertinent blocks of literature text and back to the PDB Cycle 4. 1. User clicks on content 2. Metadata and webservices to data 1. provide an interactive 3. A composite view of 1. A link brings up figures from the paper journal and database view that can be content results 3. annotated 3. Selecting features provides a data/knowledge mashup 2. 4. Analysis leads to new 2. Clicking the paper figure retrieves data from the PDB which is analyzed content I can share PLoS Comp. Biol. 2005 1(3) e34What will we contribute? Research Data Alliance March 19, 2013 31
  32. 32. PLOS Data Papers  Individual repositories register their metadata which includes access statistics, commentary etc. – DataCite is a beginning  Identify identical data objects and their respective metadata for comparative analysis  Funders support registration  Publishers support registrationWhat will we contribute? Research Data Alliance March 19, 2013 32
  33. 33. PLOS Data Papers Research Data Alliance March 19, 2013 33
  34. 34. The PDB as an App Store  The App model – Think of it operating on the PDB content base rather than a mobile device  Advantages – Enriches the questions the PDB can answer – Creates an even greater sense of community – Simple and consistent user interface – Needs to pass some quality control – Has a rating and reward systemWhat will we contribute? Research Data Alliance March 19, 2013 34
  35. 35. Acknowledgements  www.force11.org – Tim Clark – Ivan Herman – Paul Groth – Ed Hovy – Maryann Martone – Cameron Neylon – David Shotton – Anita de Waard  www.plos.org  Beyond the PDF  Many others Funding Agencies: NSF, NIGMS, DOE, NLM, NCI, NCRR, NIBIB, NINDS, NIDDK Research Data Alliance March 19, 2013 35

×
https://www.slideshare.net/pebourne/rda032013
www.slideshare.net
crawl=CC-MAIN-2018-30
186696
application/http; msgtype=response
sha1:XEZE3T3MNRLCQ4HC6QVVNTPSWAQJS6EA
<urn:uuid:0f97cce9-0b2e-4f5d-a808-e7ba8c3e71c3>
2018-07-18T22:51:17Z
108.174.10.19
text/html
sha1:R4DC3J5HCABU7JAVFUHVWF3L6XE5ZYDV
<urn:uuid:71d24392-aa50-4138-9954-96338e48c2f6>
https://www.slideshare.net/pebourne/rda032013
response
<urn:uuid:816419b8-0ee1-4fef-acbd-120111c14d53>
robots: classic
hostname: ip-10-81-219-4.ec2.internal
software: Nutch 1.6 (CC)
isPartOf: CC-MAIN-2018-30
operator: Common Crawl Admin
description: Wide crawl of the web for July 2018
publisher: Common Crawl
format: WARC File Format 1.0
conformsTo: http://bibnum.bnf.fr/WARC/WARC_ISO_28500_version1_latestdraft.pdf