RDAP 033111

A Few RDAP Thoughts Based on Experience with The RCSB Protein Data Bank www.rcsb.org Philip E. Bourne UCSD [email_address] 3/31/11 RDAP Summit 2011

Disclaimer
I am not an expert in institutional repositories
I happen to have helped develop and oversee a resource that I use for my own research
3/31/11 RDAP Summit 2011

What is the Protein Data Bank (PDB)?
The single community owned worldwide repository containing structures of publically accessible biological macromolecules
A resource used by ~ 200,000 individuals per month
A resource distributing worldwide the equivalent to ¼ the National Library of Congress each month
A bicoastal resource
1TB
3/31/11

PDB Total Contents by Year Number of released entries Year 3/31/11

Why We Think We Are Successful?
Number of visits and page views is growing faster than number of unique visitors

Metric of Success - A Research Tool for Influenza * http://www.cdc.gov/h1n1flu/estimates/April_March_13.htm Structure Summary page activity for H1N1 Influenza related structures * 3B7E: Neuraminidase of A/Brevig Mission/1/1918 H1N1 strain in complex with zanamivir Jan. 2008 Jan. 2009 Jan. 2010 Jul. 2009 Jul. 2008 Jul. 2010 1RUZ: 1918 H1 Hemagglutinin

Looking Back Over the Past 12 Years – In General
Everything was harder and took longer than we thought
There are a lot of politics associated with data
Emphasis has shifted from archive to + analytical tool to + educational tool
Consequently outreach is our most important yet least understood activity today
Staff needed to change accordingly
Policy has changed as well – some support for non-generic tools
Prorated our budget has decreased

Looking Back Over the Past 12 Years – Infrastructure
It took about 5 years to achieve and subsequently sustain 99.99% uptime
We have gone through 3 distinct architectural changes
Object model / Perl CGI
Object-relational model Enterprise Java
Redesign same model widget based UI
3/31/11 RDAP Summit 2011 Bluhm et al. 2011 Quality Assurance doi: 10.1093/database/bar003

Looking Back Over the Past 12 Years – Data & Data Management
About 25% of our budget has been spent on data remediation
Support yearly snapshots and versioning
Our ontology/data model has been a critical component of our workflow and data accuracy
The same model is too complex to facilitate wide adoption by others that use our data
Our data are such that we can retain redundant copies
Data objects are discreet and we assign DOIs
Constantly striving to have the user distinguish raw from derived data

Trends Today
Constant demand for better performance
Use of Web services (SOAP and now RESTful) are increasing
The uptake on the use of widgets has been slower than I hoped
Users are hankering after additional annotations of the data – working on database-literature integration
Mobile use is increasing
Web 2.0 services are in demand

Website Performance Improvements
Back End
Back-end tuning and use of multilevel caching in the areas of searches, query results, explorer pages and hierarchical views
Better performance and a more robust and scalable system
Front End
Cleaner JavaScript and CSS
Inline Image Data
Compressed Content (Gzip + Base 64)
Result: 25% - 40% increase in render performance

Literature Integration – The Dream
User clicks on content
Metadata and webservices to data provide an interactive view that can be annotated
Selecting features provides a data/knowledge mashup
Analysis leads to new content I can share
1. A link brings up figures from the paper 0. Full text of PLoS papers stored in a database 2. Clicking the paper figure retrieves data from the PDB which is analyzed 3. A composite view of journal and database content results 4. The composite view has links to pertinent blocks of literature text and back to the PDB 1. 2. 3. 4. The Knowledge and Data Cycle PLoS Comp. Biol. 2005 1(3) e34

Example of Interoperability: The Database View www.rcsb.org/pdb/explore/literature.do?structureId=1TIM BMC Bioinformatics 2010 11:220

Example of Interoperability – The Literature View From Anita de Waard, Elsevier

Semantic Tagging & Widgets are a Powerful Tool to Integrate Data and Knowledge of that Data, But as Yet Not Used Much Will Widgets and Semantic Tagging Change Computational Biology? PLoS Comp. Biol. 6(2) e1000673

Semantic Tagging of Database Content in The Literature or Elsewhere http://www.rcsb.org/pdb/static.do?p=widgets/widgetShowcase.jsp PLoS Comp. Biol. 6(2) e1000673 Semantic Tagging

PDBMobile
Fast, low bandwidth data access
First version supports iPhone OS
Future versions will support Android, Blackberry OS6 and others.
HTML 5-based web application
Client-side database stores data for offline-access
Tight integration with MyPDB
Objective: PDB Data Access On-The-Go

PDBMobile
Access to saved queries
Add/delete queries
Flag interesting entries
Add personal structure annotations
Tight Integration with MyPDB

Future
New views on the data for subclasses of user
New data deposition system – increase speed and accuracy while reducing costs
New types of analysis

Acknowledgements Funding Agencies: NSF, NIGMS, DOE, NLM, NCI, NCRR, NIBIB, NINDS, NIDDK 3/31/11 RDAP Summit 2011

RDAP 033111

by Philip Bourne on Mar 31, 2011

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RDAP 033111 — Presentation Transcript