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- 1. MongoDB and academia Jan Aerts, PhD Wellcome Trust Sanger Institute Hinxton, UK [email_address] @jandot
- 2. Disclaimer 1
- 3. Disclaimer 2
- 4. Acknowledgments MongoDB community Caren Brockington 10gen
- 6. transcriptomics genomics proteomics *omics
- 7. transcriptomics genomics proteomics *omics instantiationomics metabolomics spliceomics interactomics metallomics lipidomics orfeomics phenomics histomics
- 10. transitory
- 12. slow adoption of new technology (don't break anything that works)
- 13. data management = afterthought money
- 14. Who are the players?
- 27. 4. AceDB - A C aenorhabditis e legans d ata b ase object-oriented Author "Patel B" Full_name "Bala Patel" Laboratory CB Paper [cgc1011] Paper [cgc533] Mail "Laboratory of Molecular Biology" Mail "Hills Road, Cambridge" Fax "050 3456789" Paper [cgc533] Title "Yet more of those Genes" Journal "Cell Reports" Volume 3 Year 1993
- 29. Challenges in *omics - Where can MongoDB play a role?
- 30. explosion of data every researcher must be able to handle data
- 31. low stepping stone for bench-based scientists big data
- 34. Thank you! Questions? [email_address] @jandot http://saaientist.blogspot.com
Notas do Editor
- * not an expert. Further in the presentation I’ll explain why.
- * personal ideas/opinions; not Sanger
- My background
- there are hurdles for adoption in academia
- Why is there slow adoption?
- Why is there slow adoption?
- "need IT support for heavier work": set up MongoDB server => what if need sharded cluster? => investment from IT "creating legacy": if it's something that will be used after you're gone, you don't want to use a technology that is not supported or actively used within the organization
- Why is there slow adoption?
- Not really tab-delimited anymore because too structured Self-taught => simple scripting languages!
- Would benefit most. "bench-based scientists": are more and more learning perl and working with tab-delimited files to go to database: json looks more like how they think than having to cope with normalization steps in a relational database