Umich Grand Rounds

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University of Michigan, Health Informatics Grand Rounds presentation, 13 January 2009.

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Umich Grand Rounds

  1. 1. university of michigan health informatics grand rounds ann arbor, mi 13 january 2009 john wilbanks creative commons / science commons
  2. 2. metcalfe’s law
  3. 3. “information wants to be free”
  4. 4. “if free, and technically enabled, information trends towards connectivity and increased value”
  5. 5. information knowledge?
  6. 6. digitization changes knowledge journals, databases, ontologies, wikis, annotations...
  7. 7. why no disruptions like Metcalfe’s Law for knowledge?
  8. 8. disruptive processes can’t be planned in advance.
  9. 9. disruptive processes can’t be planned in advance. planned innovation tends to be incremental, and slow.
  10. 10. disruptive processes can’t be planned in advance. planned innovation tends to be incremental, and slow. ...and not innovative.
  11. 11. 1. stable systems are resistant to change on multiple levels.
  12. 12. © creative expression
  13. 13. the container, not the facts.
  14. 14. the container, not the facts. © locks the container. but
  15. 15. IGFBP-5 plays a role in the regulation of cellular senescence via a p53-dependent pathway and in aging-associated vascular diseases
  16. 16. IGFBP-5 plays a role in the regulation of cellular senescence via a p53-dependent pathway and in aging-associated vascular diseases
  17. 17. indexing: disallowed. http://orpheus-1.ucsd.edu/acq/license/cdlelsevier2004.pdf
  18. 18. creative work?
  19. 19. 40 minutes per year
  20. 20. nih policy.
  21. 21. Dorothea Salo, http://cavlec.yarinareth.net/2008/10/31/miniature-disasters-and-minor-catastrophes/
  22. 22. the existing system is robust against disruption the existing system is robust against disruption
  23. 23. this is how evolved systems resist change: at multiple levels, with multiple fail-safes.
  24. 24. 2. the “digital commons” presents us with a potential way out.
  25. 25. “the commons”
  26. 26. rivalrous v. non-rivalrous
  27. 27. small contributions. snap-together licensing. technically enabled.
  28. 28. “the commons”
  29. 29. “intellectual property”
  30. 30. knowledge rights
  31. 31. Copyright All Rights Reserved No Rights Reserved
  32. 32. Copyright All Rights Reserved No Rights Reserved
  33. 33. licensing step 1: choose conditions Attribution Share Alike Non-Commercial No Derivative Works
  34. 34. Ported to 50 Jurisdictions
  35. 35. 160M
  36. 36. 160M
  37. 37. Photo: Dennis Stefani, (c) Mrs. Me, Inc., 2008, made available under a CC BY-NC-ND license
  38. 38. CC BY-NC-SA
  39. 39. 3. our knowledge containers are outdated.
  40. 40. solves the legal problem
  41. 41. but not the container problem.
  42. 42. over 200 years at one paper/day
  43. 43. what you want is a list of genes. not a list of documents.
  44. 44. building a web for data: the “semantic web”
  45. 45. causes drink coee feel awake
  46. 46. we need a Domain Name System for concepts: 192.168.1.1 http://sciencecommons.org coffee http://ontology.foo.org/coffee
  47. 47. http://ontology.foo.org/causes causes drinking coffee feel awake http://ontology.foo.org/drinking coffee http://ontology.foo.org/feel awake h
  48. 48. bed person get out of bed located at last subevent does not want wants get out of bed after causes drink coee feel awake first subevent subevent causes feel jittery open eyes after after make coee pour coee pick up cup drink is a is for located in coee cafe property of often near often near wet cup sugar
  49. 49. databases as unique entities, instead of nodes in a network
  50. 50. “packages”
  51. 51. scalable aggregation
  52. 52. 4. accelerating the scientific cycles via the commons.
  53. 53. whichever we choose, we need some way for computers to help us theorize, and to leverage the work of others (either to build on or to use in creative anarchy)
  54. 54. exponential content growth
  55. 55. our brain capacity 5.00 3.75 2.50 1.25 0 1990 1994 1998 2002
  56. 56. but if we can work together...
  57. 57. Open Access Content
  58. 58. making knowledge legally and technically available for re-use and composition into new knowledge.
  59. 59. c 1000 journals under CC image from the public library of science licensed to the public under CC-BY 3.0
  60. 60. running policy code (w. SPARC)
  61. 61. + + + is it legal? + + + + +
  62. 62. conflicts with the protection instinct
  63. 63. conflicts with the protection instinct the protection instinct is sometimes an instinct to protect “freedom”
  64. 64. “a biologist would rather share her toothbrush than her data.” - carole goble
  65. 65. Open Source Data Integration
  66. 66. a repository of ontologies, namespaces, and integrated databases.
  67. 67. e pluribus unum.
  68. 68. uses: “DNS for life sciences” API to the public domain enhanced document markup activity center analysis
  69. 69. we can transform complex queries into links Mesh: Pyramidal Neurons prefix go: http://purl.org/obo/owl/GO# prefix rdfs: http://www.w3.org/2000/01/rdf-schema# prefix owl: http://www.w3.org/2002/07/owl# prefix mesh: http://purl.org/commons/record/mesh/ prefix sc: http://purl.org/science/owl/sciencecommons/ prefix ro: http://www.obofoundry.org/ro/ro.owl# select ?genename ?processname Pubmed: Journal Articles where { graph http://purl.org/commons/hcls/pubmesh { ?paper ?p mesh:D017966 . ?article sc:identified_by_pmid ?paper. ?gene sc:describes_gene_or_gene_product_mentioned_by ?article. } graph http://purl.org/commons/hcls/goa { ?protein rdfs:subClassOf ?res. Entrez Gene: Genes ?res owl:onProperty ro:has_function. ?res owl:someValuesFrom ?res2. ?res2 owl:onProperty ro:realized_as. ?res2 owl:someValuesFrom ?process. graph http://purl.org/commons/hcls/20070416/classrelations {{?process http://purl.org/obo/owl/obo#part_of go:GO_0007166} union GO: Signal Transduction {?process rdfs:subClassOf go:GO_0007166 }} ?protein rdfs:subClassOf ?parent. ?parent owl:equivalentClass ?res3. ?res3 owl:hasValue ?gene. } graph http://purl.org/commons/hcls/gene { ?gene rdfs:label ?genename } graph http://purl.org/commons/hcls/20070416 { ?process rdfs:label ?processname} }
  70. 70. DRD1, 1812 adenylate cyclase activation ADRB2, 154 adenylate cyclase activation ADRB2, 154 arrestin mediated desensitization of G-protein coupled receptor protein signaling pathway DRD1IP, 50632 dopamine receptor signaling pathway DRD1, 1812 dopamine receptor, adenylate cyclase activating pathway DRD2, 1813 dopamine receptor, adenylate cyclase inhibiting pathway GRM7, 2917 G-protein coupled receptor protein signaling pathway GNG3, 2785 G-protein coupled receptor protein signaling pathway GNG12, 55970 G-protein coupled receptor protein signaling pathway DRD2, 1813 G-protein coupled receptor protein signaling pathway ADRB2, 154 G-protein coupled receptor protein signaling pathway CALM3, 808 G-protein coupled receptor protein signaling pathway HTR2A, 3356 G-protein coupled receptor protein signaling pathway DRD1, 1812 G-protein signaling, coupled to cyclic nucleotide second messenger SSTR5, 6755 G-protein signaling, coupled to cyclic nucleotide second messenger MTNR1A, 4543 G-protein signaling, coupled to cyclic nucleotide second messenger CNR2, 1269 G-protein signaling, coupled to cyclic nucleotide second messenger HTR6, 3362 G-protein signaling, coupled to cyclic nucleotide second messenger GRIK2, 2898 glutamate signaling pathway GRIN1, 2902 glutamate signaling pathway GRIN2A, 2903 glutamate signaling pathway GRIN2B, 2904 glutamate signaling pathway ADAM10, 102 integrin-mediated signaling pathway GRM7, 2917 negative regulation of adenylate cyclase activity LRP1, 4035 negative regulation of Wnt receptor signaling pathway ADAM10, 102 Notch receptor processing ASCL1, 429 Notch signaling pathway HTR2A, 3356 serotonin receptor signaling pathway ADRB2, 154 transmembrane receptor protein tyrosine kinase activation (dimerization) PTPRG, 5793 transmembrane receptor protein tyrosine kinase signaling pathway EPHA4, 2043 transmembrane receptor protein tyrosine kinase signaling pathway NRTN, 4902 transmembrane receptor protein tyrosine kinase signaling pathway CTNND1, 1500 Wnt receptor signaling pathway `
  71. 71. we can transform complex queries into links http://hcls1.csail.mit.edu:8890/sparql/?query=prefix%20go%3A%20%3Chttp%3A%2F%2Fpurl.org%2Fobo%2Fowl%2FGO%23%3E%0Aprefix%20rdfs%3A %20%3Chttp%3A%2F%2Fwww.w3.org%2F2000%2F01%2Frdf-schema%23%3E%0Aprefix%20owl%3A%20%3Chttp%3A%2F%2Fwww.w3.org%2F2002% 2F07%2Fowl%23%3E%0Aprefix%20mesh%3A%20%3Chttp%3A%2F%2Fpurl.org%2Fcommons%2Frecord%2Fmesh%2F%3E%0Aprefix%20sc%3A%20% 3Chttp%3A%2F%2Fpurl.org%2Fscience%2Fowl%2Fsciencecommons%2F%3E%0Aprefix%20ro%3A%20%3Chttp%3A%2F%2Fwww.obofoundry.org%2Fro %2Fro.owl%23%3E%0A%0Aselect%20%3Fgenename%20%3Fprocessname%0Awhere%0A%7B%20%20graph%20%3Chttp%3A%2F%2Fpurl.org% 2Fcommons%2Fhcls%2Fpubmesh%3E%0A%20%20%20%20%20%7B%20%3Fpaper%20%3Fp%20mesh%3AD017966%20.%0A%20%20%20%20%20%20% 20%3Farticle%20sc%3Aidentified_by_pmid%20%3Fpaper.%0A%20%20%20%20%20%20%20%3Fgene%20sc% 3Adescribes_gene_or_gene_product_mentioned_by%20%3Farticle.%0A%20%20%20%20%20%7D%0A%20%20%20graph%20%3Chttp%3A%2F% 2Fpurl.org%2Fcommons%2Fhcls%2Fgoa%3E%0A%20%20%20%20%20%7B%20%3Fprotein%20rdfs%3AsubClassOf%20%3Fres.%0A%20%20%20%20% 20%20%20%3Fres%20owl%3AonProperty%20ro%3Ahas_function.%0A%20%20%20%20%20%20%20%3Fres%20owl%3AsomeValuesFrom%20%3Fres2.% 0A%20%20%20%20%20%20%20%3Fres2%20owl%3AonProperty%20ro%3Arealized_as.%0A%20%20%20%20%20%20%20%3Fres2%20owl% 3AsomeValuesFrom%20%3Fprocess.%0A%20%20%20graph%20%3Chttp%3A%2F%2Fpurl.org%2Fcommons%2Fhcls%2F20070416%2Fclassrelations%3E %0A%20%20%20%20%20%7B%7B%3Fprocess%20%3Chttp%3A%2F%2Fpurl.org%2Fobo%2Fowl%2Fobo%23part_of%3E%20go%3AGO_0007166%7D% 0A%20%20%20%20%20%20%20union%0A%20%20%20%20%20%20%7B%3Fprocess%20rdfs%3AsubClassOf%20go%3AGO_0007166%20%7D%7D%0A %20%20%20%20%20%20%20%3Fprotein%20rdfs%3AsubClassOf%20%3Fparent.%0A%20%20%20%20%20%20%20%3Fparent%20owl% 3AequivalentClass%20%3Fres3.%0A%20%20%20%20%20%20%20%3Fres3%20owl%3AhasValue%20%3Fgene.%0A%20%20%20%20%20%20%7D%0A% 20%20%20graph%20%3Chttp%3A%2F%2Fpurl.org%2Fcommons%2Fhcls%2Fgene%3E%0A%20%20%20%20%20%7B%20%3Fgene%20rdfs%3Alabel%20% 3Fgenename%20%7D%0A%20%20%20graph%20%3Chttp%3A%2F%2Fpurl.org%2Fcommons%2Fhcls%2F20070416%3E%0A%20%20%20%20%20%7B% 20%3Fprocess%20rdfs%3Alabel%20%3Fprocessname%7D%0A%7Dformat=maxrows=50
  72. 72. we can transform complex queries into links
  73. 73. we can help scholars “remix” queries prefix go: http://purl.org/obo/owl/GO# prefix rdfs: http://www.w3.org/2000/01/rdf-schema# prefix owl: http://www.w3.org/2002/07/owl# prefix mesh: http://purl.org/commons/record/mesh/ prefix sc: http://purl.org/science/owl/sciencecommons/ prefix ro: http://www.obofoundry.org/ro/ro.owl# select ?genename ?processname where { graph http://purl.org/commons/hcls/pubmesh Mesh: Cancer mesh:D009369 { ?paper ?p . ?article sc:identified_by_pmid ?paper. ?gene sc:describes_gene_or_gene_product_mentioned_by ?article. } graph http://purl.org/commons/hcls/goa { ?protein rdfs:subClassOf ?res. ?res owl:onProperty ro:has_function. ?res owl:someValuesFrom ?res2. ?res2 owl:onProperty ro:realized_as. ?res2 owl:someValuesFrom ?process. graph http://purl.org/commons/hcls/20070416/classrelations go:GO_0006610} {{?process http://purl.org/obo/owl/obo#part_of union GO: Ribosomal Protein go:GO_0006610 }} {?process rdfs:subClassOf ?protein rdfs:subClassOf ?parent. ?parent owl:equivalentClass ?res3. ?res3 owl:hasValue ?gene. } graph http://purl.org/commons/hcls/gene { ?gene rdfs:label ?genename } graph http://purl.org/commons/hcls/20070416 { ?process rdfs:label ?processname} }
  74. 74. we can build a corpus of queries as links
  75. 75. “mashups” in science “While brain maps until now have been similar to a traditional encyclopedia, the Allen Brain Atlas is more like Google Earth.”
  76. 76. ...that’s better.
  77. 77. 5. reports from the front lines: the same things that prevent change can foster change...
  78. 78. open law, balanced incentives, and distributed workloads
  79. 79. Open Access Research Tools
  80. 80. making the tacit knowledge encoded in materials and data available at high speed and low transaction costs.
  81. 81. user interface to technology transfer core contract grants the right to do research
  82. 82. “one-click” for clinical data
  83. 83. “one-click” for DNA and materials
  84. 84. ibridge
  85. 85. build offer through simple set of choices (post-authentication)
  86. 86. scientist readable lawyer readable machine readable
  87. 87. the public domain
  88. 88. conclusion?
  89. 89. don’t wait.
  90. 90. use existing systems.
  91. 91. hack around problems.
  92. 92. create new ways to measure.
  93. 93. build your own commons.
  94. 94. thank you wilbanks@creativecommons.org http://sciencecommons.org
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