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john wilbanks
creative commons / science commons

Open Innovation, Institutional Policy,
    and the Digital Commons

    ...
knowledge gaps
  process failures
 transaction costs
lost opportunities
knowledge gaps
                process failures
               transaction costs
              lost opportunities


is the...
the discovery process:
the discovery process:
thanks to the products,
we already know a lot...
we need process innovations
to match product innovations.
collaborative workflows
   standard data formats
   collaboration software
  secure legal frameworks


 we need process inn...
most products advance
    incrementally
business model: sell
more, faster, cheaper
business model: sell
more, faster, cheaper
does the ability to ask more
questions, faster, lead us to more
 knowledge or just more data?
what’s different about
communications and computers?
1. we know stuff.
1. we know stuff.
2. open networks.
content

 code

physical
1.
the “digital commons” represents a
   methodology to bring network
   externalities to the sciences
“the commons”
knowledge rights
“digital commons”

   interoperability
low transaction costs
 law and technology
user interface to copyright
140,000,000+ digital objects online
       under our licenses

licenses “ported” to 45+ countries

  integrated with Googl...
content

 code

physical
innovation

 content

  code

 physical
2.
the digital commons is a innovation-
  friendly way to manage data,
materials, and content for science.
project development   “do no harm”


 funding
pro bono                                           “running code”
community
...
what would move via the science network?
Open Access
Research Tools
making the tacit knowledge
encoded in materials and data
available at high speed and low
       transaction costs.
user interface to
  technology transfer

core contract grants the
  right to do research
“one-click”
for DNA and
  materials
ibridge
build offer through simple set of choices
          (post-authentication)
Scientist readable




                     Lawyer readable




                            Machine readable
service opportunity:
 amazon, e-bay, paypal,
shipping, materials prep
“one-click”
for clinical data
service opportunity:
    data cleaning, data
integration, data analytics,
  “virtual” clinical trials,
   storage, escrow,...
Open Access Content
making knowledge legally and
technically available for re-use and
composition into new knowledge.
we use digital
tools to replicate
paper technology
©
creative expression
©
ideas or facts
e=mc2
the container, not the facts.
the container, not the facts.

but   © locks the container.
IGFBP-5 plays a role in the
regulation of cellular senescence
via a p53-dependent pathway
and in aging-associated vascular...
IGFBP-5 plays a role in the
regulation of cellular senescence
via a p53-dependent pathway
and in aging-associated vascular...
indexing: disallowed.




  http://orpheus-1.ucsd.edu/acq/license/cdlelsevier2004.pdf
c
>1000 journals under CC

  image from the public library of science
  licensed to the public under CC-BY 3.0
service opportunity:
    enhanced publishing,
     document markup,
literature-data integration,
    indexing and search
3.
we have to build infrastructure for data
into the web of documents that we have.
solves the legal problem
but not the
container problem.
web 2.0, science 3.0, what about
 making Google work better?
over 200
   years at
one paper/day
what you want is
   a list of genes.

not a list of documents.
building a web for data:
  the “semantic web”
making computers understand links between documents




                     links to
    Web page                        ...
making computers understand relationships between concepts




                        causes
     drinking coffee        ...
causes
drink coffee            feel awake
http://ontology.foo.org/causes



                                          causes
          drinking coffee              ...
we need a Domain Name System for concepts:

192.168.1.1             http://sciencecommons.org

  coffee                htt...
use the web to
           integrate information
            from different places
             and different names
“coffee...
bed
                                                                                    person

 located at               ...
(too much work for
      coffee)
(distributed, networked
  approaches start to
   look pretty good)
Open Source
Data Integration
formatting digital knowledge into
   modular building blocks for
composition into new knowledge.
e pluribus unum.
500,000,000+ RDF “triples”
           pre-formatted queries
pathway analytic software donated by MLNM
    uses $5,000 of o...
uses:

  “DNS for life sciences”
enhanced document markup
 modular data distributions
get precise answers out of existing
       databases and resources
            prefix go: <http://purl.org/obo/owl/GO#>
  ...
DRD1, 1812      adenylate cyclase activation
ADRB2, 154      adenylate cyclase activation
ADRB2, 154      arrestin mediate...
transforms complex queries into links

http://hcls1.csail.mit.edu:8890/sparql/?query=prefix%20go%3A%20%3Chttp%3A%2F%2Fpurl....
transforms complex queries into links
“mashups” in science




“While brain maps until now have
been similar to a traditional
encyclopedia, the Allen Brain Atla...
open systems do things you don’t expect,
  that are occasionally more valuable...
service opportunity:
  distribution and services,
    database conversion,
      ontology creation,
namespace servers, reg...
they’re coming.
changes from a guild
culture of knowledge
knowledge

 content

  code

 physical
wilbanks@creativecommons.org

  http://sciencecommons.org
Innovation In Services And Business Models
Innovation In Services And Business Models
Innovation In Services And Business Models
Innovation In Services And Business Models
Innovation In Services And Business Models
Innovation In Services And Business Models
Innovation In Services And Business Models
Innovation In Services And Business Models
Innovation In Services And Business Models
Innovation In Services And Business Models
Innovation In Services And Business Models
Innovation In Services And Business Models
Innovation In Services And Business Models
Innovation In Services And Business Models
Innovation In Services And Business Models
Innovation In Services And Business Models
Innovation In Services And Business Models
Innovation In Services And Business Models
Innovation In Services And Business Models
Innovation In Services And Business Models
Innovation In Services And Business Models
Innovation In Services And Business Models
Innovation In Services And Business Models
Innovation In Services And Business Models
Innovation In Services And Business Models
Innovation In Services And Business Models
Innovation In Services And Business Models
Innovation In Services And Business Models
Innovation In Services And Business Models
Innovation In Services And Business Models
Innovation In Services And Business Models
Innovation In Services And Business Models
Innovation In Services And Business Models
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Transcript of "Innovation In Services And Business Models"

  1. 1. john wilbanks creative commons / science commons Open Innovation, Institutional Policy, and the Digital Commons 10 november 2008 haas school of business
  2. 2. knowledge gaps process failures transaction costs lost opportunities
  3. 3. knowledge gaps process failures transaction costs lost opportunities is the answer more products?
  4. 4. the discovery process:
  5. 5. the discovery process:
  6. 6. thanks to the products, we already know a lot...
  7. 7. we need process innovations to match product innovations.
  8. 8. collaborative workflows standard data formats collaboration software secure legal frameworks we need process innovations to match product innovations.
  9. 9. most products advance incrementally
  10. 10. business model: sell more, faster, cheaper
  11. 11. business model: sell more, faster, cheaper
  12. 12. does the ability to ask more questions, faster, lead us to more knowledge or just more data?
  13. 13. what’s different about communications and computers?
  14. 14. 1. we know stuff.
  15. 15. 1. we know stuff. 2. open networks.
  16. 16. content code physical
  17. 17. 1. the “digital commons” represents a methodology to bring network externalities to the sciences
  18. 18. “the commons”
  19. 19. knowledge rights
  20. 20. “digital commons” interoperability low transaction costs law and technology
  21. 21. user interface to copyright
  22. 22. 140,000,000+ digital objects online under our licenses licenses “ported” to 45+ countries integrated with Google,Yahoo, Firefox, Microsoft Office...
  23. 23. content code physical
  24. 24. innovation content code physical
  25. 25. 2. the digital commons is a innovation- friendly way to manage data, materials, and content for science.
  26. 26. project development “do no harm” funding pro bono “running code” community “think market” early focus on life sciences exploring climate change, geospatial, elsewhere
  27. 27. what would move via the science network?
  28. 28. Open Access Research Tools
  29. 29. making the tacit knowledge encoded in materials and data available at high speed and low transaction costs.
  30. 30. user interface to technology transfer core contract grants the right to do research
  31. 31. “one-click” for DNA and materials
  32. 32. ibridge
  33. 33. build offer through simple set of choices (post-authentication)
  34. 34. Scientist readable Lawyer readable Machine readable
  35. 35. service opportunity: amazon, e-bay, paypal, shipping, materials prep
  36. 36. “one-click” for clinical data
  37. 37. service opportunity: data cleaning, data integration, data analytics, “virtual” clinical trials, storage, escrow, etc.
  38. 38. Open Access Content
  39. 39. making knowledge legally and technically available for re-use and composition into new knowledge.
  40. 40. we use digital tools to replicate paper technology
  41. 41. © creative expression
  42. 42. © ideas or facts
  43. 43. e=mc2
  44. 44. the container, not the facts.
  45. 45. the container, not the facts. but © locks the container.
  46. 46. IGFBP-5 plays a role in the regulation of cellular senescence via a p53-dependent pathway and in aging-associated vascular diseases
  47. 47. IGFBP-5 plays a role in the regulation of cellular senescence via a p53-dependent pathway and in aging-associated vascular diseases
  48. 48. indexing: disallowed. http://orpheus-1.ucsd.edu/acq/license/cdlelsevier2004.pdf
  49. 49. c >1000 journals under CC image from the public library of science licensed to the public under CC-BY 3.0
  50. 50. service opportunity: enhanced publishing, document markup, literature-data integration, indexing and search
  51. 51. 3. we have to build infrastructure for data into the web of documents that we have.
  52. 52. solves the legal problem
  53. 53. but not the container problem.
  54. 54. web 2.0, science 3.0, what about making Google work better?
  55. 55. over 200 years at one paper/day
  56. 56. what you want is a list of genes. not a list of documents.
  57. 57. building a web for data: the “semantic web”
  58. 58. making computers understand links between documents links to Web page Web page
  59. 59. making computers understand relationships between concepts causes drinking coffee feel awake
  60. 60. causes drink coffee feel awake
  61. 61. http://ontology.foo.org/causes causes drinking coffee feel awake http://ontology.foo.org/drinking coffee http://ontology.foo.org/feel awake h
  62. 62. we need a Domain Name System for concepts: 192.168.1.1 http://sciencecommons.org coffee http://ontology.foo.org/coffee
  63. 63. use the web to integrate information from different places and different names “coffee” “cafe” coffee http://ontology.foo.org/coffee “kopi”
  64. 64. bed person located at get out of bed last subevent does not want wants get out of bed after causes drink coffee feel awake first subevent subevent causes feel jittery open eyes after after make coffee pour coffee pick up cup drink is a is for located in coffee cafe property of often near often near wet cup sugar
  65. 65. (too much work for coffee)
  66. 66. (distributed, networked approaches start to look pretty good)
  67. 67. Open Source Data Integration
  68. 68. formatting digital knowledge into modular building blocks for composition into new knowledge.
  69. 69. e pluribus unum.
  70. 70. 500,000,000+ RDF “triples” pre-formatted queries pathway analytic software donated by MLNM uses $5,000 of off-the-shelf hardware bundled with open source triple store download, mirror, fork. http://neurocommons.org
  71. 71. uses: “DNS for life sciences” enhanced document markup modular data distributions
  72. 72. get precise answers out of existing databases and resources prefix go: <http://purl.org/obo/owl/GO#> prefix rdfs: <http://www.w3.org/2000/01/rdf-schema#> Mesh: Pyramidal Neurons 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> Pubmed: Journal Articles { ?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> Entrez Gene: Genes { ?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> {{?process <http://purl.org/obo/owl/obo#part_of> go:GO_0007166} union {?process rdfs:subClassOf go:GO_0007166 }} ?protein rdfs:subClassOf ?parent. ?parent owl:equivalentClass ?res3. GO: Signal Transduction ?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} }
  73. 73. 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 `
  74. 74. transforms 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%7D&format=&maxrows=50
  75. 75. transforms complex queries into links
  76. 76. “mashups” in science “While brain maps until now have been similar to a traditional encyclopedia, the Allen Brain Atlas is more like Google Earth.”
  77. 77. open systems do things you don’t expect, that are occasionally more valuable...
  78. 78. service opportunity: distribution and services, database conversion, ontology creation, namespace servers, registries
  79. 79. they’re coming.
  80. 80. changes from a guild culture of knowledge
  81. 81. knowledge content code physical
  82. 82. wilbanks@creativecommons.org http://sciencecommons.org
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