2. When it was proclaimed that the Library contained all books, the rst impression was one of extravagant happiness. All men felt themselves to be the masters of an intact and secret treasure. There was no personal or world problem whose eloquent solution did not exist in some hexagon. The universe was justied, the universe suddenly usurped the unlimited dimensions of hope.
3. other ofcial futures
4. 1. past health sciences research
5. what happens when thats all digital?
6. 2. whats broken open the health sciences ofcial future?
7. cheap data has changed our politics.
8. cheap data changes how we justify our opinions.
9. cheap data transgresses lots of things we expect
14. and can we make cheap less toxic than it has been to date?
15. 3. an existence proof of the open window.
16. Promote OPEN SYSTEMS, INCENTIVES, and NORMS to redefine how complex biological data is GATHERED, SHARED, AND USED.
17. decentralization the process of redistributing or dispersing functions, powers, people, or things away from a central location or authority wikipedia
18. pervasiveness of networked information cloud infrastructure democratization of research process govt agencies and public pushing for > sharing
19. recruitment data generation data analysis institutional silos
20. recruitment data generation data analysis institutional silosbreaking down
21. recruitment data generation data analysis institutional silosbreaking down
22. crc subtyping consortium
23. A B C D E F 1 2 3 4 5 6 expert team data subtype crc subtyping consortium
24. A B C D E F 1 2 3 4 5 6 ... expert team data subtype crc subtyping consortium
25. crc subtyping consortium
26. doi:10.1038/nm.3967 crc subtyping consortium
27. analytical challenges unbiased, consistent, and rigorous method assessment sampling of a space of diverse methods
28. predict survival for prostate cancer patients analytical challenges
29. recruitment data generation data analysis institutional silosbreaking down
30. recruitment data generation data analysis institutional silosbreaking down
31. public / private partnership between NIH, 10 biopharmaceutical companies and several non-prot organizations accelerating medicines partnership data generation data analysis|
32. ($ Millions) Total Project Total NIH Total Industry Alzheimers Disease 129.5 67.6 61.9 Type 2 Diabetes 58.4 30.4 28 Rheumatoid Arthritis 41.6 20.9 20.7 TOTAL 229.5 118.9 110.6 accelerating medicines partnership data generation data analysis|
33. Target Discovery Target Discovery Target Discovery Target Discovery Target Validation Target Validation Target Validation Target Validation Shared Information for Target Identification coordinate sharing of early-phase target identication insights accelerating medicines partnership data generation data analysis|
34. AMP-AD Collaborative Workspace Quarterly Depositions Broad/ RUSH Mt. Sinai U Fl/ ISB/ Mayo Emory Sage Other Partners Individual Partner Workspaces AMP-AD Data Portal Consortium Space Public space AMP-AD Synapse Project Structure accelerating medicines partnership data generation data analysis|
36. recruitment data generation data analysis institutional silosbreaking down
37. recruitment data generation data analysis institutional silosbreaking down
40. insular health trackingmove beyond
41. nearly 200 million smart phone users in US insular health trackingmove beyond
42. 2015 march
43. participant-centered consent open source toolkit http://sagebase.org/pcc
44. participant-centered consent 1. tiered information access by participants 2. pictorial dominant on rst information tier 3. text dominant on second information tier 4. require perfect score on short assessment
48. motor initiation gait/balance hypophonia memory mPower data generation activities
49. six month data releasemPower data generation
50. six month data releasemPower task name type of task and schedule unique participants unique tasks demographics survey - once 6,805 6,805 MDS-UPDRS survey - monthly 2,024 2,305 PDQ8 survey - monthly 1,334 1,641 memory activity - t.i.d. 968 8,569 tapping activity - t.i.d. 8,003 78,887 voice activity - t.i.d. 5,826 65,022 walking activity - t.i.d. 3,101 35,410 data generation
51. Parkinsons Disease Foundation Eli Lilly AstraZeneca Apple Verily Intel Infocepts Posit Science MIT The Ohio State University University of Otago University of Texas Health Science Center Istanbul Sehir University University of Iowa University of Virginia University of Toronto Johns Hopkins University Vanderbilt University University of Rochester McGill University Xi'an Jiaotong University University of Washington Harvard University mHealth research communityParkinson study data released before any primary publication 60+ independent qualied researchers working towards building a PD research community
52. products at scale, but non-corporate
53. products at scale, but non-corporate libraries as essential partners
54. 4. meet the new boss, same as the old boss.
55. store content organize content query content
56. were doing the same thing with library services.
57. a group of volunteers connected by a global computer network will build for free and give away an encyclopedia that displaces Britannica
58. cloud things can be disappeared instantly
59. were doing the same thing with library services. thats bad.
60. 5. were the ones who need to articulate the new ofcial futures.
61. a. incrementalism.
62. (this is arguably off the table)
63. b. the stacks.
64. c. small but compatibly communicating groups
65. but we cant do it if we have to be dependent on the stacks.
66. look to metaphors and models beyond the startup
68. The impious maintain that nonsense is normal in the Library and that the reasonable (and even humble and pure coherence) is an almost miraculous exception.