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Data, Code, and
Research at Scale
         Josh Greenberg
  The Alfred P. Sloan Foundation

      greenberg@sloan.org
       @epistemographer
Disclaimer
These statements do not necessarily reflect the
thoughts of the Alfred P. Sloan Foundation or my
        colleagues; they are mine alone.
Research at Scale
http://www.flickr.com/photos/ryanwick/3461850112/
http://www.flickr.com/photos/tncountryfan/5543540985/
Macroscope
http://pespmc1.vub.ac.be/macroscope/default.html
“My aim here is to inspire computer scientists to
implement software frameworks that empower
domain scientists to assemble their own continuously
evolving macroscopes, adding and upgrading existing
(and removing obsolete) plug-ins to arrive at a set
that is truly relevant for their work”

           Katy Borner, “Plug and Play Macroscopes”




            http://cacm.acm.org/magazines/2011/3/105316-plug-and-play-macroscopes/fulltext
http://ngrams.googlelabs.com/graph?content=science,+technology&year_start=1800&year_end=2000&corpus=0&smoothing=3
Data, Code, and Research at Scale
http://blog.okcupid.com/index.php/the-best-questions-for-first-dates/
Data
Big Data
Data, Code, and Research at Scale
SDSS



       http://www.sdss.org/includes/sideimages/sm_sdss_pie2.jpg
Census of Marine Life


                   http://comlmaps.org/oceanlifemap
Data, Code, and Research at Scale
http://www.flickr.com/photos/72427965@N00/3731550892/
http://www.flickr.com/photos/anders-vindegg/3369218571/
Code
http://www.flickr.com/photos/roidelapatate/4313265988/
http://ngrams.googlelabs.com/graph?content=science,+technology&year_start=1800&year_end=2000&corpus=0&smoothing=3
http://ngrams.googlelabs.com/graph?content=science,+technology&year_start=1800&year_end=2000&corpus=0&smoothing=3
http://www.sciencemag.org/content/331/6014/176.full#F1
Who does the work?
Data Science
Data Science
Engineering




                  Applied Math
              John Rauser @ http://www.youtube.com/watch?v=0tuEEnL61HM
Ap
  pli
        ed
             M
              at
                 h



                                                   Writing




       ri ng
     ee
  gin
En




                     John Rauser @ http://www.youtube.com/watch?v=0tuEEnL61HM
Ap
  pli
        ed
             M
              at
                 h



                                                   Writing




       ri ng
     ee
  gin
En




                     John Rauser @ http://www.youtube.com/watch?v=0tuEEnL61HM
Data Science
 (#alt-ac?)
All hands on deck
Galaxy Zoo
http://www.oldweather.org/
http://menus.nypl.org
Data, Code, and Research at Scale
Data, Code, and Research at Scale
Galaxy Zoo
Epistemology
Data, Code, and Research at Scale
Epistemology
          of Big Data?



(Flip Kromer)
Data, Code, and Research at Scale
Screwmeneutics?



http://www.playingwithhistory.com/wp-content/uploads/2010/04/hermeneutics.pdf
http://www.flickr.com/photos/amishsteve/98994505/
Trust
http://en.wikipedia.org/wiki/File:Library_of_Congress,_Rosenwald_4,_Bl._5r.jpg
Reproducibility
empirical falsifiability : methods
                 ::
hermeneutic inquiry : provenance
Citation
Data, Code, and Research at Scale
Our means of dissemination are
out of sync with the methods of
      scholarly production
http://www.sciencemag.org/content/331/6014/176.full#F1
A thought experiment:
A thought experiment:
  What if we wrote
scholarship like code?
Version Control
Tagged release
Data, Code, and Research at Scale
Bug Tracking
Data, Code, and Research at Scale
The very technology that
enables research at scale
 potentially enables new
 modes of dissemination
http://www.stodden.net/AMP2011/
http://en.wikipedia.org/wiki/File:Panopticon.jpg
Del Rigor en la Ciencia
                         Jorge Luis Borges

“En aquel Imperio, el Arte de la Cartografía logró tal Perfección
que el Mapa de una sola Provincia ocupaba toda una Ciudad, y el
Mapa del Imperio, toda una Provincia. Con el tiempo, estos Mapas
Desmesurados no satisficieron y los Colegios de Cartógrafos
levantaron un Mapa del Imperio, que tenía el Tamaño del Imperio y
coincidía puntualmente con él. Menos Adictas al Estudio de la
Cartografía, las Generaciones Siguientes entendieron que ese
dilatado Mapa era Inútil y no sin Impiedad lo entregaron a las
Inclemencias del Sol y los Inviernos. En los Desiertos del Oeste
perduran despedazadas Ruinas del Mapa, habitadas por Animales y
por Mendigos; en todo el País no hay otra reliquia de las Disciplinas
Geográficas.

“Suárez Miranda: Viajes de varones prudentes,
libro cuarto, cap. XLV, Lérida, 1658.”




                        via http://elmundoenverso.blogspot.com/2007/12/del-rigor-en-la-ciencia-jorge-lus.html
Discuss...
One more thing...
Research at Scale
Disaggregation of
scholarly materials
Flourishing of new
 channels / genres
Humanities : blogs
                   ::
   Social Sciences : SSRN (preprint)
                   ::
Sciences : PLoS ONE (rapid publication)
Addition of data and
   code to pile
New macroscopic
methods of discovery,
  assessing impact
Why (digital) humanities?

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Data, Code, and Research at Scale

Hinweis der Redaktion

  1. \n
  2. \n
  3. \n
  4. \n
  5. \n
  6. \n
  7. Figure from Joël de Rosnay, 1979 book “The Macroscope”\n
  8. \n
  9. This is happening elsewhere, across other fields. Consider the impact of Google Books as a macroscope.\n
  10. \n
  11. \n34,260 real-life couples - “I met someone on OkCupid”, give username, hundreds per day\n\n- Would you consider sleeping with someone on the first date :: do you like the taste of beer?\n- Long-term compatibility :: Do you like horror movies?; Have you ever traveled around another country alone?; Wouldn't it be fun to chuck it all and go live on a sailboat?\n\n
  12. \n
  13. \n
  14. The Foundation makes grants to support original research and broad-based education related to science, technology, and economic performance; and to improve the quality of American life\n\nOne thing to know about Sloan - the Foundation likes data. A lot.\n
  15. The Sloan Digital Sky Survey or SDSS is a major multi-filter imaging and spectroscopic redshift survey using a dedicated 2.5-m wide-angle optical telescope at Apache Point Observatory in New Mexico, United States\nThe survey was begun in 2000, and has mapped over 35% of the sky\n\n
  16. Census of Marine Life - “global network of researchers in more than 80 nations engaged in a 10-year scientific initiative to assess and explain the diversity, distribution, and abundance of life in the oceans.”\n
  17. Indoor Environment - in fact, virtually every science or social science program we have now involves a data infrastructure\n
  18. Data deluge\n
  19. What to throw away?\n
  20. Code\n
  21. Data’s great, but to work with it at scale, you need code.\n\n(The coffee grinder analogy isn’t quite right, but be glad that you didn’t get a meat grinder instead)\n
  22. The n-gram viewer is a big black box. We have no idea what’s happening inside.\n
  23. They do offer links to the data itself\n
  24. Look at arrows, which mask some important transformations.\n
  25. A lot of my scholarly work was on “mediators”, the people between producers and consumers. Oriented in this direction. Handwork vs. work “at scale”\n
  26. NPR piece on data science\n
  27. John Rauser from Amazon at Strata NYC 2011\n
  28. John Rauser from Amazon at Strata NYC 2011\n\n“Telling stories with Data”\n
  29. John Rauser from Amazon at Strata NYC 2011\n
  30. NPR piece on data science\n
  31. \n
  32. \n
  33. \n
  34. \n
  35. \n
  36. \n
  37. Beyond data cleanup, production of new knowledge. Communication between participants (channel Lintott)\n
  38. \n
  39. Two main modes of knowledge production: scientific method founded on empirical falsifiability, and hermeneutic approaches that characterize much of the humanities and some social science.\n
  40. Get a big pile of stuff, look for patterns, and iteratively hone in.\n\nAny economist will start shouting “correlation, not causation”.\n
  41. nod to Dan Atkins for mentioning it yesterday - data mining\n
  42. Steve Ramsay on browsing a library: “Here, I don’t know what I’m looking for, really. I just have a bundle of ‘interests’ and proclivities. I’m not really trying to find ‘a path through culture.’ I’m really just screwing around.”\n
  43. Working at scale with data - Sense of play, fiddling with knobs. Exploration, visualization.\n\n\n
  44. \n
  45. Standing on the shoulders of giants\n
  46. \n
  47. \n
  48. takes for granted wide system of institutions, as well as platforms and genres. Cite a book, you can trust a broad system of libraries as well as the consistency of individual manifestations of the same work\n
  49. Chain of evidence\n
  50. Data, code, are all important\n
  51. Let’s imagine you publish an article. Many possible points of failure along chain moving upstream. Sociologists of science describe process of contestation as sequential opening of black boxes...\n
  52. \n
  53. \n
  54. \n
  55. Dan Cohen talked about learning to live with imperfection - software is never perfect, it’s just shipped.\n
  56. Social features (Github)\n
  57. Not everyone gets commit access; bug tracking is a form of decentralized review\n
  58. Forking\n
  59. \n
  60. Workshop hosted by Victoria Stodden and others that convened projects that leverage technology in the interest of reproducible research\n
  61. Some problems - looked at through another lens, this is essentially a culture of surveillance where everything is visible at all times.\n
  62. Also, limited resources mean that the perfect capture of everything isn’t feasible, or useful downstream\n
  63. Lots to decide on, and hopefully affirmatively address rather than simply allow technology to determine.\n
  64. \n
  65. Step back and look not at individual research projects, but the overall system. We’re seeing a lot of changes...\n
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  67. \n
  68. \n
  69. \n
  70. Dan Cohen on PressForward yesterday (12/2/11) - “if you don’t like our choices, you can check our work”\n
  71. Opportunities to innovate in humanities, given 1) low stakes in publishing industry, 2) close linkages with libraries, and 3) vibrant community discussion.\n