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Data, Code, and Research at Scale
- 1. Data, Code, and Research at Scale Josh Greenberg The Alfred P. Sloan Foundation greenberg@sloan.org @epistemographer
- 2. Disclaimer These statements do not necessarily reflect the thoughts of the Alfred P. Sloan Foundation or my colleagues; they are mine alone.
- 6. Macroscope
- 8. “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
- 12. Data
- 13. Big Data
- 15. SDSS http://www.sdss.org/includes/sideimages/sm_sdss_pie2.jpg
- 16. Census of Marine Life http://comlmaps.org/oceanlifemap
- 20. Code
- 25. Who does the work?
- 26. Data Science
- 27. Data Science Engineering Applied Math John Rauser @ http://www.youtube.com/watch?v=0tuEEnL61HM
- 28. Ap pli ed M at h Writing ri ng ee gin En John Rauser @ http://www.youtube.com/watch?v=0tuEEnL61HM
- 29. Ap pli ed M at h Writing ri ng ee gin En John Rauser @ http://www.youtube.com/watch?v=0tuEEnL61HM
- 31. All hands on deck
- 32. Galaxy Zoo
- 37. Galaxy Zoo
- 38. Epistemology
- 40. Epistemology of Big Data? (Flip Kromer)
- 44. Trust
- 46. Reproducibility
- 47. empirical falsifiability : methods :: hermeneutic inquiry : provenance
- 48. Citation
- 50. Our means of dissemination are out of sync with the methods of scholarly production
- 53. A thought experiment: What if we wrote scholarship like code?
- 54. Version Control
- 55. Tagged release
- 57. Bug Tracking
- 59. The very technology that enables research at scale potentially enables new modes of dissemination
- 62. 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
- 63. Discuss...
- 67. Flourishing of new channels / genres
- 68. Humanities : blogs :: Social Sciences : SSRN (preprint) :: Sciences : PLoS ONE (rapid publication)
- 69. Addition of data and code to pile
- 70. New macroscopic methods of discovery, assessing impact
Notas do Editor
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- Figure from Joël de Rosnay, 1979 book “The Macroscope”\n
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- This is happening elsewhere, across other fields. Consider the impact of Google Books as a macroscope.\n
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- \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
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- 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
- 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
- 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
- Indoor Environment - in fact, virtually every science or social science program we have now involves a data infrastructure\n
- Data deluge\n
- What to throw away?\n
- Code\n
- 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
- The n-gram viewer is a big black box. We have no idea what’s happening inside.\n
- They do offer links to the data itself\n
- Look at arrows, which mask some important transformations.\n
- 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
- NPR piece on data science\n
- John Rauser from Amazon at Strata NYC 2011\n
- John Rauser from Amazon at Strata NYC 2011\n\n“Telling stories with Data”\n
- John Rauser from Amazon at Strata NYC 2011\n
- NPR piece on data science\n
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- Beyond data cleanup, production of new knowledge. Communication between participants (channel Lintott)\n
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- 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
- Get a big pile of stuff, look for patterns, and iteratively hone in.\n\nAny economist will start shouting “correlation, not causation”.\n
- nod to Dan Atkins for mentioning it yesterday - data mining\n
- 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
- Working at scale with data - Sense of play, fiddling with knobs. Exploration, visualization.\n\n\n
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- Standing on the shoulders of giants\n
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- 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
- Chain of evidence\n
- Data, code, are all important\n
- 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
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- Dan Cohen talked about learning to live with imperfection - software is never perfect, it’s just shipped.\n
- Social features (Github)\n
- Not everyone gets commit access; bug tracking is a form of decentralized review\n
- Forking\n
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- Workshop hosted by Victoria Stodden and others that convened projects that leverage technology in the interest of reproducible research\n
- Some problems - looked at through another lens, this is essentially a culture of surveillance where everything is visible at all times.\n
- Also, limited resources mean that the perfect capture of everything isn’t feasible, or useful downstream\n
- Lots to decide on, and hopefully affirmatively address rather than simply allow technology to determine.\n
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- 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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- Dan Cohen on PressForward yesterday (12/2/11) - “if you don’t like our choices, you can check our work”\n
- Opportunities to innovate in humanities, given 1) low stakes in publishing industry, 2) close linkages with libraries, and 3) vibrant community discussion.\n