Humanities in the Digital World
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The document discusses the intersection of humanities and digital technology, emphasizing the role of data-intensive research and social machines in scholarship. It highlights challenges in collaborative projects like Wikipedia due to declining participation and the need for new approaches to scholarly communication. Supported by funding bodies, the text covers various aspects including social networks, citizen engagement, and advancements in data science applications.
Humanities in the Digital World
- 1. David De Roure @dder Intersection, Scale, and Social Machines: The Humanities in the Digital World DIRECTOR, UNIVERSITY OF OXFORD E-RESEARCH CENTRE
- 2. Data-intensive research Human-intensive research Music Scholarly Communication
- 3. The Big Picture(s) Challenging Assumptions
- 5. 13,785,659 Β total Β volumes Β 6,871,154 Β book Β 6tles Β 364,473 Β serial Β 6tles Β 4,824,980,650 Β pages Β 618 Β terabytes Β 163 Β miles Β 11,201 Β tons Β 5,372,477 Β public Β domain Β volumes Β 10,000,000,000,000,000 bytes archived!
- 6. New Forms of Data βΆβ―Internet data, derived from social media and other online interactions (including data gathered by connected people and devices, eg mobile devices, wearable technology, Internet of Things) βΆβ―Tracking data, monitoring the movement of people and objects (including GPS/geolocation data, traffic and other transport sensor data, CCTV images etc) βΆβ―Satellite and aerial imagery (eg Google Earth, Landsat, infrared, radar mapping etc) http://www.oecd.org/sti/sci-tech/new-data-for- understanding-the-human-condition.htm
- 7. The Β Big Β Picture Β More people Moremachines Big Data Big Compute Conventional Computation βBig Socialβ Social Networks e-infrastructure Online R&D (Science 2.0) Digital Scholarship @dder
- 8. theODI.org
- 9. Data Detect Store AnalyticsFilter Analysts @dder
- 10. There is no such thing as the Internet of Things There is no such thing as a closed system Humans are creative and subversive The Rise of the Bots A Swarm of Drones Accidents happen (in the lab, bin) Holding machines to account Software vulnerability Where are the throttle points? @dder
- 11. F i r s t
- 12. Edwards, P. N., et al. (2013) Knowledge Infrastructures: Intellectual Frameworks and Research Challenges. Ann Arbor: Deep Blue. http://hdl.handle.net/2027.42/97552
- 14. Social Β Machines Β Deο¬ni6on Β TBL Β Pip Willcox
- 15. https://twitter.com/CR_UK/status/446223117841494016/ Some people's smartphones had autocorrected the word "BEAT" to instead read "BEAR". "Thank you for choosing an adorable polar bear," the reply from the WWF said. "We will call you today to set up your adoption." http://www.bbc.com/news/technology-26723457
- 17. SOCIAM: The Theory and Practice of Social Machines is funded by the UK Engineering and Physical Sciences Research Council (EPSRC) under grant number EPJ017728/1 and comprises the Universities of Southampton, Oxford and Edinburgh. See sociam.org
- 18. βYet Β Wikipedia Β and Β its Β stated Β ambi6on Β to Β βcompile Β the Β sum Β of Β all Β human Β knowledgeβ Β are Β in Β trouble. Β The Β volunteer Β workforce Β that Β built Β the Β projectβs Β ο¬agship, Β the Β English-Ββlanguage Β Wikipediaβand Β must Β defend Β it Β against Β vandalism, Β hoaxes, Β and Β manipula6onβ has Β shrunk Β by Β more Β than Β a Β third Β since Β 2007 Β and Β is Β s6ll Β shrinkingβ¦ Β Β The Β main Β source Β of Β those Β problems Β is Β not Β mysterious. Β The Β loose Β collec6ve Β running Β the Β site Β today, Β es6mated Β to Β be Β 90 Β percent Β male, Β operates Β a Β crushing Β bureaucracy Β with Β an Β oYen Β abrasive Β atmosphere Β that Β deters Β newcomers Β who Β might Β increase Β par6cipa6on Β in Β Wikipedia Β and Β broaden Β its Β coverageβ¦β Β Β http://www.technologyreview.com/featuredstory/520446/the-decline-of-wikipedia/
- 20. βPanoptes has been designed so that itβs easier for us to update and maintain, and to allow more powerful tools for project builders. Itβs also open source from the start, and if you find bugs or have suggestions about the new site you can note them on Github (or, if youβre so inclined, contribute to the codebase yourself).β " Β http://blog.zooniverse.org/2015/06/29/a-whole-new-zooniverse/ http://monsterspedia.wikia.com/wiki/File:Argus-Panoptes.jpg Panoptes
- 21. Musical Social Machines Social Machines of Scholarship
- 22. INT. VERSE VERSE VERSE VERSEBRIDGEBRIDGE OUT. Γͺοͺ The Β Problem Β signal understanding Ichiro Fujinaga
- 23. salami.music.mcgill.ca Jordan B. L. Smith, J. Ashley Burgoyne, Ichiro Fujinaga, David De Roure, and J. Stephen Downie. 2011. Design and creation of a large-scale database of structural annotations. In Proceedings of the International Society for Music Information Retrieval Conference, Miami, FL, 555β60
- 25. Dan Edelstein, Robert Morrissey, and Glenn Roe, To Quote or not to Quote: Citation Strategies in the EncyclopΓ©die. Journal of the History of Ideas , Volume 74, Number 2, April 2013 . pp. 213-236. 10.1353/jhi.2013.0012 Glenn Roe
- 26. Digital Β Music Β Collec6ons Β Grad-Ββsourced Β ground Β truth Β Community Β SoYware Β Linked Β Data Β Repositories Β Supercomputer Β 23,000 hours of recorded music Music Information Retrieval Community SALAMI
- 27. Ashley Burgoyne
- 28. www.music-ir.org/mirex Music Information Retrieval Evaluation eXchange Audio Onset Detection Audio Beat Tracking Audio Key Detection Audio Downbeat Detection Real-time Audio to Score Alignment(a.k.a Score Following) Audio Cover Song Identification Discovery of Repeated Themes & Sections Audio Melody Extraction Query by Singing/Humming Audio Chord Estimation Singing Voice Separation Audio Fingerprinting Music/Speech Classification/Detection Audio Offset Detection Downie, J. Stephen, Andreas F. Ehmann, Mert Bay and M. Cameron Jones. (2010). The Music Information Retrieval Evaluation eXchange: Some Observations and Insights. Advances in Music Information Retrieval Vol. 274, pp. 93-115
- 31. Digital Β Material Β Pip Willcox
- 32. Kevin Page David Weigl Interfaces, for computer and human !
- 34. Sonifying Β the Β Variants Β β’β― From Β Play Β to Β Soniο¬ca6on Β β’β― Using Β First Β Folio Β and Β Quartos Β data Β β’β― Parsing Β the Β TEI Β XML, Β conver6ng Β it Β with Β rule Β set Β into Β numbers, Β sonifying Β the Β data Β to Β produce Β sounds Β 34 Sonification Β Iain Emsley
- 35. Studying Social Machines Scholarship of Social Machines
- 36. Ecosystem Perspective β’β― We see a community of living, hybrid organisms, rather than a set of machines which happen to have humans amongst their components β’β― Their successes and failures inform the design and construction of their offspring and successors
- 37. time Social Machine instances @dder
- 38. Observer of one social machine Observers using third party observatory Observer of multiple social machines Human participants in Social Machine Human participants in multiple Social Machines Observer of Social Machine infrastructure 1 Β 4 Β 2 Β 3 Β 5 Β 6 Β SM SM SM Social Machine Observing Social Machines 7 Β @dder De Roure, D., Hooper, C., Page, K., Tarte, S., and Willcox, P. 2015. Observing Social Machines Part 2: How to Observe? ACM Web Science
- 39. The Web Observatory Tiropanis, T., Hall, W., Shadbolt, N., De Roure, D., Contractor, N. and Hendler, J. 2013. The Web Science Observatory, IEEE Intelligent Systems 28(2) pp 100β104. ThanassisTiropanis
- 40. Simpson, R., Page, K.R. and De Roure, D. 2014. Zooniverse: observing the world's largest citizen science platform. In Proceedings of the companion publication of the 23rd international conference on World Wide Web, 1049-1054. Kevin Page
- 41. STORYTELLING AS A STETHOSCOPE FOR SOCIAL MACHINES 1.β― Sociality through storytelling potential and realization 2.β― Sustainability through reactivity and interactivity 3.β― Emergence through collaborative authorship and mixed authority Zooniverse Β is Β a Β highly Β storiο¬ed Β Social Β Machine Β Facebook Β doesnβt Β allow Β for Β improvisa6on Β Wikipedia Β assigns Β authority Β rights Β rigidly Β http://ora.ox.ac.uk/objects/ora:8033 Tarte, S.M., De Roure, D. and Willcox, P. 2014. Working out the Plot: the Role of Stories in Social Machines. SOCM2014: The Theory and Practice of Social Machines, Seoul, Korea, International World Wide Web Conferences pp. 909β914
- 42. Pip Willcox
- 43. Tarte, S. Willcox, P., Glaser, H. and De Roure, D. 2015. Archetypal Narratives in Social Machines: Approaching Sociality through Prosopography. ACM Web Science 2015. SégolèneTarte
- 48. A computationally-enabled sense-making network of expertise, data, software, models and narratives Big Data, in a Big Data Centre
- 49. Pip Willcox and Kevin Page
- 50. Β Β consume Β Β produce Β Β compose Β perform Β capture Β Β distribute Β Β Β Β Β Β Β Β Mark Β Sandler Β Curate Β Β Β Β Β Β Preserve Β !
- 51. Notifications and automatic re-runs Machines are users too Autonomic Curation Self-repair New research?
- 52. The Β R Β Dimensions Β Research Β Objects Β facilitate Β research Β that Β is Β reproducible, Β repeatable, Β replicable, Β reusable, Β referenceable, Β retrievable, Β reviewable, Β replayable, Β re-Ββinterpretable, Β reprocessable, Β recomposable, Β reconstructable, Β repurposable, Β reliable, Β respecful, Β reputable, Β revealable, Β recoverable, Β restorable, Β reparable, Β refreshable?β Β @dder 14 April 2014 sci Β method Β access Β understand Β new Β use Β social Β cura6on Β Research Β Object Β Principles Β De Roure, D. 2014. The future of scholarly communications. Insights: the UKSG journal, 27, (3), 233-238. DOI 10.1629/2048-7754.171
- 54. Intersection, Scale, and Social Machines: The Humanities in the Digital World
- 55. First Β Folio Β Social Β Machines Β Metadata Story of the First Folio Social Machines Annotation David De Roure and Pip Willcox ββConiunction, with the participation of Societyβ: Citizens, Scale, and Scholarly Social Machinesβ Beyond the PDF: Born-Digital Humanities, Boston, 27β28 April 2015 Pip Willcox
- 56. PipWillcox
- 57. david.deroure@oerc.ox.ac.uk @dder Thanks to Tim Crawford, Mark dβInverno, Stephen Downie, Iain Emsley, Ichiro Fujinaga, Chris Lintott, Grant Miller, Terhi Nurmikko-Fuller, Kevin Page, Carolin Rindο¬eisch, Glenn Roe, Mark Sandler, SΓ©golΓ¨ne Tarte, David Weigl, and Pip Willcox. http://www.slideshare.net/davidderoure/humanities-in-the-digital-world Supported by SOCIAM: The Theory and Practice of Social Machines, funded by the UK Engineering and Physical Sciences Research Council (EPSRC) under grant number EP/J017728/1; Fusing Semantic and Audio Technologies for Intelligent Music Production and Consumption (FAST) funded by EPSRC under grant number EP/L019981/1; and Transforming Musicology, funded by the UK Arts and Humanities Research Council under the Digital Transformations programme. Thanks also to the Andrew W. Mellon Foundation.
Editor's Notes
- #35: ----- Meeting Notes (25/10/15 20:38) ----- Pipeline to transform the XML into numbers according to a simple set of rules. These numbers are then transformed into sound in the black box. Mention the Hinman collator here and stereoscopy. Used the First Folio Hamlet and the Quartos variants as the test data. One stream Two steams to create an audio version of a steroscopic illusion.