Big Data goes to the movies: Kinomatics Part 2
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Reflection on the challenges and opportunities provided by the Kinomatics database: A large dataset of global cinema showtimes.
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Big Data goes to the movies: Kinomatics Part 2
- 1. Deakin University CRICOS Provider Code: 00113B KINOMATICS: BIG DATA GOES TO THE MOVIES DEB VERHOEVEN (DEAKIN UNIVERSITY) @BESTQUALITYCRAB
- 2. Deakin University CRICOS Provider Code: 00113B KINOMATICS: BIG DATA WILL GO TO THE MOVIES DEB VERHOEVEN (DEAKIN UNIVERSITY) @BESTQUALITYCRAB
- 3. Deakin University CRICOS Provider Code: 00113B KINOMATICS: BIG DATA WENT TO THE MOVIES DEB VERHOEVEN (DEAKIN UNIVERSITY) @BESTQUALITYCRAB
- 4. Deakin University CRICOS Provider Code: 00113B RECAP: What is Kinomatics? •KINEMATICS: THE STUDY OF THE GEOMETRY OF MOTION •KINOMATICS: THE STUDY OF THE INDUSTRIAL GEOMETRY OF MOTION PICTURES
- 5. Deakin University CRICOS Provider Code: 00113B Kinomatics.com
- 6. Deakin University CRICOS Provider Code: 00113B RECAP: Who is Kinomatics? Deb Verhoeven (Cinema Studies; Digital Humanities) Colin Arrowsmith (Geospatial Science) Alwyn Davidson (Geospatial Science) Bronwyn Coate (Economist) Ben Eltham (Cultural Policy) Stuart Palmer (Network Analyst)
- 7. 150 million showtimes 60 000 movies 55 000 venues 48 countries Visualisation: Alwyn Davidson
- 8. Deakin University CRICOS Provider Code: 00113B RECAP: What is Kinomatics?
- 9. Deakin University CRICOS Provider Code: 00113B RECAP: What is Kinomatics?The major research aim of Kinomatics is to foster and investigate: • the global flow of culture – in particular in the film industry; • the computational turn in cinema (and music) research; • innovative approaches to digital research methodologies; • models for ‘big’ cultural data research.
- 10. Deakin University CRICOS Provider Code: 00113B “BIG” data It’s not how big your data is, it’s what you do with it that counts
- 11. Deakin University CRICOS Provider Code: 00113B “BIG” data and anxiety •Size anxiety - dimensia - who has the biggest? •Primacy anxiety - who came first? Or who did it first?
- 12. Deakin University CRICOS Provider Code: 00113B ONE YEAR LATER… Big Data doesn’t immediately equate to Big Breakthroughs. Moving beyond The Obvious takes work.
- 13. Deakin University CRICOS Provider Code: 00113B FLOW?
- 14. Deakin University CRICOS Provider Code: 00113B SCALE?: cinemacities.com
- 15. Deakin University CRICOS Provider Code: 00113B TIME?: HOBBIT EARS
- 16. Deakin University CRICOS Provider Code: 00113B TIME?: HOBBIT YEARS
- 17. Deakin University CRICOS Provider Code: 00113B TIME?: PLAYWEEKSW ednesday-Tuesday Thursday-W ednesday Friday-Thursday Saturday-Friday No Data
- 18. Deakin University CRICOS Provider Code: 00113B MULTIPLE TEMPORALITIES • Data describes showtimes at the level of individual sessions that are projected to occur in a forthcoming week • Data arrives at kinomatics weekly • Data is obsolete after one month (and is disposed of by the data provider) • Showtime data in the kinomatics database is replaced on a weekly basis if records are incomplete • The kinomatics database itself is built in ‘legacy’ data formats (MySQL)
- 19. Deakin University CRICOS Provider Code: 00113B BEYOND BINARIES Above Below Theoretical Empirical Big Small Fast Slow Uniform Heterogeneous Distant Close Global Local Generated Recuperated Now Then Abstract Concrete
- 20. Deakin University CRICOS Provider Code: 00113B BIG DATA AND NCH Big Data changes the past by changing our approach to it. Working with Big Data invites researchers to reflect on the nature of history itself: how do we deal with passing media, passing technologies and also passing ideas about ‘newness’ itself? If we understand information systems as inherently theoretical and temporary formations/formulations then what theoretical and historical questions do they themselves recommend?
- 21. Deakin University CRICOS Provider Code: 00113B BIG NEW CINEMA HISTORY I am large, I contain multitudes Walt Whitman, Song of Myself
- 22. Deakin University CRICOS Provider Code: 00113B THE ORDERING OF THINGS Reflect on changes in our own temporality as researchers: knowledge is always in process—not a priori nor a posteriori
- 23. Deakin University CRICOS Provider Code: 00113B MIND BLOWN?
- 24. Deakin University CRICOS Provider Code: 00113B HOLD THAT THOUGHT
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- To date digital cinema research has been undertaken through of a series of initiatives produced “from below” (Maltby et al). This preference for working with local datasets is consistent with recent methodological breakthroughs in cinema historiography sometimes known as the New Cinema History. Without exception the existing datasets that form the empirical basis for digital cinema research have occurred at the national or sub-national level. Cinema datasets have been generated for scholarly research projects focussed on (and not limited to): London (Christie), the Netherlands (Dibbets), Ghent (Biltereyst et al), Antwerp (Meers et al), Australia (Maltby et al; Verhoeven et al), Scotland (Hopwood et al) and North Carolina (Robert C. Allen). Each of these datasets were developed independently to solve specific research problems and they are not technically or semantically compatible. The prospect of interoperating these data collections remains a tantalising but near impossible challenge with few options for resourcing an undertaking of this magnitude. Whilst the proliferation of these digital case studies has produced a great deal of methodological innovation in Cinema Studies, this disjointed approach has also resulted in a significant deficit in our understanding of the global nature of the cinema. These distributed computational platforms are not yet capable of addressing the global, elastic, and networked nature of the contemporary international film industry currently producing and exploiting huge quantities and varieties of data. - See more at: http://kinomatics.com/about/what-is-kinomatics/#sthash.75Zssawz.dpuf Through its use and development of digital research techniques the project will also open broader questions; How might the opportunities presented by an unprecedented proliferation of networked data for example, also challenge the unspoken assumptions and ordinary practices of conventional film studies research? And how might the ‘computational turn’ present opportunities (and challenges) for a New Cinema History at the intersection of qualitative historiographies (focused on the social experience of the cinema) and quantitative research approaches such as data mining, empirical analysis and digital visualisations?
- How many cars stacked to the moon. (220,000 km almost all the way to the moon) How many soccer balls in a swimming pool (we would fill 452 Olympic sized swimming pools)
- All our research described here relies on our showtimes data
- How many cars to the moon. (around 785 round trips to the moon) How many soccer balls in a swimming pool (we would fill 452 Olympic sized swimming pools)
- How many cars to the moon. (around 785 round trips to the moon) How many soccer balls in a swimming pool (we would fill 452 Olympic sized swimming pools)
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- Imperial anxieties – field setting, territorial, anxieties of occupation and ownership (control). Volume. Spatial anxiety. Velocity…Temporal anxiety. Other anxieties – hydrophobia, technophobia and so on.
- Decoherence – an interaction with wider environment that wipes out quantum behaviour. Loss of information from a system into the environment. Entanglements are generated between system and environment. Decoherence provides an explanation for the transition of the system to a mixture of states that seem to correspond to those states observers perceive. HOBBIT viz - Does the word flow have any meaning in the world of select all.
- Scale – country and city level for the moment. Complex levels of analysis combining different data sets a huge problem at global scale. (e.g. no global database of cities). Country information when city information is not available. (use cinema cities). Working with country boundaries - where they are administrative but not necessarily practically lived. Accounting for border effects for example. How can we use the detailed data to full advantage (i.e. not just to generalize). Cannot combine information at a suburb level. So different scales will always. Our analysis will always be multi-scaled.
- Data describes a legacy (yet persistent) media industry. Show me the history? How does DICIS relate to HOMER. Richard Maltby’s remarks distinguishing historical effort from contemporary studies.
- The 5th V of big data – volume, velocity, variety, veracity and also vantage Every new field also has a theory about the past and the present, of change, of what was and what is, a notion of time: a theory of history. New Cinema History – already contains in its title an historiographic inclination. The use of ‘new’ already implies a notion of a past.
- Franco Moretti got it partly right. Changes are occurring at scale but … Big new cinema history is multi-scaled. Not just about long versus short of it. Through its focus on multiple scales, velocities and locations of cultural diffusion, Kinomatics addresses the global, elastic and networked nature of the contemporary international film industry that is itself producing and exploiting huge quantities and varieties of data.
- Research itself is always in beta mode—what’s important is not the end result of a purely scholarly exercise but the iterative, multimodal, recursive, and co-created aspects of engagement.
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