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Digital Research Infrastructure
The document discusses the intersection of digital scholarship, automation, and social machines, emphasizing the global collaboration in scientific infrastructure and the evolving role of technology in scholarly activities. It highlights the challenges faced by platforms like Wikipedia and the potential for combining human and machine efforts in classification tasks. The text also explores concepts in AI, responsible innovation, and the future of knowledge infrastructure, promoting creativity and interdisciplinary collaboration.
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Digital Research Infrastructure
- 1. David De Roure DigitalScholarship Intersection, Automation, and Scholarly Social Machines Oxford e-Research Centre Alan Turing Institute @dder
- 2. TORCH DH Zooniverse Linguistics English Oxford Martin School IT Services GeographyPhysics Computer Science Maths History Oxford Internet InsBtute Music Archaeology Classics Zoology Museums Wolfson Bodleian Libraries Pharmacology Biochemistry St Annes PembrokeEngineering e-Science is about global collaboration in key areas of science and the infrastructure that will enable it
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- 4. Digital Scholarship Social Networks More people Moremachines Distributed Computation Conventional Computation Science 2.0 DataScience Citizen Science Scientific Computing Living in IoT Web 2.0 @dder
- 5. More people Moremachines Automation &Machine Learning @dder Digital Scholarship
- 6. Social Machines myExperiment SALAMI New andEmerging Forms of Data Apparatus with Agency From Box 170 to the Barbican
- 8. Social Machines “Real lifeis and must be full of all kinds of social constraint – the very processes from which society arises. Computers can help if we use them to create abstract social machines on the Web: processes in which the people do the creative work and the machine does the administration... The stage is set for an evolutionary growth of new social engines. The ability to create new forms of social process would be given to the world at large, and development would be rapid.” Berners-Lee, Weaving the Web, 1999 (pp. 172–175)
- 9. “Yet Wikipedia andits stated ambition to “compile the sum of all human knowledge” are in trouble. The volunteer workforce that built the project’s flagship, the English-language Wikipedia—and must defend it against vandalism, hoaxes, and manipulation—has shrunk by more than a third since 2007 and is still shrinking… The main source of those problems is not mysterious. The loose collective running the site today, estimated to be 90 percent male, operates a crushing bureaucracy with an often abrasive atmosphere that deters newcomers who might increase participation in Wikipedia and broaden its coverage…” http://www.technologyreview.com/featuredstory/520446/the-decline-of-wikipedia/ 2013
- 11. In an effortto speed up classifications to cope with the large number of galaxies we expect to receive from new surveys, we've been working on ways to combine your classifications with those of machines, inspired by the idea that the combination of both automatic and human classification may be more powerful than either alone. If you choose the 'Enhanced' work flow, you will be much more likely to see the top 100 galaxies our galaxy-classifying robot thinks it needs help with in order to improve. All galaxies will be seen by at least a few volunteers to make sure we aren't missing anything. If you'd rather just see a random selection of available galaxies, choose 'Classic’.
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- 14. Notifications and automaticre-runs Machines are users too Autonomic Curation Self-repair New research? JCDL 2013
- 15. Ada Lovelace Charles Babbage BodleianLibraries 19th Century AI 21st Century AI Audience Human composer Robert Laidlow Alter Text – PRiSM team led by Robert Laidlow Commissioned by Barbican, performed by Britten Sinfonia with Marta Fontanals-Simmons, conductor William Cole, November 2019. Mezzo-soprano Marta Fontanals-Simmons prompts Images © Clay Mathematics Institute
- 16. Open scholarship, s/w Non-consumptiveresearch Social Machines ✓ Reproducible research Jupyter notebooks Co-creation Capacity building Ethics, responsible innovation Innovation in infrastructure ✓ RSEs, Agility, team sizes Archives of the future Linked Data Provenance Comp archival science ✓ Automation ✓ Artificial Intelligence ✓ IoT, NEFD, VR/AR Information security Dave’s checklist of infrastructure points
- 17. Intersection Human, Digital, Physical Across discipline Acrosstime Automation Routine computation on & in collections Artificial Intelligence Social Machines Innovation in the Knowledge Infrastructure Permission to be creative Labs “The best way to predict the future is to invent it”
- 18. Thanks to Ruth Ahnert EiriniGoudarouli Rob Laidlow Grant Miller Pip Willcox