In data is discovery.
"PDF" data
Athletes
Staff
Visitors
Accessible data
CC BY 2.0 familymwr
10'9K ATHLETES
$44 BILLION
4.7 BILLION VIEWERS
"Big" data
CC BY 2.0 familymwr
Athletes
rdf:employee
4.7 BILLION
Web data
CC BY 2.0 familymwr
vcard:title
rdf:employee
foaf:persons
Linked data
"Deep" APIs
CC BY 2.0 familymwr
What we really want to know
plotter?
winner?
pop idol?
mkdir eukaryota; dat init; dat pull http://eukaryota.dathub.org eukaryota; dat import Caprinae.json -d eukaryota; dat push ssh://192.168.0.5:~/data
Pushed 438 changes (32.03 Mb, 4.4 Mb/s). Push completed successfully.
Making from open data
Educating with open data
Collaborating on open data
Acquisition starts
at home.
Problems?
People!
References
Intentions
Map and organise
CC BY 2.0 John Walker
"Release early, release often, and listen to your customers." -E.S.R.
Rinse, repeat, optimise
Data doesn't lie*
* more accurately, it does not know how to lie
Decision maker/consumer
Producer
Researcher/portal
Expert/analyst/app
Sampler
Many layers
one data cake
Further info
Dankeschön
oleg@datalets.ch
@loleg
Open data: smart business
By Oleg Lavrovsky
Open data: smart business
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