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Slow-cooked data and APIs in
the world of Big Data:
the view from a city perspective
16/09/2015
Oscar Corcho
ocorcho@fi.upm.es
@ocorcho
https://www.slideshare.com/ocorcho
License
• This work is licensed under the license
CC BY-NC-SA 4.0 International
• http://purl.org/NET/rdflicense/cc-by-nc-sa4.0
• You are free:
• to Share — to copy, distribute and transmit the work
• to Remix — to adapt the work
• Under the following conditions
• Attribution — You must attribute the work by inserting
• “[source Oscar Corcho]” at the footer of each reused slide
• a credits slide stating: “These slides are partially based on
“Slow-cooked data and APIs in the world of Big Data:
the view from a city perspective” by O. Corcho”
• Non-commercial
• Share-Alike
Disclaimers
• I may be politically incorrect at
some points in time
• Don’t feel offended…, it’s a dinner speech
• Please, continue talking to me afterwards
• If you still feel offended, let me invite
you to a beer and discuss about it
• I have some questions for you
• Please respond to them…
• I explicitly asked not to serve tomatoes for dinner…
• Just in case that you are tempted to throw them at me…
• I hope that by the end of the talk, we all learn a bit
about data and slow food
Act 1
On Data and Food
Big Data, Open Data, fast food, slow food
What is Big Data?
Source: http://www.ibmbigdatahub.com/sites/default/files/infographic_file/4-Vs-of-big-data.jpg
What is (Linked) Open Data?
Source: "Linking Open Data cloud diagram 2014, by Max Schmachtenberg, Christian Bizer, Anja Jentzsch and Richard Cyganiak. http://lod-cloud.net/"
What is Big Data?
Source: http://www.ibmbigdatahub.com/sites/default/files/infographic_file/4-Vs-of-big-data.jpg
What is (Linked) Open Data?
Source: "Linking Open Data cloud diagram 2014, by Max Schmachtenberg, Christian Bizer, Anja Jentzsch and Richard Cyganiak. http://lod-cloud.net/"
Big Data, Linked Data and Food
An analogy between Big Data and Fast Food
• Too much data to
consume
• Too little time to
process it
• One is never sure
about the data
provenance
• No time for a good
espresso (or a nice
chat) afterwards
What about slow food?
Quiz 1 of the night
• Let’s see whether we agree on what slow food is…
• Hands up if you think that this is slow food
• Let’s now move into Spain, which I know a bit better
Slow food (and nouvelle cuisine) in Spain
• It’s everywhere, but most of it connected to two
regions with some of the best chefs
• Not sure how long they will be part of Spain anyway ;-)
Basque Country
Catalunya
That’s too experimental: other slow food in Spain
Nothing like a good pisto manchego
The origin for slow-cooked open data in Spain
• It comes from the region of Aragón…
Let’s meet the chef and her team of talented cooks
The Web team at Zaragoza, also responsible for the Open Data portal and API
And let’s see some of their slow-cooked data
Act 2
The five rules for
slow-cooked data
that this team is applying
Rule 1.
Chop your onions
appropriately
Rule 1. Chop your onions appropriately
• Take care about the number of datasets that you
produce
• There’s still a silly competition about
“my open data portal has more datasets than yours”
• This provokes, sometimes, over-segmentation of data
• Main question: What makes a dataset useful and
which datasets should I publish?
Rule 1. Chop your onions appropriately
• UNE 178301:2015
• Norm on Open Data for
Smart Cities
• Organised by
• AENOR CTN 178 group
• Government and Mobility
• Government
• Open Data
(led by Localidata)
• Formed by
• Several cities
• Private companies
• Nation-wide
organisations
Rule 1. Chop your onions appropriately
• 10 datasets selected
• Based on frequency of
requests from reusers
• Target for 2015
• And now working on extending it to 100 datasets
• With an additional group of people
Datasets
Cultural Agenda
Traffic
Population
Streets
Public Transport
Touristic Places and POIs
Budget
Shop Census
Air Quality
Contracts
Parkings
Rule 2.
Add some spices,
but not too many
Rule 2. Add some spices, but not too many
• Annotate (semantically) your data, so that others can
understand what you produce
• And produce examples for consumers to understand them
• Don’t wait until all schema.org properties are settled
• Generate SKOS thesauri for your own classifications
• e.g., for groups of citizens (young, elderly, etc.), for types of
events (cultural, children, music, etc.)
Rule 3. Try different ways of plating up your food
Rule 3. Try different ways of plating up your food
• Produce your data in different formats
• Agreed-upon JSONs
• JSON-LD
• RDF
• Agreed-upon CSVs
• With the upcoming CSV on the Web
• But don’t get crazy at offering all options
• The ones that get finally used are more than enough
Rule 4.
Let children appreciate (and cook) slow food
Rule 4. Let children appreciate (and cook) slow food
Let children understand the
benefits of open data
(and Citizen Science)
and how they can contribute to
improving the data of their city
Rule 5…. Eat your own…
Well, this is not a proper thing
to say for a dinner speech…
Let’s better say…
Rule 5.
Try it out yourself first…
… Before giving your
food to your customers
Rule 5. Try it out yourself first…
• Open data by default
• So that your applications are also based on open data
Source: Los Datos Abiertos como Eje Central del desarrollo de la Plataforma de Gobierno Abierto. M.J. Fernández-Ruiz, V. Morlán
Act 3 (final act)
But whom of you haven’t
ever eaten a burger in his/her life?
(tofu ones as well)
Rule 6.
Fast food has its value
as well, why not…
You go anywhere in the world and know how
McDonald’s burgers are…
So let’s only learn this from fast food..
Rule 6. Fast food has its value as well, why not…
• When we open our data, let’s use at least the same
data structures
Publish
Extract
Publish
Extract
Publish
Extract
I want to publish
my data
I am using GTFS I am using my own CSV
structure
I provide it as a Web
service
Write an app and deploy everywhere
Rule 6. Fast food has its value as well, why not…
So, are we ready to start cooking our open data better?
Slow-cooked data and APIs in
the world of Big Data:
the view from a city perspective
16/09/2015
Oscar Corcho
ocorcho@fi.upm.es
@ocorcho
https://www.slideshare.com/ocorcho

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Slow-cooked data and APIs in the world of Big Data: the view from a city perspective

  • 1. Slow-cooked data and APIs in the world of Big Data: the view from a city perspective 16/09/2015 Oscar Corcho ocorcho@fi.upm.es @ocorcho https://www.slideshare.com/ocorcho
  • 2. License • This work is licensed under the license CC BY-NC-SA 4.0 International • http://purl.org/NET/rdflicense/cc-by-nc-sa4.0 • You are free: • to Share — to copy, distribute and transmit the work • to Remix — to adapt the work • Under the following conditions • Attribution — You must attribute the work by inserting • “[source Oscar Corcho]” at the footer of each reused slide • a credits slide stating: “These slides are partially based on “Slow-cooked data and APIs in the world of Big Data: the view from a city perspective” by O. Corcho” • Non-commercial • Share-Alike
  • 3. Disclaimers • I may be politically incorrect at some points in time • Don’t feel offended…, it’s a dinner speech • Please, continue talking to me afterwards • If you still feel offended, let me invite you to a beer and discuss about it • I have some questions for you • Please respond to them… • I explicitly asked not to serve tomatoes for dinner… • Just in case that you are tempted to throw them at me… • I hope that by the end of the talk, we all learn a bit about data and slow food
  • 4. Act 1 On Data and Food Big Data, Open Data, fast food, slow food
  • 5. What is Big Data? Source: http://www.ibmbigdatahub.com/sites/default/files/infographic_file/4-Vs-of-big-data.jpg
  • 6. What is (Linked) Open Data? Source: "Linking Open Data cloud diagram 2014, by Max Schmachtenberg, Christian Bizer, Anja Jentzsch and Richard Cyganiak. http://lod-cloud.net/"
  • 7. What is Big Data? Source: http://www.ibmbigdatahub.com/sites/default/files/infographic_file/4-Vs-of-big-data.jpg
  • 8. What is (Linked) Open Data? Source: "Linking Open Data cloud diagram 2014, by Max Schmachtenberg, Christian Bizer, Anja Jentzsch and Richard Cyganiak. http://lod-cloud.net/"
  • 9. Big Data, Linked Data and Food
  • 10. An analogy between Big Data and Fast Food • Too much data to consume • Too little time to process it • One is never sure about the data provenance • No time for a good espresso (or a nice chat) afterwards
  • 12. Quiz 1 of the night • Let’s see whether we agree on what slow food is… • Hands up if you think that this is slow food • Let’s now move into Spain, which I know a bit better
  • 13. Slow food (and nouvelle cuisine) in Spain • It’s everywhere, but most of it connected to two regions with some of the best chefs • Not sure how long they will be part of Spain anyway ;-) Basque Country Catalunya
  • 14. That’s too experimental: other slow food in Spain Nothing like a good pisto manchego
  • 15. The origin for slow-cooked open data in Spain • It comes from the region of Aragón…
  • 16. Let’s meet the chef and her team of talented cooks The Web team at Zaragoza, also responsible for the Open Data portal and API
  • 17. And let’s see some of their slow-cooked data
  • 18. Act 2 The five rules for slow-cooked data that this team is applying
  • 19. Rule 1. Chop your onions appropriately
  • 20. Rule 1. Chop your onions appropriately • Take care about the number of datasets that you produce • There’s still a silly competition about “my open data portal has more datasets than yours” • This provokes, sometimes, over-segmentation of data • Main question: What makes a dataset useful and which datasets should I publish?
  • 21. Rule 1. Chop your onions appropriately • UNE 178301:2015 • Norm on Open Data for Smart Cities • Organised by • AENOR CTN 178 group • Government and Mobility • Government • Open Data (led by Localidata) • Formed by • Several cities • Private companies • Nation-wide organisations
  • 22. Rule 1. Chop your onions appropriately • 10 datasets selected • Based on frequency of requests from reusers • Target for 2015 • And now working on extending it to 100 datasets • With an additional group of people Datasets Cultural Agenda Traffic Population Streets Public Transport Touristic Places and POIs Budget Shop Census Air Quality Contracts Parkings
  • 23. Rule 2. Add some spices, but not too many
  • 24. Rule 2. Add some spices, but not too many • Annotate (semantically) your data, so that others can understand what you produce • And produce examples for consumers to understand them • Don’t wait until all schema.org properties are settled • Generate SKOS thesauri for your own classifications • e.g., for groups of citizens (young, elderly, etc.), for types of events (cultural, children, music, etc.)
  • 25. Rule 3. Try different ways of plating up your food
  • 26. Rule 3. Try different ways of plating up your food • Produce your data in different formats • Agreed-upon JSONs • JSON-LD • RDF • Agreed-upon CSVs • With the upcoming CSV on the Web • But don’t get crazy at offering all options • The ones that get finally used are more than enough
  • 27. Rule 4. Let children appreciate (and cook) slow food
  • 28. Rule 4. Let children appreciate (and cook) slow food Let children understand the benefits of open data (and Citizen Science) and how they can contribute to improving the data of their city
  • 29. Rule 5…. Eat your own… Well, this is not a proper thing to say for a dinner speech…
  • 30. Let’s better say… Rule 5. Try it out yourself first… … Before giving your food to your customers
  • 31. Rule 5. Try it out yourself first… • Open data by default • So that your applications are also based on open data Source: Los Datos Abiertos como Eje Central del desarrollo de la Plataforma de Gobierno Abierto. M.J. Fernández-Ruiz, V. Morlán
  • 32. Act 3 (final act) But whom of you haven’t ever eaten a burger in his/her life? (tofu ones as well)
  • 33. Rule 6. Fast food has its value as well, why not… You go anywhere in the world and know how McDonald’s burgers are… So let’s only learn this from fast food..
  • 34. Rule 6. Fast food has its value as well, why not… • When we open our data, let’s use at least the same data structures Publish Extract Publish Extract Publish Extract I want to publish my data I am using GTFS I am using my own CSV structure I provide it as a Web service Write an app and deploy everywhere
  • 35. Rule 6. Fast food has its value as well, why not…
  • 36. So, are we ready to start cooking our open data better?
  • 37. Slow-cooked data and APIs in the world of Big Data: the view from a city perspective 16/09/2015 Oscar Corcho ocorcho@fi.upm.es @ocorcho https://www.slideshare.com/ocorcho