This is the presentation of the #ojoaldata100 initiative (http://ojoaldata100.okfn.es) for the selection of 100 datasets that every city should be publishing in their open data portal. This presentation was used in a call for sharing session at the 4th International Open Data Conference (IODC2016).

1. Call for Sharing session at IODC 2016, Madrid, 7 Oct 2016
Oscar Corcho, @ocorcho (on behalf of the #OjoAlData100 group)
Slides available at www.slideshare.com/ocorcho
#OJOALDATA100
http://ojoaldata100.okfn.es/

2. Página 2#OJOALDATA100
Before we start… The team
(acknowledgements)

3. #OJOALDATA100
Alberto Abella
Oscar
Corcho
Esther Minguela
Victoria López
Andrés Recio
Guadalupe Miñana
Antonio Ibáñez
Eva Méndez
Nancy Gómez
Santiago Mota
Enrique Crespo
… And all those who participated
in the UNE178301 technical norm
Olga Quirós

4. #OJOALDATA100
Structure of the session
 The OjoAlData100 initiative: introduction and presentation of
attendees
 Our starting point: the UNE178301:2015 technical norm on Open
Data and Smart Cities.
 From 10 to 100 datasets
 Technical infrastructure for vocabulary management
 Next steps
 Open discussion with attendees

5. #OJOALDATA100
Structure of the session
 The OjoAlData100 initiative: introduction and presentation
of attendees
 Our starting point: the UNE178301:2015 technical norm on Open
Data and Smart Cities.
 From 10 to 100 datasets
 Technical infrastructure for vocabulary management
 Next steps
 Open discussion with attendees

6. #OJOALDATA100
What is #OJOALDATA100?
Our proposed catalogue of 100
DATASETS that every city should be
publishing in their open data portal/API
A community-based effort rooted in
Madrid, and based on previous
nationwide experiences

7. #OJOALDATA100
Why #OJOALDATA100?
No clear guidelines for cities on what to
publish
Heterogeneity
Reusers want to:
Develop once, deploy everywhere

8. #OJOALDATA100
City Census
http://us-city.census.okfn.org/, http://es-city.census.okfn.org/, etc.
 Annual Budget
 Public Facilities
 Procurement contracts
 Transport Timetables
 Election results
 Air Quality
 Expenditure (detailed)
 Real-Time Transit
 Business Listings
 Traffic accidents
 Service Requests
 Building permits
 Business Permits
 Crime statistics
 Food safety inspections
15

9. #OJOALDATA100
11
UNE 178301: Open Data for Smart Cities
 Shop census
 Cultural agenda
 Population census
 Air quality
 Public procurement
 Budget
 Public parking
 Public transport
 Traffic
 Tourism-relevant places
 Streets

10. #OJOALDATA100
World Council on City Data (ISO 37120)
100 indicators (not datasets)
Organised in 17 themes
Economy
Education
Energy
Environment
Finance
Fire & Emergency
Response
Governance
Health
Recreation
Safety
Shelter
Solid Waste
Telecommunications
Transportation
Urban Planning
Wastewater
Water & Sanitation
100

11. #OJOALDATA100
And a few others
UK’s PAS 181 Smart City Framework
Smart city’s catalogue from AMETIC (National IT
companies Association)
 And all those that can be derived from the
different transparency indicators…
 Although open data and transparency are not the same
thing

12. #OJOALDATA100
Which are our main challenges?
• What should we publish?
• Added value for cities
• Added value for reusers
• Available legislation
• How should we publish it?
• In which format(s)?
• With which level of detail?

13. #OJOALDATA100
Our decision
Let’s work towards creating a
rich catalogue of datasets
(around 100), with a wide range
of stakeholders and following a
bottom-up approach
Thanks to…

14. #OJOALDATA100
Structure of the session
 The OjoAlData100 initiative: introduction and presentation of
attendees
 Our starting point: the UNE178301:2015 technical norm on
Open Data and Smart Cities
 From 10 to 100 datasets
 Technical infrastructure for vocabulary management
 Next steps
 Open discussion with attendees

15. #OJOALDATA100
UNE 178301. Introduction. Team
 Working group CTN 178. Ciudades Inteligentes
 Promoted by:
• AENOR
• Ministry of Industry, Energy and Tourism
(Secretary for Telecommunications
and the Information Society – SETSI)

16. #OJOALDATA100
UNE 178301. Introduction. Team
Coordinators:
 Localidata. Esther Minguela and Oscar Corcho
Participants (37):
 6 private companies
 10 city councils
 3 regions
 3 ministries
 2 other
This work would not have been
possible without the collaboration
of this group of people

17. #OJOALDATA100
UNE 178301. Introduction. Needs
Reference document for city managers and non
experts in open data
Unify heterogeneity of criteria in open data
strategies
More of a guideline, rather than a pure technical
norm
 Not just technical
 It’s more about understanding where we are and where
we should reach
Data interoperability among cities

18. #OJOALDATA100
This standard establishes how to assess the publication of a City's
Open Data.
It is determined in the form of metrics and an indicatorto
measure the degree of maturity of open data created or held by the
public sector that may be reused in the scope of Smart Cities. This
standard is applicable to the public sector entity responsible for city
management.
It also establishes a list of data setsthat are considered a
priorityin open data initiatives, together with a set of
vocabularyrecommended for use in their publication.
UNE 178301. Introduction. Summary

19. #OJOALDATA100
Strategic aspect
• Strategy
• Leadership
• Commitment to service
• Sustainability
Legal aspect
• Internal and external regulations
• Terms of use and licensing
Organisational aspect
• Responsible unit
• Personnel and training
• Inventory
• Priority
Measuring aspect
• Measurement of process
compliance
• Measurement of use and impact
Availability aspect
• Catalogue
• Presence in the Catalogue of
Public Information
• Documented data sets
• Categorisation and search
• Availability
• Persistent and friendly
references
UNE 178301. Metrics (I)

20. #OJOALDATA100
Access aspect
• Strategy
• Accessibility/Non-discrimination
• Cost-free status
• Access systems
Quality aspect
• Primary data
• Complete data
• Documented data
• Technically correct data
• Georeferenced data
• Linked data
Updating aspect
• Updating process
• Updating frequency
• Expansion of data sets
Reuse aspect
• Amount of data
• Data format
• Standard data vocabularies
Participation and collaboration aspect
• Transparency, participation and
collaboration
• Complaint and dispute resolution
• Promoting reuse
• Developed reuse initiatives
UNE 178301. Metrics (II)

21. #OJOALDATA100
Datamanagement
Strategy
Legal Organizational
Measurements
AvailabilityAccess
Quality
Updates
Reuse
Participation and
collaboration
UNE 178301. Metrics. Example

22. #OJOALDATA100
UNE 178301. Metrics. Example

23. #OJOALDATA100
Initial
assessment
Application during
the deployment
MeasuringContinuous
improvement
UNE 178301. Metrics. Indicator

24. #OJOALDATA100
Publish
Semantic
Extract
Open data publishing according
to the UNE 178301 vocabularies
and data structures
UNE 178301. Datasets and vocabularies.

25. #OJOALDATA100
UNE 178301. Datasets and vocabularies. Example
Dataset Vocabulary
General vocabularies – Postal Address Vocabulary:
http://vocab.linkeddata.es/datosabiertos/def/urbanismo-infraestructuras/direccionPostal
– Territorial Unit Vocabulary
http://vocab.linkeddata.es/datosabiertos/def/sector-publico/territorio
Budget – Vocabulary: http://vocab.linkeddata.es/datosabiertos/def/hacienda/presupuesto
Public procurement – Vocabulary: http://contsem.unizar.es/def/sector-publico/pproc
Air quality – Vocabulary: http://www.w3.org/2005/Incubator/ssn/ssnx/ssn
Traffic status – Vocabulary: http://vocab.linkeddata.es/datosabiertos/def/transporte/trafico
Public transport – Vocabulary: http://vocab.linkeddata.es/datosabiertos/def/transporte/transportePublico
… …

26. #OJOALDATA100
International. ITU:
UNE 178301 Ciudades Inteligentes. Datos Abiertos
Spain: AENOR-SETSI:
Without homogeneisation, open city
data will not reach their full potential
Y.ODI. Open Data Indicator in Smart Cities
UNE 178301. International

27. #OJOALDATA100
Structure of the session
 The OjoAlData100 initiative: introduction and presentation of
attendees
 Our starting point: the UNE178301:2015 technical norm on Open
Data and Smart Cities.
 From 10 to 100 datasets
 Technical infrastructure for vocabulary management
 Next steps
 Open discussion with attendees

28. #OJOALDATA100
Accordion way of working
 10 starting
 After different contributions
 Including personal experience
 More than 250 datasets

29. #OJOALDATA100
Funnel process
 Approach: Focus on an average city (global)
 Seaside/Port?
 Size above … 20k inhabitants
 Not megacities
 City competences
 Spain
 Abroad

30. #OJOALDATA100
Funnel process
 Remove duplicates
 Consolidate others
 Detected our lack of competence on some fields
 Remove conflictive datasets
 Results : around 170

31. #OJOALDATA100
Funnel process
 Priorities
 Based on citizen perspective
 And on potential apps/external services
 Consensus based (when possible :-D)
 Voting in case of conflict (few times)

32. #OJOALDATA100
Just a sample (those starting with “A”)
Accidentalidad del tráfico (coches, motos, bicis, heridos, muertos, ….)
Actividad inspectora. (se puede publicar la actividad inspectora, pero no así la sancionadora)
Actos en vía pública
Actuaciones Bomberos
Actuaciones de atención social a personas (mayores, sin hogar, etc.)
Actuaciones de urgencias (SAMUR, sociales, o similares)
Actuaciones Policía y Protección Civil
Agenda (Municipal y Alcaldía)
Agenda de Actividades (se unifica en una agenda todo) incluyendo cursos y cursos deportivos
Agentes económicos que pagan impuestos
Albergues y centros de noche (oferta y uso)
Alquiler de vivienda pública
Aparcamiento público
Aparcamiento y reserva en vía pública
Arbolado y Arbolado monumental
Avisos, Sugerencias, Quejas y Reclamaciones

33. #OJOALDATA100
Getting into details
 Is there any open standard / vocabulary / best practice?
 Yes → done (we choose it)
 No → OMG
 Decide the minimum data to be present
 Additional data can be included

34. #OJOALDATA100
http://ojoaldata100.okfn.es/

35. #OJOALDATA100
Structure of the session
 The OjoAlData100 initiative: introduction and presentation of
attendees
 Our starting point: the UNE178301:2015 technical norm on Open
Data and Smart Cities.
 From 10 to 100 datasets
 Technical infrastructure for vocabulary management
 Next steps
 Open discussion with attendees

36. #OJOALDATA100
Vocabularies for #OjoAlData100
Objective
 Define the shared data structures to be used by all cities
adhering to #OjoAlData100
Shared data structure == vocabulary == ontology
Realisations in
 OWL (to be used for RDF data)
 JSON-LD contexts
 CSV structures
Very important: Good documentation (a CSV
structure with no documentation is useless)

37. #OJOALDATA100
https://github.com/opencitydata

38. #OJOALDATA100
Tooling landscape
based on
Evaluation
Documentation
Publication
Registration
integrates
integrates integratesintegrates
Developed at…

39. #OJOALDATA100
URLs
 vocab.linkeddata.es
 URL: http://vocab.linkeddata.es/
 GitHub: https://github.com/mariapoveda/vocab.linkeddata.es/
 vocabLite
 GitHub: https://github.com/dgarijo/vocabLite
 OnToology
 URL: http://ontoology.linkeddata.es
 GitHub: https://github.com/OnToology/OnToology/
 AR2DTool
 URL: http://ar2dtool.linkeddata.es/
 GitHub: https://github.com/idafensp/ar2dtool
 Widoco
 Github: https://github.com/dgarijo/Widoco/
 OOPS!
 Web application: http://oops.linkeddata.es/
 Web service: http://oops-ws.oeg-upm.net/
 Vocabularium
 GitHub: https://github.com/SmartDeveloperHub/sdh-vocabulary/tree/feature/publisher

40. #OJOALDATA100
OnToology
Evaluation reports
HTML documentation
Diagrams
Permanet ids
Content negotiation
Bundle
Previsualization

41. #OJOALDATA100
A landing page for each repository
Extracted from ontology metadata
Errors produced in generation
Work in progress

42. #OJOALDATA100
Example. Public services offered by a city
https://opencitydata.github.io/sector-publico-
servicio/index.html

43. #OJOALDATA100
Structure of the session
 The OjoAlData100 initiative: introduction and presentation of
attendees
 Our starting point: the UNE178301:2015 technical norm on Open
Data and Smart Cities.
 From 10 to 100 datasets
 Technical infrastructure for vocabulary management
 Next steps
 Open discussion with attendees

44. #OJOALDATA100
Next steps (I)
 Disseminate (refine, extend and adapt) the
catalogue (#ojoaldata100)
 In Spain, via the Spanish thematic network on Open Data
for Smart Cities (www.opencitydata.es)
 Internationally
 Connect with the ISO 37120
indicators
 Datasets to be used to generate
those indicators
 Discussed at OpenCitiesSummit

45. #OJOALDATA100
Next steps (II)
 Continue improving technical infrastructure
 Much of it available at https://github.com/oeg-upm/
 Create working groups for specific datasets
 Similarly to what is being done
with OpenContracting, Open311,
etc.
 We need dataset leaders
 We will provide help, but not do
all the work required
Events will be organised over the next year to get
together and discuss (and work) about results

46. #OJOALDATA100
Structure of the session
 The OjoAlData100 initiative: introduction and presentation of
attendees
 Our starting point: the UNE178301:2015 technical norm on Open
Data and Smart Cities.
 From 10 to 100 datasets
 Technical infrastructure for vocabulary management
 Next steps
 Open discussion with attendees
 Would you apply this in your country?
 Do you know of other similar initiatives?
 How do we apply this for the whole world?
 Do you want to help on this?