The document discusses the development of collaboration-centered cities using urban apps that leverage open and user-generated data, addressing urban challenges such as congestion, resource management, and aging infrastructure. It emphasizes the role of smart sustainable cities in improving the quality of life and efficiency through citizen participation and innovative solutions. The IES Cities project aims to enhance urban services by promoting user-centric mobile micro-services, enabling better access to and utilization of city data.

1. Collaboration-centred Cities through Urban
Apps based on Open and User-generated Data
Puerto Varas, Chile, 3rd December 2015
Diego López-de-Ipiña, Unai Aguilera, Jorge Pérez
MORElab Research Group, DeustoTech – Deusto Institute of Technology,
Faculty of Engineering, University of Deusto
dipina@deusto.es
http://paginaspersonales.deusto.es/dipina

2. The need for Smart Cities
• Challenges cities face today:
– Growing population
• Traffic congestion
• Space – homes and public space
– Resource management (water and energy use)
– Global warming (carbon emissions)
– Tighter city budgets
– Aging infrastructure and population

3. What is a Smart City?
• Smart Cities improve the efficiency and quality
of the services provided by governing entities
and business and (are supposed to) increase
citizens’ quality of life within a city
– This view can be achieved by leveraging:
• Available infrastructure such as Open Government Data and
deployed sensor networks in cities
• Citizens’ participation through apps in their smartphones
– Or go for big companies’ “smart city in a box”
solutions

4. What is a Smart Sustainable City?
A smart sustainable city is an innovative city that uses
information and communication technologies and
other means to improve quality of life, efficiency of
urban operation and services, and competitiveness,
while ensuring that it meets the needs of present and
future generations with respect to economic, social
and environmental aspects
https://itunews.itu.int/en/5215-What-is-a-smart-sustainable-city.note.aspx

5. Open Data as Enabler of Open Government
• Open government is the governing approach where citizens
have the right to access the documents and proceedings of
the government to allow for effective public oversight
– Enables citizens to get more directly involved in the legislative process
– Open Data brings about:
1. More efficient and effective government
2. Innovation and economic growth
3. Transparency and accountability and
4. Inclusion and empowerment
• BUT, serious lacks on exploiting the potential of Open Data,
since Governments:
– Focused their attention only on implementing their open data portals
– Low effort on bringing open data closer to entrepreneurs and citizens
through suitable APIs, easily consumable by application developers

6. Why Collaborative Cities?
• Not enough with the traditional resource efficiency
approach of Smart City initiatives
• “City appeal and dynamicity” will be key to attract and
retain citizens, companies and tourists
• Only possible by user-driven and centric innovation:
– The citizen should be heard, EMPOWERED!
» Urban apps to enhance the experience and interactions of the
citizen, by taking advantage of the city infrastructure
– The information generated by cities and citizens must be linked
and processed
» How do we correlate, link and exploit such humongous data for all
stakeholders’ benefit?
• We should start talking about Big (Linked) Data

7. Technical Ingredients for
Smart Cities: Broad Data
+ Open APIs
• BroadData: Linked Data + Social Data + IoT Data
– Linked Data: recommended best practice for
exposing, sharing, and connecting pieces
of data, information, and knowledge on the Semantic
Web using URIs and RDF
– Crowdsourced Data: citizens can be viewed as mobile
sensors that monitor the variables of the city, and the
data provided by them as crowd-sourced data
• Open APIs: there are several initiatives trying to
promote Open APIs for Smart Cities: CitySDK,
Open311, Ushahidi

8. IES Cities Project
• The IES Cities project promotes user-centric
mobile micro-services that exploit open and
user-supplied data
– Fosters and accelerates the development and
deployment of new urban services that exploit city
knowledge
• Its platform aims to:
– Enable user supplied data to complement, enrich and
enhance existing datasets about a city
– Facilitate the generation of citizen-centric apps that
exploit urban data in different domains
European CIP
project 36 month
long, finishes in
Feb 2016
http://iescities.eu

9. IES Cities Stakeholders

10. IES Cities Objectives
• To create a new open-platform adapting the technologies and
over taking the knowledge from previous initiatives.
• To validate and test a set of predefined urban apps across
the cities.
• To validate, analyse and retrieve technical feedback from the
different pilots in order to detect and solve the major
incidences of the technical solutions used in the cities.
• To adequately achieve engagement of users in the pilots and
measure their acceptability during the validations.
• To maximize the impact of the project through adequate
dissemination activities and publication of solutions upon a
Dual-license model.
10

11. IES Cities Platform (I)
• IES Cities platform v2 ready for execution of 2nd pilots phase:
– Query Mapper: eases app development:
• Access to dataset information controlled using different mechanisms
including ACL control
• Platform automatically creates and publishes new datasets when an
application developer specifies a schema of dataset for their app
– Logging & Rating interfaces: enables to monitor usage &
acceptance
– IES Cities Entities Management: manages apps, datasets, users
– IES Cities Player: broker among users and platform
– IES Cities Web Interface: offers a web UI for all platform
stakeholders and to manage all entities
• Includes KPI graphical visualization
• Business logic can rely on the client side (HTML5+JS) whilst data
persistence hosting is done at the IES Cities back-end

12. IES Cities Platform (II)
• User-support tools integrated to ensure
platform sustainability:
– IES Cities Forum: http://iescities.freeforums.org/
– IES Cities Contact Form in three supported
languages
– IES Cities Manual including support for
installation, developers and users:
https://iescities.com/IESCities/manual/index.html

13. IES Cities Platform (III)
13

14. IES Cities Platform Architecture (I)

15. IES Cities Platform Architecture (II)
Mobile Apps
Account REST
Interface
REST Interface
IES Cities Player
REST Interface
User Interface
WEB Interface
Developer
Interface
Admin Interface
Council Interface
Apps & DataSet
Stats REST
Interface
Data Wrapper
Query Mapper
Logging Module
Account Interface
Authentication:
Login
Authorization
Scalaris JDO
Data Interface
PostgreSQL
Scalaris
IES Cities Player
Virtuoso
Ckan
D2RQ
Dataset
Registration
App Registration
User Interface
Developer
Interface
Admin Interface
Council Interface
User
Management
IES Cities Player
Interface
Apps Filter
App Data REST
interface
Application Server
Server-side app
specific logic
Data Validator

16. • All the functionality of the IES Cities platform is offered
through a RESTful API which groups operations in the
following categories:
– Entities interface which offers CRUD operations to deal
with the main entities tackled by the project;
– Logging module which enables server-side components to
register diverse events associated to apps life cycle (e.g.
AppStart, AppProsumer and so on), player
interactions (e.g. PlayerAppSearch), or dataset-
related (e.g. DatasetRegistered);
– Query Mapper which offers methods to enable the query
and insertion of data through SQL
http://iescities.com/IESCities/swagger/
IES Cities RESTful Open API

17. IES Cities RESTful Open API

18. Query Mapper
• A key component of this platform devised to
streamline the development of Open Data based
mobile urban apps for web developers:
– Supported datasource types:
• JSON (new), CSV (new), SPARQL, Relational
– User/local created datasets
– Connection with external repositories
– Permissions
– Data response formats:
• JSON and JSON-LD
IES Cities
Dataset
Query
Response
Update
Data source
Data source
type
Mapping
attributes
Permission
section

19. IES Cities Query Mapper

20. • Modus operandi:
1. Public administrations register datasets,
including several metadata fields, e.g. mapping
script between original format and JSON
2. A developer searches and selects a dataset
against which develops his/her app and
registers it with the solution
3. End-users/citizens with the help of the IES Cities
Player browse, search, select and execute a
desired urban app
IES Cities in Use

21. • Datasets registered in the IES Cities platform require a mapping description in
order to be connected with the data sources.
– Supported data sources are: database, sparql, json and csv.
– json_schema data type is used to create user-generated datasets
• Let’s consider the following JSON file from Zaragoza about accommodation:
"result": [
{
"id": 1,
"title": "FELISA GALu00c9, 6",
"lastUpdated": "2013-04-30T00:00:00Z",
"geometry": {
"type": "Point",
"coordinates": [
678191.46,
4614794.52
]
}, ...
]
Step 1: Public Administration Dataset Registration

22. • The following code shows the mapping to register the ZGZ dataset:
– Observe that access control is enabled through the permissions field
{
"mapping": "json",
"uri": "https://www.zaragoza.es/api/recurso/turismo/alojamiento.json",
"root": "result",
"key": "id",
"refresh": 86400,
"table": "hotel"
"permissions": {
"select": [
{
"table": "hotel",
"access": "ALL"
},
{
"table": "hotel_geometry",
"access": "USER",
"users": ["user1", "user2"]
}
]
}
}
Step 1: Public Administration Dataset Registration

23. • For application-specific datasets a the mapping type is "json_schema"
and within the tables field, the schema of each underlying table has to
be defined using JSON syntax
"mapping":"json_schema",
"schema":{
"tables":[
{
"key":"id",
"name":"Comments",
"Comments":[
{
"id":1,
"text":"some_string",
"author":"some_string",
"rating":1,
"app":"some_string",
"date":"2015-01-01"
} ] } ],
Step 1: Public Administration Dataset Registration

24. Step 2: A developer searches and selects a dataset against
which develops his/her app and registers it with the solution

25. Step 2: A developer searches and selects a dataset against
which develops his/her app and registers it with the solution

26. Step3: End-users/citizens browse, search and
select a desired urban app with IES Cities Player

27. IES Cities Apps

28. • 16 apps + IES Cities Player have been created:
– E.g. Zaragoza Complains & Suggestions
Apps validating IES Cities solution

29. • Thanks to the support of the IES Cities a platform, a web developer only needs to
create a query in the standard SQL language and send it to the Query Mapper:
– The query is submitted through a REST API to the IES Cities Query Mapper
(data/query/{datasetid}/sql) which delegates to Zaragoza SPARQL
endpoint and maps the results into JSON
• For Zaragoza council enrichment of its datasets by third parties (userss)
presented some issues:
– Data does not need to be approved before being published
– There is no mechanism to control the amount of data a citizen can add
• Possible VERIFICATION solutions are:
– IntelliSense techniques and other consolidation techniques (earlier submitted
reports)
– Social opinion: enable end-users to vote up or down reports
• The adopted VERIFICATION solution has been:
– End-user suggestions and complaints are first validated by an officer before
they can be viewed and voted for by the final users
Zaragoza Complaints & Suggestions

30. Apps Evaluation Methodology
• The Compass Acceptance Model has been taken as reference for
the evaluation process: feedback and assessment of the apps
– The original CAM contains ease of use, usefulness, cost and
mobility factors.
• To replace mobility we have added “interaction with the city”
Reported
ease of use
Reported
usefulness
Costs and
Efforts
Reported
interaction
with the
city
Short Term
Short Term
Short Term
Short Term
Long Term
Long Term
Long Term
Low
Neutral
High

31. Apps Evaluation Methodology
• Degree of acceptance of apps measured by:
– Definition of a range of Key Performance Indicators (KPIs).
• Defined regarding the types of users and for the different apps uses.
• Some common KPIs defined across apps are: a) number of
downloads, b) number of active users, c) users activity based on data
consumption, d) users activity based on data contributions
– Set-up of a range of data sources to feed the KPIs:
• User questionnaires were obtained by asking users directly about
their opinions and experiences with the application
• Logging data was generated from logs of events generated by the app
in use
• Google Play, i.e. the marketplace where our apps have been
uploaded has been checked to obtain online application distribution
service;
• Platform stats were extracted from other meta-data stored in the IES
Platform
– A mapping of data sources to KPIs has been performed.
• Available data sources values assigned to KPI variables.

32. • IES Cities platform allows councils to manage their
dataset and urban app ecosystem
– Aimed to increase the quality of life of their citizens and to
foster economy promotion
– Allowing both administration provided and end-user
generated data exploitation
• The IES Cities’ Query Mapper component streamlines
Open Data-based app development:
– A SQL-based interface which returns as result the lingua
franca of web developers, i.e. JSON
• 16 apps across 4 European cities have been developed
and are currently being tested.
Conclusions

33. Collaboration-centred Cities through Urban
Apps based on Open and User-generated Data
Puerto Varas, Chile, 3rd December 2015
Diego López-de-Ipiña, Unai Aguilera, Jorge Pérez
MORElab Research Group, DeustoTech – Deusto Institute of Technology,
Faculty of Engineering, University of Deusto
dipina@deusto.es
http://paginaspersonales.deusto.es/dipina