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 Deustodipina@deusto.es

http://paginaspersonales.deusto.es/dipina

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

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

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

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

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

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

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

IES Cities Stakeholders

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

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

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

IES Cities Platform (III)

13

IES Cities Platform Architecture (I)

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 PlayerVirtuoso

Ckan

D2RQ

Dataset

Registration

App RegistrationUser 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

• 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 SQLhttp://iescities.com/IESCities/swagger/

IES Cities RESTful Open API

IES Cities RESTful Open API

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

IES Cities Query Mapper

• 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

• 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 GAL\u00c9, 6",

"lastUpdated": "2013-04-30T00:00:00Z",

"geometry": {

"type": "Point",

"coordinates": [

678191.46,

4614794.52

]

}, ...

]

Step 1: Public Administration Dataset Registration

• 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

• 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

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

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

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

IES Cities Apps

• 16 apps + IES Cities Player have been created:

– E.g. Zaragoza Complains & Suggestions

Apps validating IES Cities solution

• 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 submittedreports)

– 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

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

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.

• 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

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 Deustodipina@deusto.es

http://paginaspersonales.deusto.es/dipina