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