The document discusses how data from the Internet of Things and citizen science can be used for public benefit. It outlines how data is being generated from more sources and in larger volumes, and how this data combined with artificial intelligence is fueling a new data economy. It also presents several approaches for how citizens can be engaged to help refine open government data through incentives and blockchain-based systems, moving from just consuming open data to co-creating and maintaining public services.
Internet de las cosas y datos de ciencia ciudadana para uso público
1. 1
Internet de las cosas y datos de ciencia
ciudadana para uso público
La Transformación digital: Aspectos a considerar en el
futuro Plan Estadístico y Cartográfico de Andalucía 2021-2027
Sesión II: Territorios inteligentes e inteligencia artificial
18 de Noviembre 2020, 9:30-9:50
Dr. Diego López-de-Ipiña González-de-Artaza
dipina@deusto.es
http://paginaspersonales.deusto.es/dipina
http://www.morelab.deusto.es
@dipina
2. 2
Agenda
• Generación de datos: IoP & Citizen science
• Explosión datos + IA = Economía de Datos
– Data Marketplaces: EDI & REACH
• Explotación de los datos:
– Ciudadanos co-idean, co-crean y co-explotan
(WeLive)
– Colaboración sostenible entre ciudadanos y
personas (AUDABLOK)
3. 3
Internet of Things (IoT) Promise
• There will be around 25 billion devices connected to the
Internet by 2030
– A dynamic and universal network where billions of identifiable
“things” (e.g. devices, people, applications, etc.) communicate
with one another anytime anywhere; things become context-
aware, are able to configure themselves and exchange
information, and show “intelligence/cognitive” behaviour
5. 5
Human-mediated Mobile Sensing:
Citizen Science & Users as prosumers
• The combination of varied data sources such as Humans,
SmartPhones and sensors gives place to Mobile
Sensing/Participatory Sensing & CrowdSensing → Broad Data
6. 6
User-generated Data: Google Maps vs.
Open Street Map
• OSM is an excellent cartographic product driven by user contributions (crowd sensing)
• Google Maps has progressed from mapping for the world to mapping from the world,
where cartography is not the end product, but rather the necessary means for:
– Google’s autonomous car (Waymo) combines sensors, GPS & 3D maps for self-driving cars.
– Google’s Project Wing: a drone-based delivery systems to make use of a detailed 3D model
of the world to quickly link supply to demand
• By connecting the geometrical content of its Google Maps databases to digital traces
that it collects, Google can assign meaning to space, transforming it into place.
– Mapping by machines if not about “you are here”, but to understand who you are, where
you should be heading, what you could be doing there!
7. 7
Data generation is changing …
• 90% of the world’s data
was created in the last two
years
• 80% of enterprise data is
unstructured
• Unstructured data growing
2x faster than structured
• 90% of the world’s data
was created in the last two
years
• 80% of enterprise data is
unstructured
• Unstructured data growing
2x faster than structured
8. 8
Data Deluge
• Netflix transmite
694.444 horas de
video
• Instagram publica
277.777 historias
• Se ven 4.500.000
videos en Youtube
• Se envían 511.200
tweets
• 231.840 llamadas
de Skype
• Airbnb recibe
1.389 reservas
• En Uber se
realizan 9.772
viajes
• Usan Tinder
1.400.000
personas
• Google realiza
4.497.420
búsquedas
11. 11
Datos: el “maná” de la
Inteligencia Artificial (algoritmos)
• Cuantos más datos se creen, mejor comprensión y sabiduría
podrán obtener las personas y las máquinas
20. 20
Connecting Data Providers with
Solution Providers through Data
Analytics
Smart tuning of the thermal
plant to reduce gas
consumption
Smart tuning of the thermal
plant to reduce gas
consumption
Thermal power plant smart
management
Thermal power plant smart
management
Energy
management
system data +
Weather station
21. 21
Creation of cross sector
Data Value Chains (DVC)
enables the EU data
ecosystem to reap socio-
economic benefits from
large-scale deployment of
data-based products and
service
Support for innovation
experiments promoting
the development of secure
and privacy-aware
analytics solutions based
on proprietary industrial
and personal data is
required
Special emphasis should
be placed on access to,
sharing and use of data,
data security, Artificial
Intelligence and
environment of trust
(European Commission)
22. 22
“A Data Value Chain represents a multi-stakeholder data workflow whereby applying
data analytics, both data and solution providers reciprocally benefit through joint
exploitation models”
• A multi-stakeholder ecosystem of actors in data value chains
• Select, incubate and coach +100 data-driven SMEs and startups –
11 month incubation programmes focusing on business-oriented
experimentations on multi-stakeholder trusted and secure data
value chains
• Run 3 Open Calls Rounds (Startups, Data Providers, DIHs and
Investors)
• Distribute 3.5mil EUR to Startups and SMEs
• Early involvement of 5 data providers (finance, retail, digital
marketing, tourism & entertainment, media) and DIHs
(healthcare, energy, transport, social services, tourism) as
catalysers to promote sub-granted experiments solving proposed
challenges and data value chain themes
23. 23
Towards smarter environments …
• Broad Data aggregates data from heterogeneous sources:
– Open Government Data repositories
– User-supplied data through social networks or apps
– Public private sector data or
– End-user private data
• Humongous potential on correlating and analysing Broad
Data in the city/region context:
– Leverage digital traces left by citizens in their daily interactions with
the city to gain insights about why, how and when they do things
– We can progress from Open Data to Open Knowledge
• Energy saving, improve health monitoring, optimized transport system,
filtering and recommendation of contents and services
24. 24
Beyond Open Data Government Portals
CITIZENS have
NO SKILLS or TOOLS to
utilize COMPLEX DATA
LOW BENEFITS
from OPEN DATA
published by CITIES
25. 25
WeLive provides tools and a methodology to promote CO-
CREATION where data publishers, citizens and developers
can meet each other and CO-DESIGN and CO-EXPLOIT
personalized and sustainable public services for real needs
and actively take part in the value-chain of a municipality
or a territory
WeLive provides tools and a methodology to promote CO-
CREATION where data publishers, citizens and developers
can meet each other and CO-DESIGN and CO-EXPLOIT
personalized and sustainable public services for real needs
and actively take part in the value-chain of a municipality
or a territory
CitizensCitizens CompaniesCompaniesP. AdministrationP. Administration
Project Aim
26. 26
WeLive approach
Stakeholder Collaboration + Public-private Partnership →
IDEAS >> APPLICATIONS >> MARKETPLACE
Stakeholder Collaboration + Public-private Partnership →
IDEAS >> APPLICATIONS >> MARKETPLACE
WeLive offers tools to transform the needs into ideasWeLive offers tools to transform the needs into ideas
Tools to select the best Ideas and create the B. BlocksTools to select the best Ideas and create the B. Blocks
A way to compose the
Building Blocks into mass
market Applications which
can be exploited through the
marketplace
A way to compose the
Building Blocks into mass
market Applications which
can be exploited through the
marketplace
1
2
3
27. 27
Full CO-CREATION Lifecycle
Support
CO-BUSINESSCO-MAINTENANCECO-IMPLEMENTATIONCO-IDEATION
WeLive Platform
WeLive Hosting Environments
CO-DESIGN
The core WeLive Platform supports the first phases
of the CO-CREATION lifecycle by giving tools for
innovating and implementing services together
CO-CREATION
CO-CREATION of SUSTAINABLE services requires
support for both CO-DESIGN and CO-
EXPLOITATION
CO-EXPLOITATION
WeLive Hosting Environments support CO-
MAINTENANCE of co-created services. Preliminary CO-
BUSINESS support has been implemented into the CNS
Marketplace
28. 28
Crowdsourcing & gamification are not
enough to truly engage users …
• Civil servants are reluctant to moderate the contents
provided by end-users
• End users are usually initially motivated, but their
contributions are diminished in time:
– Receiving no feedback is discouraging
– If the benefit is not clear or reward immediate → eventually user
contributions diminish
• Quality of the provided data may vary from one citizen to
another (duplication, miss-classification, mismatching )
• Conclusion: Human Computation is appealing but requires
(moderation + automatic quality assessment) and continuous
high involvement
29. 29
AUDABLOK: User-engagement for
for Data Refinement
• AUDABLOK explores how to turn consumers of open
data (public services) into prosumers:
– refining and enhancing contents, through incentivized
crowdsourcing, encouraging more proactive users
• Software framework to make open government data
portals increasable evolvable and sustainable in
time. HOW?
– By combining Human Computation & Internet of People
– KISS principle: Pull Request combined with Blockchain
30. 30
Engagement driven by
Incentivization
• AUDABLOK improves citizen collaboration through
incentivisation (token economy) and recognition,
i.e., trustworthy recording of citizen collaborations
– Blockchain is used to deal with rewarding and recognition
aspects, i.e. higher co-creation of citizens
32. 32
AUDABLOK: Technical solution
• Integrate:
– Redmine – an open source issue management system for
handling issues raised from user-generated contributions t
– Ethereum —an open source, public, blockchain-based
distributed computing platform and operating system
featuring smart contract (scripting) functionality—into
– CKAN open data management software—an open source
tool which makes data accessible by providing tools to
streamline publishing, sharing, finding, and using data.
• AUDABLOK behaves as smart oracle which feeds
Ethereum network, recording citizen-initiated Open
Data refinement transactions
34. 34
Conclusion
• Huge opportunities to exploit data & enter Data Economy
– Broad Data → Open Data + Industrial Data + Human-generated data
need to be aligned, mixed and correlated
• Open Data Portals + IoT devices + User apps (citizen science)
• Citizen collaboration is a must for prosuming data &
collaborating in Open Innovation processes
• Disruptive technologies & citizen engagement approaches to
be seamlessly combined, with an ICT for good perspective:
– Big Data, Transparent AI, co-creation & Blockchain, which can:
• Reliably trace user collaboration and participation in co-creation processes
• Enabling the development of novel business models based on the collaboration
and partnership of government and its stakeholders
35. 35
Internet de las cosas y datos de ciencia
ciudadana para uso público
La Transformación digital: Aspectos a considerar en el
futuro Plan Estadístico y Cartográfico de Andalucía 2021-2027
Sesión II: Territorios inteligentes e inteligencia artificial
18 de Noviembre 2020, 18 de noviembre, 9:30-9:50
Dr. Diego López-de-Ipiña González-de-Artaza
dipina@deusto.es
http://paginaspersonales.deusto.es/dipina
http://www.morelab.deusto.es
@dipina