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FIWARE and Smart Data Models
Fernando López
FIWARE Cloud & Platform Senior Expert
fernando.lopez@fiware.org
@flopezaguilar
https://www.slideshare.net/flopezaguilar
https://github.com/flopezag
2
FIWARE was created to ease solutions supporting the Smart Digital Life
building around open standards for managing Context / Digital Twin Data
that blurs the frontiers among application domains and enable the Data Economy
Smar
t
Wate
r
FIWARE provides the basis for development of smart
solutions in multiple sectors
Smart Solutions “powered by FIWARE” gather
data from many different sources to build a
“digital twin representation” of the real world
(also referred as “context representation”)
which is constantly analysed and processed in
order to automate processes or bring support
to smart decisions
3
Process / Analyze
/ Monitor
Digital Twin
representation
Context
(Real World)
update actuation
update
notify /
query
FIWARE: Supporting a system of systems architecture
▪ Need to integrate data to build a holistic picture of what
is going on in right-time (context data).
▪ Smart management systems can be developed at
overall organization-level on top of this context data.
▪ A Reference Architecture for such organizations will
look like a “System of Systems”.
▪ Key properties in “System of Systems” architectures:
• Replaceability (systems can be replaced)
• Extensibility (new systems can be added easily)
• Loose coupling (systems can evolve independently)
• Low intrusiveness (systems do not need to change)
4
FIWARE driving key standards: Digital Twin Data API
5
Process / Analyze
/ Monitor
Digital Twin
representation
Context
(Real World)
capture actuate
update
notify /
query
Application/Service
FIWARE NGSI API
(NGSIv2 - NGSI-LD)
Bus
• Location
• No. passengers
• Driver
• Licence plate
Citizen
• Name-Surname
• Birthday
• Preferences
• Location
• ToDo list
Shop
• Location
• Business name
• Franchise
• offerings
Context Broker
FIWARE driving key standards: Digital Twin Data API
6
KeyrockIdM&WilmaAccessControl
APIManagement
IoT platformsKurento RT
media stream
processing
IDAS NGSI Agent Framework
System
Adapter …IoT
Agent
FIWARE Context Broker
Bus
• location
• route
• next stop
• time next stop
Street
• location
• traffic
• pollution
Parking space
• location
• no. slots
Shared car
• location
• status
Citizen claim
• location
• citizen id
• description
Waste Bin
• location
• capacity
Other information sources
…Social
netwoks
CRM
Deployed IoT networks,
machines, cameras, robots
High-level
Context
Updates
Processing Engines
(Flink, Spark, Tensorflow, Hadoop, …)
Smart City Governance System
Operation
Dashboards
Advanced
Data Maps
AI AlgorithmsBig Data
Algorithms
Complex Event
Processing
Cygnus / Draco / Cosmos / STH Comet /
QuantumLeap
History Data
Stream
Vertical solutions
Waste
Mgmt..
Smart
Parking
Air
Quality …Traffic
control
GIS
Wirecloud
Mashup
Apache
Superset
System
Adapter
System
Adapter
System
Adapter
Extended Data Publication Platform
(e.g., CKAN)
Open Data Portal
(supporting
right-time datasets)
Why smart data models?
▪ Standardization allows dramatic reductions of costs and
remarkable increases in efficiency if some conditions are met:
a) Shared transmission / interface protocols → ETSI NGSI-LD
b) Payloads share semantic and format standards
7
What are the Smart Data Models?
▪ What is it: A community site with
detailed data models
▪ Available at: github.com/smart-data-models
and a front page for users at
smartdatamodels.org
▪ Data models come from existing
regulations, actual uses cases, projects,
and voluntary contributions.
8
Smart Data Models’ goal
▪ Easy contribution. One single file instead
of two. Enabling self checking.
▪ Easy use and adoption. Enabling
multilanguage specifications.
▪ Efficient approach. Automation reduces
the burden on manual review.
▪ Scalable. Automation enables growth.
By Pieter Brueghel the Elder - bAGKOdJfvfAhYQ at Google Cultural Institute,
zoom level maximum, Public Domain,
https://commons.wikimedia.org/w/index.php?curid=22178101
9
Principles of Smart Data Models initiative
▪ A community site with detailed data models available
for open use for multiple sectors.
▪ Together with other relevant organizations in the
curation of the different domains and subjects.
▪ Providing coherence and consistency between data
models across different domains.
▪ To create a method for AGILE standardization and
evolution these data models.
▪ Using open license (CC4.0) to allow extensive use
and adoption.
10
Principles of Smart Data Models initiative
▪ Based on widely adopted standards (e.g. ontologies
and international schemas, schema.org).
▪ To provide extended usefulness to FIWARE platform
users in terms of:
• Extended interoperability
• Reduced time dedicated to data model coding
• Accumulated experience tested in serious games
• Mapped to be integrated with other platforms
▪ Based on git and GitHub platform.
▪ Consensus as main decision method.
11
Who leads the initiative?
▪ Technical Steering Board currently composed by FIWARE Foundation, TMForum
and IUDX.
▪ Each domain teams with the relevant organizations and beyond.
▪ It is possible to join.
12
Added value for users
▪ SDM provides examples, specifications and validation tools for each data model
free to use.
▪ Checks coherence and consistency across data models.
▪ SDM takes care about providing updates at market speed.
▪ SDM data models use open license. Possible to adapt and integrate with other
tools and systems.
13
Services to users and contributors
▪ DB of attributes and enumerations.
▪ DB of attributes’ descriptions.
▪ Subscription to news (per domain).
▪ Support to issues.
▪ Submit data models.
▪ Training.
▪ Contribution manual.
▪ Contribution agreement.
▪ Example 1. Looking for attributes
for a new data model
▪ Example 2. Integration of data
model with other system.
▪ Licensing of data models.
▪ How to contribute .
▪ Governance .
▪ Roadmap.
14
Smart Data Models: Next steps
15
▪ Engage additional organizations in the Smart Data Models
initiative (same as IUDX). Some candidates:
• GS1
• MaaS Alliance
• ...
▪ Continue population of Data Models through engagement of
contributors. Some currently:
• Smart Energy
• Smart Water
• Smart Building
• Smart Destinations
▪ More user-friendly website (https://smartdatamodels.org)
▪ Reference under https://schema.org
▪ Promotion campaign
• Smart Manufacturing (Robotics)
• Smart Ports / Airports
Thank you!
http://fiware.org
Follow @FIWARE on Twitter

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FIWARE and Smart Data Models

  • 1. FIWARE and Smart Data Models Fernando López FIWARE Cloud & Platform Senior Expert fernando.lopez@fiware.org @flopezaguilar https://www.slideshare.net/flopezaguilar https://github.com/flopezag
  • 2. 2 FIWARE was created to ease solutions supporting the Smart Digital Life building around open standards for managing Context / Digital Twin Data that blurs the frontiers among application domains and enable the Data Economy Smar t Wate r
  • 3. FIWARE provides the basis for development of smart solutions in multiple sectors Smart Solutions “powered by FIWARE” gather data from many different sources to build a “digital twin representation” of the real world (also referred as “context representation”) which is constantly analysed and processed in order to automate processes or bring support to smart decisions 3 Process / Analyze / Monitor Digital Twin representation Context (Real World) update actuation update notify / query
  • 4. FIWARE: Supporting a system of systems architecture ▪ Need to integrate data to build a holistic picture of what is going on in right-time (context data). ▪ Smart management systems can be developed at overall organization-level on top of this context data. ▪ A Reference Architecture for such organizations will look like a “System of Systems”. ▪ Key properties in “System of Systems” architectures: • Replaceability (systems can be replaced) • Extensibility (new systems can be added easily) • Loose coupling (systems can evolve independently) • Low intrusiveness (systems do not need to change) 4
  • 5. FIWARE driving key standards: Digital Twin Data API 5 Process / Analyze / Monitor Digital Twin representation Context (Real World) capture actuate update notify / query Application/Service FIWARE NGSI API (NGSIv2 - NGSI-LD) Bus • Location • No. passengers • Driver • Licence plate Citizen • Name-Surname • Birthday • Preferences • Location • ToDo list Shop • Location • Business name • Franchise • offerings Context Broker
  • 6. FIWARE driving key standards: Digital Twin Data API 6 KeyrockIdM&WilmaAccessControl APIManagement IoT platformsKurento RT media stream processing IDAS NGSI Agent Framework System Adapter …IoT Agent FIWARE Context Broker Bus • location • route • next stop • time next stop Street • location • traffic • pollution Parking space • location • no. slots Shared car • location • status Citizen claim • location • citizen id • description Waste Bin • location • capacity Other information sources …Social netwoks CRM Deployed IoT networks, machines, cameras, robots High-level Context Updates Processing Engines (Flink, Spark, Tensorflow, Hadoop, …) Smart City Governance System Operation Dashboards Advanced Data Maps AI AlgorithmsBig Data Algorithms Complex Event Processing Cygnus / Draco / Cosmos / STH Comet / QuantumLeap History Data Stream Vertical solutions Waste Mgmt.. Smart Parking Air Quality …Traffic control GIS Wirecloud Mashup Apache Superset System Adapter System Adapter System Adapter Extended Data Publication Platform (e.g., CKAN) Open Data Portal (supporting right-time datasets)
  • 7. Why smart data models? ▪ Standardization allows dramatic reductions of costs and remarkable increases in efficiency if some conditions are met: a) Shared transmission / interface protocols → ETSI NGSI-LD b) Payloads share semantic and format standards 7
  • 8. What are the Smart Data Models? ▪ What is it: A community site with detailed data models ▪ Available at: github.com/smart-data-models and a front page for users at smartdatamodels.org ▪ Data models come from existing regulations, actual uses cases, projects, and voluntary contributions. 8
  • 9. Smart Data Models’ goal ▪ Easy contribution. One single file instead of two. Enabling self checking. ▪ Easy use and adoption. Enabling multilanguage specifications. ▪ Efficient approach. Automation reduces the burden on manual review. ▪ Scalable. Automation enables growth. By Pieter Brueghel the Elder - bAGKOdJfvfAhYQ at Google Cultural Institute, zoom level maximum, Public Domain, https://commons.wikimedia.org/w/index.php?curid=22178101 9
  • 10. Principles of Smart Data Models initiative ▪ A community site with detailed data models available for open use for multiple sectors. ▪ Together with other relevant organizations in the curation of the different domains and subjects. ▪ Providing coherence and consistency between data models across different domains. ▪ To create a method for AGILE standardization and evolution these data models. ▪ Using open license (CC4.0) to allow extensive use and adoption. 10
  • 11. Principles of Smart Data Models initiative ▪ Based on widely adopted standards (e.g. ontologies and international schemas, schema.org). ▪ To provide extended usefulness to FIWARE platform users in terms of: • Extended interoperability • Reduced time dedicated to data model coding • Accumulated experience tested in serious games • Mapped to be integrated with other platforms ▪ Based on git and GitHub platform. ▪ Consensus as main decision method. 11
  • 12. Who leads the initiative? ▪ Technical Steering Board currently composed by FIWARE Foundation, TMForum and IUDX. ▪ Each domain teams with the relevant organizations and beyond. ▪ It is possible to join. 12
  • 13. Added value for users ▪ SDM provides examples, specifications and validation tools for each data model free to use. ▪ Checks coherence and consistency across data models. ▪ SDM takes care about providing updates at market speed. ▪ SDM data models use open license. Possible to adapt and integrate with other tools and systems. 13
  • 14. Services to users and contributors ▪ DB of attributes and enumerations. ▪ DB of attributes’ descriptions. ▪ Subscription to news (per domain). ▪ Support to issues. ▪ Submit data models. ▪ Training. ▪ Contribution manual. ▪ Contribution agreement. ▪ Example 1. Looking for attributes for a new data model ▪ Example 2. Integration of data model with other system. ▪ Licensing of data models. ▪ How to contribute . ▪ Governance . ▪ Roadmap. 14
  • 15. Smart Data Models: Next steps 15 ▪ Engage additional organizations in the Smart Data Models initiative (same as IUDX). Some candidates: • GS1 • MaaS Alliance • ... ▪ Continue population of Data Models through engagement of contributors. Some currently: • Smart Energy • Smart Water • Smart Building • Smart Destinations ▪ More user-friendly website (https://smartdatamodels.org) ▪ Reference under https://schema.org ▪ Promotion campaign • Smart Manufacturing (Robotics) • Smart Ports / Airports