FIWARE Wednesday Webinars - Cities as Enablers of the Data Economy: Smart Data Models for Cities
0 likes428 views
The document discusses the role of cities as data ecosystems to enhance economic welfare, emphasizing the importance of standardization for technology adoption. It presents the Smart Data Models initiative aimed at creating open and interoperable data models, promoting collaboration among contributors, and facilitating the development of smart applications. Key aspects include the use of digital twins, standard APIs for data access, and a community-driven approach to managing data models across various sectors.
FIWARE Wednesday Webinars - Cities as Enablers of the Data Economy: Smart Data Models for Cities
- 1. Cities as Enablers of the Data Economy: Smart Data Models for Cities 21-10-20 Alberto Abella Data modelling expert FIWARE Foundation
- 2. Introduction 1 Alberto Abella Data modelling expert FIWARE foundation
- 3. Learning goals ▪ Assuming the economic relevance of the cities and how to develop this ecosystem for producing welfare for the citizens ▪ Understanding the need for standardization as the base for reducing costs for technology adoption ▪ The Smart Data Models initiative and how it will help you on your projects ▪ Understanding how to use smart data models and how to contribute to them 2 ● Citizen as consumer ● Citizen as user ● Citizen as creator ● Citizen as designer
- 4. Index 1. The city as a data ecosystem for creating economic impact. 2. Context / Digital Twin Data Management in FIWARE. 3. Relevance of standardization. New approach. Open principle. 4. The Smart data Models Initiative. Structure. 5. The Smart data Models Initiative. Examples. 6. The Smart data Models Initiative. Users and contributors. 3
- 5. 1. The city as a data ecosystem for creating economic impact. 4
- 6. 5 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 SMART CITIES
- 7. Digital Ecosystem 6 Smart city Digital Ecosystem. Source: Based on Abella, Ortiz-de-Urbina & De-Pablos (2015)
- 8. Economic impact of data economy 7 Size of the Smart cities market Billions (pre Covid-19) Avg yearly growth: 20% Source: Mckinsey 2016
- 9. 2. Context / Digital Twin Data Management in FIWARE. 8
- 10. What are we referring to as Digital Twin? ▪ Digital Twin = Digital representation of an asset • Characterized by attributes □ Properties □ Relationships Linked Data • Values of attributes may change over time (or not) • Typically have a location (but it is not a must requirement) ▪ (digital representation of) Context = Digital Twins Collection ▪ Basis for the development of any Smart Solution: • Standard API for getting access to Digital Twin data (context) • Common Data Models associated to Digital Twin classes 9
- 11. Modeling Context using Digital Twins for Cities … 10 Entities (Digital Twins) Bus • Location • # passengers • Driver • License plate Citizen • Birthday • Preferences • Location • ToDo list Incident / claim • Date • Location • Type • Issuer • Description Shop • Location • Business name • Franchise • offerings Attribute Process / Analyze / Monitor Digital Twin representation Context (Real World) capture actuate update notify / query
- 12. Integration at multiple levels 11 Digital Twin representation Digital Twin representation Digital Twin representation Architecting Smart Solutions Integrating systems and data within organizations (system of systems) Sharing Data across organizations 3rd systems sensors Smart Solution System 3 System 4 System 1 System 2 Smart City Smart Building Smart Logistics Smart Grid
- 13. NGSI: a standard API for accessing Context / Digital Twin data 12 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
- 14. 3. Relevance of standardization. New approach. Open principle. 13
- 15. NGSI API: Endorsement at global level 14 TM Forum supports FIWARE NGSI for real-time access to context information in cities TM Forum and FIWARE collaborate in development of data marketplace platform components TM Forum and FIWARE also collaborate in definition of common smart data models in collaboration with cities ETSI created Jan 2017 an Industry Specification Group (ISG CIM) for defining a Context Information Management API FIWARE NGSIv2 provided the basis for the NGSI-LD specs published by ETSI FIWARE provides several open source implementations of ETSI NGSI-LD The FIWARE Context Broker Technology has been selected as a new CEF (Connecting Europe Facility) Building Block recommended to public and private sector for publication of right-time context data The European Data portal will support the publication of right-time Open Data The GSMA has published a Reference Architecture for IoT Big Data Ecosystem which recommends to mobile operators NGSI-LD plays the core role in the defined Reference Architecture
- 16. Approach to data models. ‘De facto’ standardization. 15 Concept Classic De-facto Standardization body Stable and fully-dedicated entity → DIN Unstable or not fully dedicated → Fiware foundation Standardization groups Extended and Balanced members from relevant and interested actors Interested users and developers with expertise on the field Consensus mechanisms Global Reviews by participants By contribution and Benevolent dictator Prestige of standards By source entity By use of the results Advantages Low-biased standards. Coherence with former standardizations Predictable reviews Funding based on standard costs and members fees Standard created together with implementation Evolution by use Quick reviews Low cost Disadvantages Creation of theoretical standards (never implemented) Slow reviews Standardization hardly support costs Potential biased standards Low barriers to Potential competitors
- 17. 4. The Smart Data Models Initiative. Structure. 16
- 18. And what will happen to the data models you use when …. Scenario: Imagine you have to create data models for the development o integration of a service / application What will happen to the data models you use when ▪ … your project ends. ▪ … you have to update it. ▪ … you were asked to make it interoperable with other/new initiatives? ▪ … you need to update it to new regulations / standards? Wouldn’t be more efficient and useful to do it together? 17
- 19. ▪ 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 ▪ To provide extended usefulness to FIWARE platform users in terms of: − Extended interoperability − Reduced time dedicated to data model codying − Accumulated experience tested in real case scenarios − Mapped to be integrated with other platforms ▪ Using open licensing to allow extensive use and adoption ▪ Used in real case scenarios (and based on real use cases) ▪ Based on git platform and github as development frontend ▪ Consensus as main decision method ▪ Based on widely adopted standards (including ontologies and international schemas, i.e. schema.org) Principles of Smart data models initiative 18
- 20. GITHUB http://github.com/smart-data-models - Oriented to developers - All resources available - Contribution by PR - Issues on data models SITE (Wordpress) http://smartdatamodels.org - Oriented to end users - News on updates (subscription) - Check attributes and enumerations Structure: Webs 19
- 21. data-models Umbrella repo Cross Sector Smart Manufacturing Subject NSubject 1 Smart Water Smart Robotics Smart Agrifood Smart Cities Smart Environment Smart Destinations Smart Sensoring Subject 2 Subject 3 Subject 4 DOMAINS REPOSITORIES Readme pointing to the list of subjects General info or shared resources DATA-MODELS - Guides for coding new data models - Template for new data models and examples - Directory for scripting tools to check data models - Inventory of domains and data models - Inventory of attributes and terms - @Context for json-ld SUBJECTS’ REPOSITORIES Readme pointing to the list of data models for the objects Contributors.md subject-schema.json DATA MODELS README.md /doc/spec.md /examples schema.json Current Adopters Structure: domains and subjects compile data models 20
- 22. - Global data about the initiative ○ List of data models ○ List of attributes ○ Required attributes - Domains’ repositories - Updated daily to the last commit of Subjects - Free contribution repo - Under request Domain repositories and others. http://github.com/smart-data-models/specs Structure: Github. Domains 21
- 23. - Subjects as submodules of the Domain - Updated daily to last commit - Data models in the subject Domain repositories and others. https://github.com/smart-data-models/SmartCities - Shared elements for all the Data models in the subject Structure: Github. Domains 22
- 24. - Agreement for release data models with open license - Contact options - Presentation on the governance of the initiative - Tools & links for learning about data modelling - Manual submission of data model (with help) - Newslists on different Domains - News updates on the data models - Document for future contributors to data models - List of data models - Attributes database - Coding instructions Frontpage. https://smartdatamodels.org Structure: WP 23
- 25. Subscriptions: http://smartdatamodels.org/index.php/subscriptions-page/ Frontpage 1 list per domain 1 mail a week (unless very important changes) Structure: WP 24 News: https://smartdatamodels.org/index.php/news/
- 26. 5. The Smart data Models Initiative. Examples. 25
- 28. 27 Example 1. Look for an attribute for your data model 1. Look for a parameter into the attributes database (i.e. light) 2. Explore the different data models related 3. Review the specification
- 29. Attributes and enumerations database ▪ Front page of https://smartdatamodels.org ▪ Searchable in > 3000 terms ▪ Across all data model ▪ Immediate answer and link to the schema 28
- 30. 29 Example 2. Creating an entity on NGSI and other systems 1. Browse github till retrieve GTFS trip payload (json) 2. Open editor to run the queries into a NGSI engine 3. Get example csv (raw) 4. Convert into SQL 5. Create a SQL database into a DB editor By -stk - Own work, CC0, https://commons.wikimedia.org/w/index.php?curid=47287176 sudo docker pull mongo:3.6 sudo docker pull fiware/orion sudo docker network create fiware_default sudo docker run -d --name=mongo-db --network=fiware_default --expose=27017 mongo:3.6 --bind_ip_all --smallfiles sudo docker run -d --name fiware-orion -h orion --network=fiware_default -p 1026:1026 fiware/orion -dbhost mongo-db
- 31. 30 Example 3. Using example payloads of a data model 1. Just use this link (Weather observation) 2. Or this one (Device) 3. Proof of Concept to be extended
- 32. 6. The Smart data Models Initiative. Users and contributors. 31
- 33. 32 Licensing Data Models 1. Preferred: Creative Commons 4.0 2. Apache 2.0 or other open licenses could be approved as long as they: a. Recognise contributions b. Allow free reuse of the data models c. Do not impose other restrictions to use and adoption 3. Contributors has to fill a form to provide rights to the initiative for releasing with those licenses (not losing their IPR)
- 34. 33 Management of contributions CONTRIBUTORS ● Anybody can contribute as long as he/she meets guidelines (for checking automation) ● Participation can be as individual or representing an organization ● Contributors are explicitly recognised and vote relevant changes and contributions ● Contribution has to be based on real use of the data model ● Contribution manual explains: a. Options for contribution (PR, issue, form) b. Link to the guidelines for contribution c. Documents needed for a complete data model (reduction coming)
- 35. 34 Roadmap
- 36. 1. Dramatic increase in the # of data models (See incubated repo) − Adaptation of existing standards (Cities, Agrifood, Manufacturing, Energy, Water, Robotics, Smart Destinations, etc) 2. Engagement of additional relevant organizations and bodies 3. Automation tools for reducing the workload for contributors − Automatic creation of examples − Generation of payloads − Help on data model generation and testing 4. Survey to users to get actual needs 5. Growth the community relying on the decentralized governance Roadmap 35
- 37. Q & A 36
- 38. Thank you! http://fiware.org Follow @FIWARE on Twitter contact: [email protected]