In the Smart Cities Preliminary Report 2014 published by ISO/IEC JTC1, they have emphasized the importance of standardized, computer-recognizable, and actionable open data produced by various city resources. International standardization working groups such as ISO/IEC JTC1, JTC1/SC31 have been establishing new standards and also adopting existing standards for object identification, data modeling, and data acquisition which are the key features of the smart-city data platform.
ISO/IEC data standards have adopted many existing GS1 (Global Standards One) standards. GS1 is an international non-profit organization with 112 member organizations worldwide and more than two million user companies over 40 years. They develop global standards of how to identify, capture, share and use the data of real-world objects in business communication. The best-known standard is the barcode in retails, and they are expanding their area to healthcare, transport and logistics, food service, technical industries, and smart cities.
In this tutorial, we will give the introduction of GS1, and present the GS1’s standardization efforts with use case examples. Topics are as follows; 1) Identification and classification, 2) Semantic vocabulary, 3) Modeling and sharing of city resource metadata, 4) Master data, transaction, and event data modeling, 5) Data sharing system (API, distributed repository), 6) Smart data browsing, 7) Service registration, discovery, and access, 8) Traceability and block chain adoption, 9) Web vocabulary for city data, and 10) Oliot open source project.
Lastly, we would like to introduce Urban Technology Alliance (UTA) that aims to bring a complete smart city ecosystem, concerning various stakeholders such as city and government, industry, academia, non-profit organizations, and the most important, citizen.
Tutorial: Standardization Efforts for Smart Cities - GS1/ISO/IEC Standards At-a-Glance: Identify, Capture, Share, and Use
1. Tutorial: Standardization Efforts for Smart Cities
GS1/ISO/IEC Standards At-a-Glance:
Identify, Capture, Share, and Use
Daeyoung Kim
September 16, 2018
Professor, School of Computing, KAIST
Director, Auto-ID Labs, KAIST
• kimd@kaist.ac.kr, http://oliot.org, http://autoidlab.kaist.ac.kr, http://resl.kaist.ac.kr, http://autoidlabs.org, http://gs1.org
2. https://news.joins.com/article/22942850
Kauffman Stadium:
GLN (Global Location Number)
American Royal Rodeo Show:
GTIN (Global Trade Item Number)
National WW1 Museum:
GLN (Global Location Number)
Kansas City Scout Statue:
GLN & GIAI
The Nelson-Atkins Museum’s Arts:
GIAI (Global Individual Asset Identifier)
World of Fun’s Discount Ticket:
GCN (Global Coupon Number)
B-Bike in KC:
GRAI (Global Returnable
Asset Identifier)
Souvenir of Museum
GTIN (Global Trade
Item Number)
7. Manufacturing Data
(Parts, Factory,
Manufacturing date)
Korea, Busan Bus Spain, Santander Bus
Registration/
Inspection Data
(VIN, Plate Number,
Reg. Number, Owner,
Inspection Data)
Sensor Data
(Location, Speed,
RPM)
Accident Record
Data
(Date, Location,
Damages)
Arrival
Estimation
Service
Traceability
Service
Recall
Service
Nearby
School
Service
Advertise-
ment
Service
8. Seoul
Busan
InIn Korea, 50 number of Bus Line #100, Three bus stops of ID 43030
Local and non-standard Identification System, API, and Data format/contents
1. Data Sharing
(Data Hub)
9. QR code carries a single service
Through URL
Needs Scalability
2. Service Sharing
(Service Hub)