National Data Strategy and initiatives in Japan 2023-02-06 Kenji Hiramoto, Head of Data Strategy, Executive officer Government of Japan

Overview of the Digital agency 2 Minister of Digital agency Chief officer of Digital agency Vice minister for Digital policy Strategy and planning group Strategy Management Technology & platform group CoE Service group (G2B,G2C) Dev. and Op. Service group (In G&LG) Dev. and Op. Head of Domain （International strategy, Data strategy, Solution, Cloud, Resource management, Education, Health） Adviser CXO (Architect, Technology, Product, Information Security) Data Digital agency • Digital strategy • Rules • Government-wide services • Platform • Technology standards • Service coordination • Advice & Training Other ministries IPA IT Promotion Agency DSA Data Society Alliance

Vision & Strategy for Digital society 3 Other Acts Privacy act and Info. disclosure act Society 5.0 (2016) Economic Growth Strategy (2022-6) Innovation Strategy (2022-6) Digital Strategy (2022-6) Data Strategy (2021-6) Digital Government Action Plan (2020-12) • Digital first • Once only • One stop Vision National Strategies Digital Strategies Data Act (2016) Digital-First Act (2019) Society 5.0 Reference Architecture Data Exchange Platform Government Interoperability Framework (GIF) Data Strategy / Policy Rule Organization Business Data harness functions Data Data broker function Asset Sensor, Actuator, Hardware, Network Gathering, Integration, Cleansing, Device management Data definition, Data model, Code Catalogue, Search, AI, Analysis Business process Business Rule Coordination Team Legislation Regulation Vision Priority domain Security / Authentication Lifecycle AI Principal (2019-3) AI Strategy (2022-6) AI Strategy Digital society Act (2021)

Digital Strategy 4 Vision for the Digital Society Citizens can choose services that satisfy his/her demands and achieve well-being through digital technology Principles 1. Open / Transparent 2. Fairness / Ethics 3. Safety / Secure 4. Continuation/Stable/Resilient 5. Solving social issues 6. Quick / Flexible 7. Inclusion / Diversity 8. Immersion 9. Creating new value 10.Leap/International contribution Digital Garden City Economic ecosystem Local economy and community No one will be left behind Data spaces Skills for digital society International cooperation Emerging Technologies National data strategy Deregulation for digital society Priority area Initiatives

5 National Data Strategy

• Data is competitive resource in the digital society. • Government is the largest data holder and consumer in the country. So we should lead the data-eco-cycle. The role of government in digital society 6 Public sectors Provide data Gather data Society Standard Cleansing High quality data

• We published the national data strategy on June 18, 2021.We will realize a citizen-centric society by 2030. • Vision －We aim to realize a sustainable human society. It is the human-centric society that creates new value by achieving both economic development and solving social issues. It is achieved through a digital twin by using data. －It is consistent with the vision of Society 5.0 that is the future vision of Japan. －Our society values trust and safety. It is essential to realize high efficiency and hospitality services at the same time. The National data strategy

• Anyone get data easily, start business quickly and use high-quality services. Vision for 2030 citizen-centric society High value data sets Statistics Realtime sensor data Base registries • Person • Legal entities • Land • Administration data • Traffic • Weather Digital Twin Service providers keep their services, sustainably. Trust & Safety Once only services Citizen can use various services Open data Data from private sectors Platform Anyone get data easily Reduce the duplicate cost Reduce city maintenance cost 8

Principles 9 Use anytime, anywhere • Availability • Quickness • Cross-boarder Connect • Interoperability • Efficiency Control your data yourself • controllability • Privacy Safe • Security • Trust • Quality Create together • Co-creation • Creation of new value Evidence Based administration •Identify the priority data •EBPM •Business transformation •Data management and open data •Cultural change Data ecosystem •Data engineering for data ecosystems •Data standards •Data quality management •List of data asset in the administrations Maximize the value of data •Rule management for data access •Chanel management for the various data accesses •Open data Principle of Data strategy Principle of ministry’s action

Trust （DFFT） Architecture of our strategy Data Data Service Platform Service Platform Rule Rule Security / Privacy Security / Privacy Services for citizens and businesses Services for citizens and businesses Organization and human resource Organization and human resource Infrastructure, Asset Infrastructure, Asset Tools Tools Maximizing the Value of services Base registries Base registries Internal data Internal data Statistics Statistics Open data Open data

• To make it a sustainable initiative, it is important to build on the foundation. The steps for realizing the data-driven Society 11 Findable • Data catalogue • Service catalogue • Platform Usable • Structured data model • Quality management Processable • Machine readable Automatable • Auto-check • RPA（Robotic Process Automation） Analyzable • AI • Big data analysis We are here. Trust

• GIF has just completed the basic part and will be enhanced. • In 2022, ｗe will enhance the content through implementation in smart cities and government systems. Roadmap 12 2022.3 2023.3 2025 2030 Enterprise and area services Cross-Industry services AI-driven services Digital twins Phase of implementation and verification by organization or service unit Phase to fix the foundation, as framework. Phase of connecting data across business fields and areas Phase to fully utilize AI and Digital twin Society5.0 Mechanisms will be developed and verified. Data will be enhanced. Government Interoperability framework（GIF) Activities A sustainable society through Trust and Quality

Government Interoperability Framework

• GIF is essential infrastructure for data-driven society. • All services, including AI and mobility services, will be based on this infrastructure. Role of GIF 14 Reduction of design cost and time Ease of integration and scalability Improvement of user experience GIF Lower design and operating costs and time because it utilizes a reference model Utilizes a reference model, making it easier to collaborate with other organizations and leverage existing applications Improve the convenience of services by redirecting the design effort to service enhancement one. (Once-Only services)

Data models Code Character Data（Japanese/English） Core data parts(Basic data items） Core vocabulary（Data dictionary） Numeric data（Sensing data, Image data） Core data models（Basic data models for Service one） Service Data models［DM］ Base registry DM Metadata model Smart city DM Disaster risk mgt. DM Education DM Government DM ・・・ • We have developed our product around a data model. • Next step, we will continuously add data models, tools, and guidebooks. Overview of GIF products 15 List of rules Guidebooks Platform services and tools(Catalogue, Data dictionary, Connecting Facilities) National Data Strategy

• Stakeholders • Transactions • Certification Trust Trust • DATA-EX • Catalogue Platform Platform • Base registries • Open data • Data engineering Data Data • Smart cities • Once-only Showcase Showcase Priority Actions in the architecture 16 Citizens use and store data with confidence Citizens efficiently use data Citizens can use various data Citizens understand the value of data

17 GIF priority action: Trust

Economic Mechanism Trust Interoperability Framework Engine for the Data Flow 18 Motivation (Win-Win) GIF (Government Interoperability Framework) - Rule - Tool - Data • To enhance the economy, it is important to have a foundation to interoperability and a foundation for trust. Transparency Fairness Accountability

The trust for the smart society 19 Rules for trust • Privacy, security and Intellectual property issue. (Need to coordinate rules among service areas) Trust of Stakeholders • Transparency and confidence of stakeholder. (Need to check the sustainability of the stakeholders) Platform for trust • Transparency of platformer.(Needs to know the policy, management and technologies) Trust of Information • Transparency of society. Dis-、Mis-Information. (Need to check information) Data for trust • Accuracy, currency, and comprehensiveness of data.(Need to manage the quality of data) Technologies for Trust • Originality and non-tampering. (Need to use security technologies) • DFFT(Data Flee Flow with Trust) is a basic concept for the data-driven society.

• We need the architecture of trust for the smart societies. Trust in the smart societies and the data space 20 Area Level Trust Smart Society Area Level Trust National Level Trust Area Level Trust Area Level Trust National Level Trust Area Level Trust Area Level Trust National Level Trust Universal Level Trust （Data space） Limited participation Level Trust Rules for trust Trust of Stakeholders Platform for trust Trust of Information Data for trust Technologies for Trust

• Government provides some services to make trust in the smart cities. Our actions for trust 21 Rules for trust Trust of Stakeholders Platform for trust Trust of Information Data for trust Technologies for Trust Trustful source (Government data, Base registries) Common building blocks(Broker, Connector) Data quality framework (include provenance info.) Government Interoperability Framework(GIF) Certified technologies guidance Terms and Conditions for data Legal entities base registry (gBizInfo) We can use data with trustful partners through trustful environments (Rules, Platforms, Technologies).

22 GIF priority action: Platform & Services

Data Exchange Platform(DATA-EX) • Each function is modularized as a Building Blocks and are connected by API. Services Function for data management Function for connection Search Distribution Privacy Community Catalogue Taxonomy Simulation Quality Assurance Convert Merge Integrate Anonymize Cross-domain data exchange platform Data exchange platforms for each industries Rule Services for each industries • Taxonomies • Codes • Functions Other contries Services Function for data management Function for connection Search Distribution Privacy Community Catalogue Taxonomy Simulation Quality Assurance Convert Merge Integrate Anonymize 23

• We provide an open data portal site. • We will launch new open data site on the end of March. Data catalogue 24

• We will define services as data spaces. We are working to standardize the data and building blocks of our existing services. Data spaces 25 GIF Education Smart city Disaster risk managem ent Health Infrastruct ure Mobility Manufactu ring Building Blocks

26 GIF priority action: Data

• Data is fuel for the digital society. Projects in the data layer 27 Open data initiative Base registries Data catalogue / Data dictionary Government Interoperability Framework (Data quality, Data management) Government Interoperability Framework (Data model, Platform) Requirement Projects Quantity of Data Diversity of Data Quality of Data Findability Usability

Administrations • Base registries are databases of basic social data on people, corporations, land, buildings, qualifications, etc., which is registered and disclosed by public organizations and referred to in various situations. In Japan, ledgers are often the equivalent. • It is the foundation for all social activities and an essential environment in a digital society. Base registries Land Building Infrastru cture Legal entity Base registries Person Transpor tation Public facility Event Public services License Society GIF(Government Interoperability Framework)

Address Base registry • Block level(Not include Land ID) Corporation Information Base registry • Registered information • Name of corporation, Address of the headquarter • Financial information, Business locations and Certifications Public service Base registry • Information of grants, consulting services, Projects of Base Registries initiative 29

• Open is essential concept for the data strategy. Open data initiative 30 Open data Training course Good practices Advisors Data models for open data Data catalogue / Data dictionary Term and condition for open data GIF DCAT-GOJ Platform Base registries Tools Citizen or Servicer Rule for data sharing Standard Data Environment Rule Support

Data Code Character Data（Japanese/English） Core data parts Core vocabulary Numeric data（Sensing data, Image data） Core data models Service data model［DM］ Base registry DM Date & Time Address Postal code Geo coding Phone POI code Point of contact Nursing info. Accessibility Person Legal entity Facility Equipment Metadata Admen. G. Land G. Legal entity G. Smart city DM (Local service) Moving object Feature Map Disaster rm, DM Support activity Status report Shelter and evacuation site Education DM Contents Student ＆ Stakeholders School Government DM Use case Evidence and Information Application Service catalogue Report and material Event Service and program Service delivery point Activity Address BR Support program BR Business location BR Legal entity BR List of school List of evacuation site List of shelter List of hospital Event BR Public Facility BR List of code Activity Afflicted people ・・・ Others • We should provide structured and high-quality date. GIF data models 31 Acquisition Guidebooks GIF Guidebook Character data guidebook Master data design guidebook Code design guidebook API guidebook Data management guidebook Data specialist guidebook Architecture guidebook Data quality guidebook Metadata guidebook Land Building Event Combine blocks to build a data model

Guidebooks GIF Guidebook Character data guidebook Master data design guidebook Code design guidebook API guidebook Data management guidebook Data specialist guidebook Architecture guidebook Data quality guidebook Metadata guidebook • Service data models are created by derivation of a common model. So, data linkage is easy even across fields. Case 32 Core data models Building Data Code Character Data（Japanese/English） Core data parts Core vocabulary Numeric data（Sensing data, Image data） Service data model［DM］ Base registry DM Date & Time Address Postal code Geo coding Phone POI code Point of contact Nursing info. Accessibility Legal entity Land Facility Equipment Metadata Administration related data Land related data Legal entity related data Smart city DM Moving object Feature Map Disaster Risk Management DM Support activity Status report Shelter and evacuation site Education DM Contents Student ＆ Stakeholders School Government DM Use case Evidence and Information Application Service catalogue Report and material Event Service and program Service delivery point Activity Address BR Public service BR Business location BR Legal entity BR List of school List of evacuation site List of shelter List of hospital Event BR Public Facility BR List of code Activity Afflicted people ・・・ Others Acquisition Person Event BR： Base registry

• IMI2 is not standards but reference models. Anyone can enhance or make subset them for their implementation. How to use the data models 33 Before IMI IMI2 Service data model Title Implementation Subset Enhance Title Title Title Title

• ID －My number(Personal ID number) －Corporate Number －Real property ID －Address block ID • Code －Point of Interest code －Codes in the statistics • Controlled vocabularies －GIF date models defines codes. ID, Code and controlled vocabularies 34

• Conversion tools support for legacy systems and data. Data conversion 35 Legacy systems and data １man ２woman ３unknown IMI converter ０unknown １man ２women ９not applicable ０unknown １man ２women ９not applicable Tokyo Chiyoda Kasumigaseki X-X IMI building 203 Connected service Kasumigaseki X-X IMI Building 203 Tokyo Chiyoda Kasumigaseki X-X IMI building 203 Legacy systems and data IMI converter Connected service

• Data connect to the world, so global interoperability is essential. Concept of Data maturity and quality 36 Data Process Governance • Is the data of sufficient quality? • ISO25012 • Are there any issues with the process? • ISO25024 • Is the data being managed strategically? • ISO8000-61 Usage USER SIDE SUPPLY SIDE Are users making use of the data? Geospatial data Platformer AI IOT • ISO19157 • DSA whitepaper in Japan • Quality Assurance for AI guideline in Japan

• The data maturity model consist of Data view(ISO25012), Process view(ISO25024) and Governance view(ISO8000-61) －The check items have 4 levels.(Ad hoc, Part of, Basic, Sustainable) Trial project of data quality model 37 Service Data Process & Governance We measured some services. It combined service maturity model and data maturity model.

• We provide some resources for users. And we provide a maturity model and tools for data owners. Activities for data maturity and quality Data design Data collection Data integration External data acquisition Data processing Presentation Other use Data store Delete ISO25024 Reference data model Base registries Converter Validator Form/API DCAT-GOJ Feedback Data quality management guidebook Data management guidebook Architecture guidebook Data HR management framework Open data guidebook (Harnessing the open data) Use cases (Open data 100) Reference data model Design system USER SIDE SUPPLY SIDE

• In order to improve data and make use of data, an index is needed to evaluate it. We need common quality index 39 Data producer Data owner Platformer Servicer Data consumer Simple index for use data Detail index to improve data Index for data product quality Index for metadata quality

40 GIF priority action: Others

• We are using archimate as an architecture modelling language. • We can discuss the detail of KPIs, services, functions and data on the model. • We also use UML class diagram for data models and BPMN for process model. Modelling 41 KPIs Platform(function) Data Services Cross-industry services Rules Goals Assets Data models Tools

• To improve data quality, specialized personnel are needed. Literacy education is also needed to prevent misuse of the data. Human resource for data management 42 Data Architect(AR) Data Engineer(Design) (AN) • Data Analyst Data Engineer(Development)(DB) • Database engineer Data Scientist(DS) AI Specialist(AI) Geospatial data Specialist(GE) Literacy for government staffs Human Resource data model Skill set Role definition Evaluation sheet Courseware Evaluation Course Business fields

43 The role of central government and municipalities

Ministries • Set rules • Set standards • Provide common tools • Coordinate the programs • Support budget Prefectures • Support municipalities • Coordinate the wide area programs City, Town and Village • Create and run services • Request issues to ministries • Propose pilot services to ministries Roles 44

• Municipalities and private sectors provide services by using government support. Relationship of activities 45 GIF core Systems in local governments Services from the private sectors Open data System standards for local government Services from local government GIF for local services Other standards Common tool and services

We started new nation-wide projects 46 Smart City Digital Garden City Digital Village Public service density/ Public transportation Nature & Environment Aging Congestion Disaster Risk Management Carbon Neutral Zero carbon city / Carbon neutral leading area Government Interoperability Framework(GIF) / Base registries / Open data

• Map is essential information for smart city. 3D models and Digital Twin 47 Plateu 3D models(CityGML) https://www.mlit.go.jp/plateau/ https://www.youtube.com/watch?v=dbRRwQje9Fo Virtual Shizuoka 3D points models Tokyo digital twin project 3D models(CityGML) Laser scanner Underground map https://info.tokyo-digitaltwin.metro.tokyo.lg.jp/zissyou02/

48 Future Plan

• We will －reorganize our teams ∙ We will work with other data-rerated government organizations. －launch a revised strategy in next June. ∙ From platform to services －work with AI strategy team. • G7 －DFFT －International partnership for legislations 49

We are building the future society. 50