Ontology Whitepaper

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ONT A New High-Performance Public Multi-Chain Project & A Distributed Trust Collaboration Platform

Table of Contents PART I: TRUST SYSTEMS AND Ontology PART III: Ontology'S ECOSYSTEM AND APPLICABLE SCENARIOS P1 The Three Dimensions of Trust P15 Introduction P3 Current Issues in Trust Networks P16 Multi-Source Identity System for People P4 Ontology's Ethos P17 Multi-Source Identity System for Objects P5 Vision and Structure P18 Distributed Data Exchange P19 Distributed Collaborative Systems PART II: ONTOLOGY TRUST NETWORK P20 Distributed Equity Management P7 Ontology's Trust Ecosystem P21 Distributed Community Management P9 Ontology's Framework Technology P22 Distributed Content Generation and P10 Decentralized Identity Verification and Multi- Trade Modules Factor Authentication P23 Distributed Reputation System Delivering a Decentralized Trust System P24 Decentralized Inclusive Financial Services P11 Distributed Ledger Technology P25 Applicable Scenarios P12 Distributed Data Exchange P13 Other Key Functions and Modules PART IV: ECOSYSTEM / GOVERNANCE / INCENTIVIZATION P27 The Ontology Family P29 Compliance

Ontology is a blockchain/distributed ledger network which combines a distributed identity system, distributed data exchange, distributed data collaboration, distributed procedure protocols, distributed communities, distributed attestation, and various industry-specific modules. Together this builds the infrastructure for a peer-to-peer trust network which is cross-chain, cross-system, cross-industry, cross-application, and cross-device.

I TRUST SYSTEMS AND ONTOLOGY NETWORK The Three Dimensions of Trust Trust is a key component in human organization and social collaboration. Trust has become the core requirement of social and economic partnership that has been built up through technology, law, and community throughout history. 1

PART I. TRUST SYSTEMS AND ONTOLOGY Trust through Technology: Trust through Legal Systems: Trust through Communities: Building trust through technology is Trust in legal systems is the oldest Trusting those close to us can be the seen as a promising area in today's and the most basic trust mechanism, most natural form of trust. Sociologists information society. Technologies like assuring rights and protections across put the number of people we trust at cryptology, biological devices, and industries and across the world. less than one hundred; it is intrinsically big data are being used to build trust difficult to build trust networks on across industries. Economic systems, which are larger scales. inseparable from legal systems, are The introduction of blockchain a top choice for integration into Since the era of informatization and technology has brought trust to the blockchain. This means a pairing of the internet, decentralized network masses through shared access to economic and legal systems is needed systems such as peer-to-peer networks decentralized information. Blockchain to address certain issues including: and blockchains have created online has not just built trust in individual communities much larger than projects - it has fundamentally changed The issue of legal authentication. traditional communities. Based on the future of trust ecosystems. Due to the decentralized and these there have been many attempts digitalized nature of blockchains, to build new communities of trust, comprehensive collaboration with such as Google PageRank, Pretty Good offline legal entities is needed. Privacy, Web of Trust, as well as other decentralized evaluation systems and The issue of legal support. decentralized communities. Support for sandbox experiments, automated compliance, and moderation are required for the entire blockchain system. The issue of identification. Blockchains need to better collabo- rate with the world to build better identity verification solutions. 2

PART I. TRUST SYSTEMS AND ONTOLOGY Current Issues in Trust Networks Although we now have a range of trust mechanisms we still face many barriers in establishing trust including: Fragmented sources of trust. When Inaccurate identity verification. Us- Weak community management. data has to be verified by multiple ing a single information management Current community management sources the process can become system makes it difficult to form systems do not have sufficient time consuming, costly, and put data comprehensive identity portfolios. moderation tools. security in jeopardy. Security issues in the Internet Identifying false information. There Missing role of the individual. of Things. Currently there are are not sufficient mechanisms to Individuals do not have enough say not sufficient identity verification identify, report, and remove false in the use of their own data and mechanisms to prevent illegal and information from online systems. authentication of other data. malicious node access to the Internet of Things. Weak reputation systems. Adequate Emergence of new sources of trust. reputation systems require massive With fragmented sources of trust Data exchange security issues. data sets, however fragmentation the overall cost of verification has Current data exchange systems are of data in current systems does not increased. centralized, which causes problems make this possible. such as loss of data origin and Data management monopolization. threats to data security. Making charitable donations. It is Today’s data management systems becoming more important to provide are monopolizing user data while Trust issues in collaborative high levels of transparency when failing to compile useful and systems. Without a central author- managing charity donations. Basic accessible portfolios of data for ity it is difficult to form trust in transaction tracking can only solve external use. collaborative systems. part of the problem; comprehensive verification of organizations and Data fragmentation. Due to frag- Transparency issues in equity recipients is needed. mentation of databases, data which management. New equity manage- is not monopolized loses out on ment models such as crowdfunding trading potential and can often not find it hard to build trust due to lack be authenticated and used. of transparency. The variety of trust mechanisms at hand today have indirectly become the weakness of today's trust systems. Building a network which integrates the fragmented industry is needed to build a true and complete trust system. 3

PART I. TRUST SYSTEMS AND ONTOLOGY Ontology's Ethos Ontology has architected a distributed trust system. It incorporates multiple trust types in an integrated protocol system with various blockchains and databases. Multi- source identities and multi-source data exchange protocols have been implemented into the network, building a distributed trust system that is cross-chain, cross-industry, cross-system, cross-application, and cross-device. Ontology aims to develop its trust ecosystem through partnerships to provide distributed services including distributed communities, data verification, data exchange, and credit across industries. 4

PART I. TRUST SYSTEMS AND ONTOLOGY Vision and Structure Ontology’s Trust Network is a protocol network built with multiple blockchains and systems to support use with all business types. In order to meet the needs of different industries, the flexible design structure is modularized, pluggable, and easily expandable. Ontology applies blockchain technology to all business types, providing blockchains, smart contracts, distributed verification management, data exchange, and other protocols and APIs. Users can easily develop distributed services through Ontology without having previous knowledge of distributed networks. An integrated and diverse distributed trust network and the tool for building a trust ecosystem 5


II ONTOLOGY TRUST NETWORK Ontology's Trust Ecosystem Ontology is devoted to building a trust ecosystem through its decentralized services. With Ontology's infrastructure industries can integrate and develop their own systems of trust. 7

PART II. ONTOLOGY TRUST NETWORK Peer-to-Peer Collaboration in the Trust Network Collaborative Ecosystem Distributed content generation and trade Distributed community management Distributed reputation management Distributed interests management Distributed data collaboration Distributed financial services Distributed collaboration Verification of objects Verification of people Supported Scenarios Distributed Ledger Technology Foundational Infrastructure Distributed identity verification and Distributed trust transfer system authentication system 8

PART II. ONTOLOGY TRUST NETWORK Ontology's Framework Technology Decentralized Decentralized Decentralized Decentralized … data collaboration collaborative content sharing reputation system and trade systems Application Framework Application Modules SDK Data trade module Data protection module … Data synchronization Multi-source verification API module module Application Protocols Registration/verification Multi-source Data reading protocol protocol verification protocol User authorization Data exchange protocol … protocol Core Protocols Distributed Trust Framework Data Multi-source Protection identity Authorization verification Smart … Contracts Trustworthy certification Trustworthy Data Storage Distributed identification Distributed Ledger Layer … ONT Core Ledger NEO Ethereum Bitcoin At Ontology’s foundation is a fully Ontology also provides systems for and procedure management protocols decentralized ledger system that secure data storage, hardware options through the use of APIs, SDKs, and includes smart contracts and for key management, and encrypted other modules. security protocols. Ontology provides data analysis. Together this creates compatibility support for complex an application platform that allows technological systems, whether that for all kinds of services to become be existing blockchains or tradition decentralized. information systems. All systems feature decentralized entity management with Ontology provides the framework support for main protocols and different for use of all type of applications, password standards. including decentralized data exchange 9

PART II. ONTOLOGY TRUST NETWORK Decentralized Identity Verification and Multi-Factor Authentication A decentralized and multi-factor identity verification system that assures data privacy is core to building a trust network. Such a system can provide identity verification systems for individuals, organizations, and physical objects. Multi-Factor Authentication Organizational Identity Specialized Identity Verification Ontology’s identity verification system Organizational networks can be Entities can create specialized identity is characteristically decentralized. established using information such as verification systems based on industry- Decentralized identity verification is not student IDs for academic institutions or specific or legal requirements, for predefined by industry nor does it come employee IDs for businesses. All entities example by integrating compatibility with set features, it is instead built by can select a range of identity verification with external electronic identification project-specific requirements. methods in order to create systems system such as CA Identity Manager, free from third party interference. or by integrating requirements of Private information is securely stored in governments, organizations, academia, decentralized databases. businesses, or social groups. Delivering a Decentralized Trust System In Ontology a decentralized trust system can be implemented alongside traditional trust systems. This includes: Community Trust Statement Community trust is an effective system in which A statement is the medium of community trust. In communities and individuals play an active role in identity Ontology a statement is a confirmation passed from verification. one entity to another; only one statement is needed to instantly verify information. Trust Anchor Trust Transfer A trust anchor is an entity that has been entrusted to conduct identity verification. The higher the trust in the Trust transfer is conducted by submitting information trust anchor, the higher the trust in the network. required and receiving a statement. This could be an individual submitting their own identity information or using previously submitted information to form a portfolio of multiple identity certifications. 10

PART II. ONTOLOGY TRUST NETWORK Distributed Ledger Technology Ontology’s storage system works on a distributed ledger. The key feature of the completely decentralized, tamper-proof ledger is that trust is shared amongst multiple parties through the use of smart contracts, distributed networks, distributed storage, distributed authority, distributed security, and a variety of modules. Entity Registration and Authorization Procedure Protocols Data Attestation An identity registration and Ontology’s procedure protocols are The distributed ledger system does not authorization system can be built with carried out with distributed ledger only store data but also records its use. Ontology's adjustable configurations or technology, cross-chain entities, Each data request, data matching, data by using a third-party authentication cross-system privacy, and cross-chain transfer, and data usage is attested to system such as CA Identity Manager. protocols. the ledger, forming a complete private Community authentication and industry- record of the data use. specific verification methods can also be Data Exchange used to allow participants access Smart Contracts All entities using Ontology can use the to identity verification through data exchange. It allows users to have Businesses can grow by implementing the blockchain. full control of their data; having the smart contracts and trust networks Data Directory tools to trade it while being able to through new procedure protocols, meet their own privacy requirements. controls, and exchanges of data. Data can be registered categorically to directories and use data identifiers (ONT Data ID) and data resource identifiers (Data URI) to match and verify to requirements through the decentralized system. 11

PART II. ONTOLOGY TRUST NETWORK Distributed Data Exchange Ontology supports distributed data exchange, which includes: Peer-to-Peer Data Transmission Data Authorization Mechanisms Copyright Protection of Data The data exchange system uses Data privacy protection and leakage Ontology stores, manages, and attests blockchain to support accurate search and prevention are always assured whilst data throughout its life cycle. A digital transmission of data between two parties giving the user full control of their identity is created for each copy of data without having a centralized database. data; each data transfer must receive from registration, request, authorization, authorization from all parties. to exchange. Copyright protection is also recorded to each copy on the blockchain. Distributed Data Storage A distributed data storage layer supports decentralized storage for different types of data. 12

PART II. ONTOLOGY TRUST NETWORK Other Key Functions and Modules Ontology Crypto Package (OCP) Ontology Marketplace (OM) GlobalDB Ontology provides a series of Ontology Marketplace is a distributed GlobalDB is a distributed key- cryptography and data security module data exchange complete with data value storage. It provides multiple support in areas including multi-factor sets, algorithms, and models. It acts backend database module options entity authentication, distributed data as an extension to Ontology, providing including levelDB, RocksDB, TiDB, and exchange, and distributed procedure data products, data predictions, and cockroachDB. protocols. This includes encrypted data data computing resources. At the same transfer, key sharing protocols, multi- time it maintains compatibility with GlobalDB is a blockchain database and party key management, ring signature other major cross-chain systems to IPFS module. GlobalDB provides the modules, blind signature modules, and create a large data exchange platform. ability for distributed transactions, secret sharing mechanisms. In identity The native dApp lets providers across scalability, real time checking of the and data validation zero-knowledge industries implement the data trading blockchain, and ability to interact proof and homomorphic encryption market. with data off-chain. It can be used to schemes are used, and in a collaborative correlate the blockchain and data, the application two records are kept. Other blockchain and AI, and so on. multi-party technology schemes are being explored for the future. 13

PART II. ONTOLOGY TRUST NETWORK Ontology will build further modules according to project-specific requirements. HydraDAO Ortorand Consensus Engine HydraDAO is a data prediction and Certain distributed ledger networks interaction module integrating smart within Ontology’s chain network support contracts, cross-chain, and cross- Ontorand Consensus Engine (OCE), a new data source collaboration. It contains consensus engine. Ontorand is a highly Ontology’s DAO (distributed autonomous effective version of the DBFT consensus organization) and cross-chain data protocol based on Onchain’s Distributed interaction (big data/AI) features. Networks Architecture (DNA). It has Ontology’s governance mechanism reached near-infinite scalability and supports democratic and AI-automated requires a relatively low hashing rate, propositions and verifications. A unique making it highly unlikely to experience DAO address and polling token will forks of the network. Ontorand’s be created during the process, which block-creation speed is only limited allows DAO to automatically add funds to internet speed, usually resulting in and results to Ontology. Once polling confirmations within 20 seconds. As a is complete, DAO will autonomously truly decentralized protocol, Ontorand execute in accordance with the tamper- entitles its users to consensus rights, proof smart contract. The mechanism eliminating cases where miners or other allows data exchange and governance in parties solely control confirmation Ontology to function with flexibility and power. Ontorand selects who confirms supports the technology for large-scale the blockchain using a verifiable random automated network operations. function, every confirmation receiving an Ontology seed directing to the next confirmation. Ontorand also supports pluggable verifiers and online protocol recovery and upgrade. Meanwhile, in order to meet needs from different chains in Ontology, the distributed ledger framework also supports pluggable consensus mechanisms including DBFT, RBFT, and custom PoW. 14

III ONTOLOGY'S ECO SYSTEM AND AP P LIC AB LE S C ENARIOS Ontology helps its partners improve their systems by integrating them into the blockchain infrastructure and designing comprehensive applications that come with full technical support. This part will introduce some of the applications that can be built onto the network. 15

PART III: ONTOLOGY'S ECOSYSTEM AND APPLICABLE SCENARIOS Multi-Source Identity System for People Users can collect and manage their own identity data from various sources including public institutions, banks, businesses, family, colleagues, and friends. What do I want? Faith, knowledge, interest, viewpoint What skills do I have? What have I experienced? Language, driving, profession Education, work, travel What unique characteristics do I have? What do I own? Fingerprints, height, weight, DNA Assets, debt, property ONTOLOGY NETWORK Multi-Source Identity Verification School Family Classmates Friends Government Bank Company Partners NGOs Multi-Source Identity Authentication Data Tracking Multi-source identity authentication is the verification All authentications on Ontology are performed with process of an identity by more than one source to give it a signatures, which cannot be forged or repudiated. more secure and trustworthy certification. Meanwhile, to assure a secure authentication system, authenticators themselves can be subject to review if their Comprehensive Personal Profile authority or trustworthiness is questioned. A comprehensive personal profile describes the state in which an individual has built up an identity with data from multiple sources relevant to them. 16

PART III: ONTOLOGY'S ECOSYSTEM AND APPLICABLE SCENARIOS Multi-Source Identity System for Objects In Ontology you can register digital identities of physical objects into the distributed network under the supervision of the product owners and/or producers. Each object has its own API and can interact with other digital identity holders. Relationship with People Ownership, right of use, manufacturing, sale, transport Relationship with Other Goods Relationship with Money Manufacturing, assembling, storage, Price, rent compatibility, consumption Tangible Characteristics Location, date, properties ONTOLOGY NETWORK Object Authentication Cycle Object Data Recording and Authentication Objects can be tracked throughout their life cycle Ontology can fully record and authenticate with multi-factor authentication by: object data including ownership, circulation, user behavior, and other relevant information. Registering digital DIDs onto Ontology. Verifying objects with digital signatures and endorsement verification. Tracking the use and any other related data. 17

PART III: ONTOLOGY'S ECOSYSTEM AND APPLICABLE SCENARIOS Distributed Data Exchange Decentralized Database 6. Obtain exchanged data 5. Upload encrypted data Data Buyer Data Provider User 1. Data request Registration Data Discovery Data Transaction dApp Data on a single entity no longer has to be manually gathered from multiple sources. In Ontology a comprehensive portfolio of data is already compiled and can be accessed with the user ID, 2. Authorization Data Exchange 3. Data application Data Exchange allowing for easy data collection and User Agent Module Module (ODTP) (ODTP) use. Data Exchange 7. Smart contract 4. Smart transaction Registration Attest transacton complete The data owner must accept the data request before the data is exchanged ONTOLOGY NETWORK and the users credited. User online behavior data is often stored by service providers for analysis and trade. Ontology provides a data exchange system in which all data (with consent of the owner) can be discovered and traded to the owner's benefit whilst meeting individual privacy requirements. By nature of blockchain and smart contracts, all records on Ontology are open, transparent, trackable, and tamper-proof. This technology can be applied to areas including signing certificates, joint credit, distributed collaborative computing, and AI training data. 18

PART III: ONTOLOGY'S ECOSYSTEM AND APPLICABLE SCENARIOS Distributed Collaborative Systems Distributed collaborative systems in Ontology help build up the trust network. See a doctor Send electronic prescription and medical history Doctor Patient Send credentials Purchase medicine Register to identity Pass inspection and and service interface send medicine Ont ID Register to identity and service interface Inquire doctor and hospital service interface Check hospital's credentials Hospital Pharmacy An example of distributed collaborative systems in medicine: When doctors, hospitals, and patients register their identities onto the blockchain, the blockchain fills in the trust gap between the pharmacy and patient with record of the medicine's key information. The pharmaceutical enterprise then sells the prescribed medicine to the patient after verification of the doctor and hospital's credentials. Authorization Records Activity Records Evaluation Modifiable authorities of each All activity is recorded to ensure A multi-party confirmation and participant are recorded and confirmed transparency of participant identity, endorsement mechanism allows for by all relevant parties. activity, and outcomes. evaluation of collaborative entities. 19

PART III: ONTOLOGY'S ECOSYSTEM AND APPLICABLE SCENARIOS Distributed Equity Management Today's economic system contains a range of equity management models, though due to factors such as low transparency and information asymmetry these projects lack credible trust mechanisms. Equity management is also facing obstacles regarding project assessment, risk warnings, information disclosure, equity circulation, and authority entrustment. In light of this Ontology has built a trustworthy distributed equity management system. ONTOLOGY NETWORK Trustor Investor Rights entrust Equity circulation Decision making Trustee/ Company, Investor Investor Investor Investor Investor organization or project Providing project information/ risk warnings Ont ID Upstream and Cooperative Media Regulatory downstream organizations agencies enterprises Example in Investment Management: Distributed Interests Configuration Ontology has the functions to: Interests configurations are transparent to all parties and recorded onto the blockchain. Safely circulate data by having the option to include factors such as basic project information, operation Distributed Rights Entrustment status, risk warnings, and records. Ontology allows for multi-party rights entrustment and Create a multi-party assessment system to include recording, including the function to dispute actions by project operators, investors, cooperative organizations, providing relevant data. and upstream and downstream enterprises in which parties provide information on each other. Manage a project evaluation system where data can be accessed and assessed by its investors. 20

PART III: ONTOLOGY'S ECOSYSTEM AND APPLICABLE SCENARIOS Distributed Community Management Current online communities are run by centralized service providers. Ontology provides the framework for communities to run in a purely decentralized system. Online community 1 Online community 2 Online community 3 Entrance 1 Entrance 2 Entrance 3 Ont ID ONTOLOGY NETWORK Multi-source evaluation Organizations, Other individuals Credentials companies, etc New Member Control Other Features munities is essential. Ontology offers a system where users with In Ontology community managers can To address the difficulty of certifying authority can directly push content build their communities steadily by an individual's authority and credibility and ordinary users must first pass managing the inflow of members into within a distributed community content approval. the community. Ontology has integrated: An incentivization design. A reward Community Ranking A public credibility system. mechanism recognizes content According to the personal details, creators for the reactions their Most communities have ranking publication history, and chat content receives from other system where different users hold history of an individual, the com- community members (such as different levels of authority and munity can carry out multi-party “likes”). All content reactions discourse power. In Ontology users can evaluation of community members are recorded to the blockchain to present their DIDs or other evidence to reward public credibility. avoid data manipulation. of experience (for example someone presenting proof of a Java community Content publication control. group they manage) to community Controlling false or inappropriate managers to receive recognition. information in distributed com- 21

PART III: ONTOLOGY'S ECOSYSTEM AND APPLICABLE SCENARIOS Distributed Content Generation and Trade Modules Current services can convert content into tangible assets (e.g. paid content) or into other types of intangible assets (e.g. content publishing with a profit model), though nevertheless at a cost to the content producer. Ontology, however, has introduced a comprehensive distributed trade system between content generator and consumer. Optimized Content Search Content Security Guarantee Users can choose to only view content produced by users Ontology’s tamper-proof identification system can function with a certain reputation level or entrust third-parties for with legal validity. Since blockchain is an open source content recommendations. In this system users have greater third-party technology, users can carry out IP legal right control in getting the content they want and can getting a authentication, payments, and transfers worldwide. The fairer price for it. reputation system helps build a reputation-based protection for content that adds another layer of security to the content exchange system. Text Content as Property Images Ownership confirmation, profit, Content transfer of intellectual property creator's rights Audio protection ONTOLOGY NETWORK Video The cost of Liquidity Maximized liquidity trust Author Transaction Audience Content as Information Cost Trustworthy data provision, fair ranking system, recognition of high quality content Content provider 22

PART III: ONTOLOGY'S ECOSYSTEM AND APPLICABLE SCENARIOS Distributed Reputation System In our daily lives we have to provide valid proof of certification for personal endorsement, for example with academic certificates. A reputation on the other hand is seen as a weak form of validation. School Company NGO Family Bank Multi-party Receive evaluation information Applicable scenarios Police Authorization Job applications Receive information channel Loan applications Ont ID Multi-source authentication Check credentials Tax office Reputation management Comprehensive Personal Profile … Multi-source Receive authentification information Utilities Certification Industry Media Community authority Credit Management Building on Trust Models Ontology calculates local and global trust levels Trust models can be further developed by according to modifiable criteria. Local trust collaborating with the content generation and calculation uses local evaluation parameters and exchange system, for example by using multi- opinions, whereas comprehensive trust uses global source or multi-factor authentication systems for evaluation parameters to assure certainty and content evaluation and verification. diminish the influence of false information. Data Management Ontology combines two types of trust data management models: one storing data in a completely decentralized system and another storing data partly in centralized management systems where needed. 23

PART III: ONTOLOGY'S ECOSYSTEM AND APPLICABLE SCENARIOS Decentralized Inclusive Financial Services Small businesses and individuals often lack credit records and collateral while facing high operation costs. This makes them riskier for banks and other financial institutions, leading to high interest rates. At the same time the cost of change is high and businesses face retributions to their reputation if they do not comply, leading to a multifaceted dilemma. Inclusive financial services Trust information Data/identity Funds/identity Follaborative system collaborative system Fu on Ide nd ati nti sc on n rdi ati oo ty coo in rdi coo ord na rdi ty co tio nti n ati ta n Ide Da on Effective Coordination On-chain of Identity Data Management of Funds Authorization Application Multiple trustworthy data sources Financial Medium-sized and institutions small enterprises /individuals From a Financial Aspect Ontology helps businesses and Ontology helps businesses and individuals become active managers of their data. With multi-source data coordination and authorization individuals can easily and safely provide information to apply for financial services and receive fairer interest rates from reducing risks to the other party. From a Social Aspect Financial institutions can also collaborate with Ontology, establishing multi-party security coordination and analysis mechanisms to provide better interest rates and services to small businesses and individuals. 24

PART III: ONTOLOGY'S ECOSYSTEM AND APPLICABLE SCENARIOS Applicable Scenarios Ontology can provide distributed infrastructure to a range of scenarios without service providers having previous knowledge of distributed networks, blockchain, or cryptography. Listed below are scenarios that can benefit from integration into Ontology: Finance Internet of Things Trading Device-to-device payments Securities Automated operations Wealth management Grid management Derivatives trading Smart home management Collateral management Office management Supply chain finance Consumer Payments Sharing economy Micropayments Supply chain Business-to-business international remittance Pharmaceutical tracking Tax filing and collection Agricultural food authentication Know your customer (KYC) Shipping and logistics management Anti-money laundering (AML) Media Insurance Digital rights management Claim filings Art authentication Claims processing and admin Ad placement Fraud detection Ad click fraud reduction Telematics and ratings Resale of authentic assets Digital authentication 25

PART III: ONTOLOGY'S ECOSYSTEM AND APPLICABLE SCENARIOS Software Development Asset Titles Micritization of work Diamonds Disbursement of work Designer brands Ad placement direct to developer payments Car leasing and sales Ad placement API platform Home mortgages Ad placement notarization and certification Land title ownership Medical Digitalization of assets Record sharing Government Prescription sharing Voting Multi-factor authentication Vehicle registration Personalized medicine Benefits distribution DNA sequencing Copyrights Education certificates 26

IV ECOSYSTEM / GOVERNANCE/ INCENTIVIZATION The Ontology Family Ontology is built to be the foundational infrastructure of a trust ecosystem, supporting the development and upkeep of decentralized technology and data systems while acting as the connector between networks so that partners only need to focus on their business operations. Ontology Family are the major partners in the Ontology ecosystem. The following are the groups that make up the Ontology Family: 27

PART IV. ECOSYSTEM/GOVERNANCE/INCENTIVIZATION Distributed Distributed Content Equity Management Generation and Trade Asset Copyrights Management Protection Verification Internet of Verification Public Welfare of Things Things of People Distributed Finance Distributed 3FH Data Systems Insurance Services Community and Exchange Management $SPTT Government Health Care Administration Distributed Distributed 3FHJPO Reputation ONTOLOGY Community Management Management $SPTTSFH TRUST NETWORK 3FHJPOBM4DFOBSJP $SPTTSFHJPOBM4DFOBSJP 3FHJPOBM$PMMBCPSBUJPO $SPTTSFHJPOBM$PMMBCPSBUJPO Verification Service Providers Application Service Providers Communities Electonic identification, CA Cross-industry application teams Communities in Ontology can pool Identity Manager, and other publicly establishing their own projects on top together global institutional and credible identity verification service of the Ontology infrastructure are core individual-level talent to create an ideal providers for institutions, companies, to the Ontology Family. At the same environment for sharing and growth. organizations, social groups, time Ontology helps services succeed at and individuals. their projects by helping Individuals with the creation and development Individuals act as fuel to the Ontology of applications. ecosystem, powering the authentication and endorsement systems whilst helping expand the decentralized communities. 28

PART IV. ECOSYSTEM/GOVERNANCE/INCENTIVIZATION Compliance Cross-industry compliance Compliance with Compliance with regulators data verification Cross-legal system Cross-region compliance compliance Compliance with data exchange Ontology Network's Compliance Support Cross-industry cross-chain compliance Cross-legal system cross-chain compliance Cross-region cross-chain compliance 29

PART IV. ECOSYSTEM/GOVERNANCE/INCENTIVIZATION Ontology’s identity verification and data easily integrate legal framework into the systems are compliant with the various ecosystem, making it easy for all entities legal frameworks in different regions and to be compliant across the board while industries across the world. To accomplish securing Ontology’s status as a secure this Ontology has built in mechanisms to decentralized trust network. 30

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