POC4COMMERCE promotes sustainable, resilient, and trustworthy eCommerce by defining it over the ONTOCHAIN ecosystem, hence leveraging a hierarchical semantic modelling and ontological approach towards the effective and efficient interoperability of blockchain technology with the eCommerce domain. High-level goal. • An ontological stack of foundational and domain-legacy ontologies and a search engine for products and services.
and shared semantic model supporting the semantic interoperability of ONTOCHAIN stakeholders • Technical objectives ◦ One ontology for the essential stakeholders ◦ One ontology for eCommerce dynamics ◦ One ontology for the blockchain layer ◦ A search engine for enabling users (and applications) to conveniently find goods and services in an interconnected and interoperable marketplace in general ▪ E.g., find agricultural services/goods from a specific region, having specific quality, shipped to specific region ▪ E.g., find storing services for biological wheat of 1000 tons picking up from owner farm • Approach. A number of tools from the SOTA can be leveraged...
for Agents, Systems, and Integration of Services ◦ Describing agents, interactions, responsibilities and authorizations among agents ◦ Agents described in terms of their behaviors (goals, tasks, …) ◦ Defining ONTOCHAIN stakeholders, including final users ◦ Defining Ethereum essentials elements, in particular, smart-contracts (in the OASIS fashion) • OWL-2 ontology GoodRelations (and other popular ontologies for commerce) ◦ Describing market activities, goods, products, offerings, and services related with business and commerce ◦ Compliant with OASIS • High-performance SPARQL endpoint and suitable infrastructure allowing on-line/off-line reasoning capabilities • OWL 2 compliant reasoners: HermiT, Pellet, Fact++, ...
domain of interest • Resource: any physical or digital entity described via Semantic Web technologies, identified by IRIs and deferenceable • Triples: RDF building blocks consisting of a subject, a property, and a object • Graphs: RDF triples constitute graphs that can be named or anonymous • Datasets: collections of RDF graphs • Tracking changes in datasets: ◦ PROV ontology provides terms to trace the origin of resources, their derivation history, relationships between resources, and the entities that contributed to their existence ◦ Dublin Core provides terms to annotate resources with metadata (e.g., creator and versions) ◦ PAV ontology describes provenance data on digital resources as relationships with other resources and agents While RDF datasets may change, blockchain is immutable. Immutability can be leveraged to store versions of ontologies that may change over time, effectively tracking changes to ontologies by means of blockchain technology.
used to depict domain related agents, e.g., biomedicine, Web of Things (WoT), Internet of Things (IoT), … ◦ OASIS provides general purpose and high level descriptions of, in particular, agents and their interactions through their behaviors (goals and tasks that they perform) • Ontologies for services: ◦ Ontologies used to locate, select, employ, compose, monitor web-based services automatically ◦ Ontology for services, OWL-S: W3C ontology to describe web services in low level manner • AGENTS AND SERVICES To represent ONTOCHAIN participants in e-commerce, POC4COMMERCE will extend OASIS over the descriptions of the commercial parties involved in the ONTOCHAIN ecosystem, including blockchain-based smart contracts.
pages used to describe products or service in RDF fashion as to enable semantic search engines. • GoodRelations: OWL ontology describing offerings and pricing of tangible goods and commodity services, covering both product and service instance descriptions. E-COMMERCE The actual core of eCommerce is missing, that is, GoodRelations lacks a means to describe how products and services are released and purchased, and how to practically access them. Hence, the integration of GoodRelation with OASIS will form our commerce-layer ontology.
such as wallets, transactions, and blocks • Ethon ontology: semantic interpretation of smart contracts as services • OASIS: in addition to agents descriptions, constraints used to establish authorizations, responsibilities, and agreements among agents. OASIS may potentially be used to describe smart contracts and tokens BLOCKCHAINS A general purpose and formal description of smart contracts, transactions, and (non) fungible tokens is missing. In OASIS, smart contracts may be seen as agents, transactions as agent operations, tokens as digital certificates of ownership of (non) digital goods.
interoperable, and trustworthy 2. design tools allowing final users to transparently access all data provided by sellers 3. enable people and software alike to seamlessly interoperate on it 4. provide semantic interoperability for the ONTOCHAIN ecosystem POC4COMMERCE MISSION
the main ONTOCHAIN stakeholders ◦ description of features associated with agents (e.g., digital identities) • OC-Commerce ◦ description of offerings, auctions, biddings on any tradable type of asset ◦ and their integration with agents on an heterogeneous environment • OC-Ethereum ◦ description of smart contracts compliant with standard protocols (ERC70, ERC1155) ◦ description of smart contracts in the context of the deployment site POC4COMMERCE’S DESIGN
about NFTs representing a specific type of asset with peculiar characteristics ? • What are the offerings that can be purchased through specific payment methods? • What is the smart-contract generating the given NFT? • What is the supply chain of a specific product or service? • Which NFTs has been sold by a specific seller?
demonstrated on the ontologies OC-Found, OC-Commerce, and OC-Ethereum • KPI II. Competency questions defined and applied to the ontologies OC-Found, OC-Commerce, and OC-Ethereum • KPI III. SPARQL queries defined from competency questions and executed on the ontologies OC-Found, OC-Commerce, and OC-Ethereum • KPI IV. OWL 2 compliant reasoners executed on the ontologies OC-Found, OC-Commerce, and OC-Ethereum • KPI V. Data population of the ontologies OC-Found, OC-Commerce, and OC-Ethereum • KPI VI. Design and specification of the OC-CSE search engine through suitable UML diagrams and sketch exploiting standard Semantic Web APIs. POC4COMMERCE KPIs
interoperability thanks to the rise of the interaction level between producers and consumers • Clarity on time and quality of processes, notably on the extent to which an offer meets the customer’s needs and requirements • New business opportunities for customers and clients ◦ individuals and companies cooperate deciding the allocation and utilization of resources, and the subsequent effect on price • Clear representation of blockchains and commerce carried on it • Many implementation opportunities • Ground for the semantic interoperability of potentially innumerable domain-specific ontologies such as those for eScience, eEducation, eHealth, ...
trustworthy eCommerce through an epistemological process that delivers a family of ontologies that are ◦ compliant with the best ontological metrics criteria and approaches ◦ whose deployment site is realistic to confirm the requested interoperability and domain coverage ◦ concretely applicable as witnessed by the search engine ◦ industrially exploitable by project partners • Currently ◦ objectives met 90% ◦ incorporating real-world data from iExec marketplace ◦ running towards completion, due for next month
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