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Ontology for the orchestration of the aerOS continuum. @en
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AIRO represents AI risk concepts and relations based on the AI Act draft and ISO 31000 standard series. @en
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Metadata vocabularies are used in various domains of study. It provides an in-depth description of the resources. In this work, we develop Algorithm Metadata Vocabulary (AMV), a vocabulary for capturing and storing the metadata about the algorithms (a procedure or a set of rules that is followed step-by-step to solve a problem, especially by a computer). The snag faced by the researchers in the current time is the failure of getting relevant results when searching for algorithms in any search engine. AMV is represented as a semantic model and produced OWL file, which can be directly used by anyone interested to create and publish algorithm metadata as a knowledge graph, or to provide metadata service through SPARQL endpoint. To design the vocabulary, we propose a well-defined methodology, which considers real issues faced by the algorithm users and the practitioners. The evaluation shows a promising result. @en
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The Core module represents general-purpose concepts orthogonal to the whole network, which are imported by all other ontology modules (e.g. part-whole relation, classification). @en
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The Context Description module includes models for the context of a cultural property, in a broad sense: agents (e.g.: author, collector, copyright holder), objects (e.g.: inventories, bibliography, protective measures, other cultural properties, collections etc.), activities (e.g.: surveys, conservation interventions), situations (e.g.: commission, coin issuance, estimate, legal situation) related, involved or involving the cultural property. Thus it represents attributes that do not result from a measurement of features in a cultural property, but are associated with it. @en
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The Denotative Description module encodes the characteristics of a cultural property, as detectable and/or detected during the cataloguing process and measurable according to a reference system. Examples include measurements e.g. length, constituting materials e.g. clay, employed techniques e.g. melting, conservation status e.g. good, decent, bad. In this module are used as template the following Ontology Design Patterns: - http://www.ontologydesignpatterns.org/cp/owl/collectionentity.owl - http://www.ontologydesignpatterns.org/cp/owl/classification.owl - http://www.ontologydesignpatterns.org/cp/owl/descriptionandsituation.owl - http://www.ontologydesignpatterns.org/cp/owl/situation.owl @en
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The ArCo module is the root of the network ArCo - Architecture of Knowledge. It imports all the other modules and models top-level distinctions from the cultural heritage domain. @en
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The module Location models information related to the localization and georeferencing of a cultural property. In this module are used as template the following Ontology Design Patterns: - http://www.ontologydesignpatterns.org/cp/owl/collectionentity.owl - http://www.ontologydesignpatterns.org/cp/owl/classification.owl - http://www.ontologydesignpatterns.org/cp/owl/place.owl - http://www.ontologydesignpatterns.org/cp/owl/timeindexedsituation.owl - http://www.ontologydesignpatterns.org/cp/owl/situation.owl @en
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The Catalogue module allows the description of concepts related to the Italian General Catalogue of Cultural Heritage (ICCD-MiBAC), and in particular catalogue records, that is XML files recording all data gathered by a cataloguer on a particular cultural property. @en
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The Cultural Event module models cultural events, i.e. events involving cultural properties. @en
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Ontology that defines concepts for representing the aerOS Data Catalog @en
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An ontology containing additional terminology for structuring and annotating RDFS/OWL taxonomies for describing constructions (components, materials, spatial zones, damages, construction tasks and properties). It also functions as an index for known taxonomies starting from root classes and properties. @en
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The Construction Tasks Ontology (CTO) describes tasks operating on construction elements, spatial zones and/or damages. The tasks are either planned or executed depending on the dataset metadata context of the dataset its used in. Five different types of tasks are defined: instalment, removal, modification, repair and inspection. Consequences of tasks on the dataset, i.e. added and/or deleted triples, are modeled using reified statements. The tasks can link to a reified statement using the CTO relations. @en
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The ontology, presented here in a beta version, is based on the analysis of the documentation and descriptive requirements of the Intesa Sanpaolo Historical Archive and is intended to describe the content of historical banking documents and of some of the activities carried out by the bank, particularly in relation to third parties (loans, charity donations, seizures and confiscations, etc.), which involve the initiation of processes or the production of documents. The focal point of the descriptive model is the bank - an entity that initiates different types of processes, whose common feature is that they are structured into various stages/events - and the relationship between the documentation produced and the information it contains. In fact, this ontology is based on information collected from archived documents which describe various processes and activities carried out by banking institutions: the starting point for its construction were the inventories and databases of documentation stored in the Historical Archive which was produced by the various banks that over time were merged into Intesa Sanpaolo. The ontology was created to provide a sufficiently abstract representation and model for describing the processes of various banking activities from which the documentation was produced - from a company's request for financing and its outcome, to the preparation of seizure, confiscation and asset restitution filings, to charitable contributions, just to mention a few examples - reusing models that were already well established and widely used. The structure of the proposed ontology is in fact intended to adapt to the various activities, described in the archive files that a banking institution performs in relation to third parties. The proposed ontology is therefore not an ontology on banking activity in general, but on the relationship between this activity and the documents that are produced. Moreover, its objective is not to describe the documents in the strict sense of the term, for which reference is made to OAD ontology. The purpose of this project is to lay the initial, and fundamental, building blocks for describing the complexity, variety, and breadth of the domain of archiving bank records and the data they contain. Despite having data from different banks relating to different activities and having already made arrangements for the integration of third-party datasets and ontologies, before completing the project we will have to wait for the processing of representations based on other types of documents and banking institutions, including non-Italian ones. @en
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CiteDCAT-AP is an extension of the DCAT application profile for data portals in Europe (DCAT-AP) for describing resources documented by using the DataCite metadata schema - the de facto standard for data citation, and used across scientific disciplines. Its basic use case is to make research data searchable on general data portals, thereby bridging the gap between scientific and public sector information. For this purpose, CiteDCAT-AP provides an RDF vocabulary and the corresponding RDF syntax binding for the metadata elements defined in DataCite. @en