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 Ontologies


Why a computer program is a functional whole

arXiv.org Artificial Intelligence

Sharing, downloading, and reusing software is common-place, some of which is carried out legally with open source software. When it is not legal, it is unclear just how many copyright infringements and trade secret violations have taken place: does an infringement count for the artefact as a whole or perhaps for each file of the program? To answer this question, it must first be established whether a program should be considered as an integral whole, a collection, or a mere set of distinct files, and why. We argue that a program is a functional whole, availing of, and combining, arguments from mereology, granularity, modularity, unity, and function to substantiate the claim. The argumentation and answer contributes to the ontology of software artefacts, may assist industry in litigation cases, and demonstrates that the notion of unifying relation is operationalisable. Indirectly, it provides support for continued modular design of artefacts following established engineering practices.


Towards an ontology of HTTP interactions

arXiv.org Artificial Intelligence

Enterprise information systems have adopted Web-based foundations for exchanges between heterogeneous programmes. These programs provide and consume via Web APIs some resources identified by URIs, whose representations are transmitted via HTTP. Furthermore HTTP remains at the heart of all Web developments (Semantic Web, linked data, IoT...). Thus, situations where a program must be able to reason about HTTP interactions (request-response) are multiplying. This requires an explicit formal specification of a shared conceptualization of those interactions. A proposal for an RDF vocabulary exists, developed with a view to carrying out web application conformity tests and record the tests outputs. This vocabulary has already been reused. In this report we propose to adapt and extend it for making it more reusable. The content of this report has been published in French [16]


An Energy Ontology for Global City Indicators (ISO 37120)

arXiv.org Artificial Intelligence

To create tomorrow's smarter cities, today's initiatives will need to create measurable improvements. However, a city is a complex system and measuring its performance generates a breadth of issues. Specifically, determining what criteria should be measured, how indications should be defined, and how should the identified indicators be derived. This working paper is one in series that addresses the creation of a Semantic Web based representation of the 17 different themes of ISO 37120 indicators as part of the larger PolisGnosis Project (Fox, 2017). We define a standard ontology for representing general knowledge for the Energy Theme indicators, and for representing both the definition and data used to derive the Energy indicators.


A tetrachotomy of ontology-mediated queries with a covering axiom

arXiv.org Artificial Intelligence

We are interested in the problem of efficiently determining the data complexity of answering queries mediated by non-Horn description logic ontologies and constructing their optimal rewritings to standard database queries. In general, this problem is known to be extremely complex. In this article, we strip it to the bare bones and focus on conjunctive queries mediated by a simple covering axiom stating that one class is covered by the union of two other classes. We develop a novel technique to prove that, quite surprisingly, deciding first-order rewritability of even such simple ontology-mediated queries is PSpace-hard. The main result of this article is a complete and transparent syntactic AC0/NL/P/coNP tetrachotomy of path queries under the assumption that the covering classes are disjoint. We also obtain a number of syntactic and semantic sufficient conditions (without the path query assumption) for membership in AC0, L, NL, and P.


OBA: An Ontology-Based Framework for Creating REST APIs for Knowledge Graphs

arXiv.org Artificial Intelligence

In recent years, Semantic Web technologies have been increasingly adopted by researchers, industry and public institutions to describe and link data on the Web, create web annotations and consume large knowledge graphs like Wikidata and DBPedia. However, there is still a knowledge gap between ontology engineers, who design, populate and create knowledge graphs; and web developers, who need to understand, access and query these knowledge graphs but are not familiar with ontologies, RDF or SPARQL. In this paper we describe the Ontology-Based APIs framework (OBA), our approach to automatically create REST APIs from ontologies while following RESTful API best practices. Given an ontology (or ontology network) OBA uses standard technologies familiar to web developers (OpenAPI Specification, JSON) and combines them with W3C standards (OWL, JSON-LD frames and SPARQL) to create maintainable APIs with documentation, units tests, automated validation of resources and clients (in Python, Javascript, etc.) for non Semantic Web experts to access the contents of a target knowledge graph. We showcase OBA with three examples that illustrate the capabilities of the framework for different ontologies.


Counting Query Answers over a DL-Lite Knowledge Base (extended version)

arXiv.org Artificial Intelligence

Counting answers to a query is an operation supported by virtually all database management systems. In this paper we focus on counting answers over a Knowledge Base (KB), which may be viewed as a database enriched with background knowledge about the domain under consideration. In particular, we place our work in the context of Ontology-Mediated Query Answering/Ontology-based Data Access (OMQA/OBDA), where the language used for the ontology is a member of the DL-Lite family and the data is a (usually virtual) set of assertions. We study the data complexity of query answering, for different members of the DL-Lite family that include number restrictions, and for variants of conjunctive queries with counting that differ with respect to their shape (connected, branching, rooted). We improve upon existing results by providing a PTIME and coNP lower bounds, and upper bounds in PTIME and LOGSPACE. For the latter case, we define a novel query rewriting technique into first-order logic with counting.


Conceptual Modeling of Time for Computational Ontologies

arXiv.org Artificial Intelligence

To provide a foundation for conceptual modeling, ontologies have been introduced to specify the entities, the existences of which are acknowledged in the model. Ontologies are essential components as mechanisms to model a portion of reality in software engineering. In this context, a model refers to a description of objects and processes that populate a system. Developing such a description constrains and directs the design, development, and use of the corresponding system, thus avoiding such difficulties as conflicts and lack of a common understanding. In this cross-area research between modeling and ontology, there has been a growing interest in the development and use of domain ontologies (e.g., Resource Description Framework, Ontology Web Language). This paper contributes to the establishment of a broad ontological foundation for conceptual modeling in a specific domain through proposing a workable ontology (abbreviated as TM). A TM is a one-category ontology called a thimac (things/machines) that is used to elaborate the design and analysis of ontological presumptions. The focus of the study is on such notions as change, event, and time. Several current ontological difficulties are reviewed and remodeled in the TM. TM modeling is also contrasted with time representation in SysML. The results demonstrate that a TM is a useful tool for addressing these ontological problems.


Defeasible RDFS via Rational Closure

arXiv.org Artificial Intelligence

In the field of non-monotonic logics, the notion of Rational Closure (RC) is acknowledged as a prominent approach. In recent years, RC has gained even more popularity in the context of Description Logics (DLs), the logic underpinning the semantic web standard ontology language OWL 2, whose main ingredients are classes and roles. In this work, we show how to integrate RC within the triple language RDFS, which together with OWL2 are the two major standard semantic web ontology languages. To do so, we start from $\rho df$, which is the logic behind RDFS, and then extend it to $\rho df_\bot$, allowing to state that two entities are incompatible. Eventually, we propose defeasible $\rho df_\bot$ via a typical RC construction. The main features of our approach are: (i) unlike most other approaches that add an extra non-monotone rule layer on top of monotone RDFS, defeasible $\rho df_\bot$ remains syntactically a triple language and is a simple extension of $\rho df_\bot$ by introducing some new predicate symbols with specific semantics. In particular, any RDFS reasoner/store may handle them as ordinary terms if it does not want to take account for the extra semantics of the new predicate symbols; (ii) the defeasible $\rho df_\bot$ entailment decision procedure is build on top of the $\rho df_\bot$ entailment decision procedure, which in turn is an extension of the one for $\rho df$ via some additional inference rules favouring an potential implementation; and (iii) defeasible $\rho df_\bot$ entailment can be decided in polynomial time.


Python for Machine Learning - Classes and Objects

#artificialintelligence

This Python for Machine Learning Tutorial will help you learn the Python programming language from scratch. You'll learn about Classes and Objects in Python. Everything in this course is explained with the relevant example thus you will actually know how to implement the topics that you will learn in this course.


Intelligent requirements engineering from natural language and their chaining toward CAD models

arXiv.org Artificial Intelligence

This paper assumes that design language plays an important role in how designers design and on the creativity of designers. Designers use and develop models as an aid to thinking, a focus for discussion and decision-making and a means of evaluating the reliability of the proposals. This paper proposes an intelligent method for requirements engineering from natural language and their chaining toward CAD models. The transition from linguistic analysis to the representation of engineering requirements consists of the translation of the syntactic structure into semantic form represented by conceptual graphs. Based on the isomorphism between conceptual graphs and predicate logic, a formal language of the specification is proposed. The outcome of this language is chained and translated in Computer Aided Three-Dimensional Interactive Application (CATIA) models. The tool (EGEON: Engineering desiGn sEmantics elabOration and applicatioN) is developed to represent the semantic network of engineering requirements. A case study on the design of a car door hinge is presented to illustrates the proposed method.