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We describe the development and envisioned use case applications of a comprehensive insider threat ontology—“Sociotechnical and Organizational Factors for Insider Threat” (SOFIT)—that comprises more than 300 indicators of technical, behavioral, and organizational factors. Requirements, design, and engineering development for the Web Ontology Language (OWL) implementation of the SOFIT knowledge base are reviewed; additional relationships among constructs are defined that extend the representation beyond a simple taxonomic hierarchy and that enable inferences for qualitative and quantitative threat assessment. We show how queries may be constructed to support these inferences and threat assessments. Several major application concepts are reviewed to show how the ontology may be used by the insider threat research and operational communities. To this end, the SOFIT knowledge base may be shared with stakeholders to advance research and practice for proactive insider threat mitigation.

To date, widely implemented and full-featured query languages for building models in their native exchange formats do not exist. While interesting proposals exist for querying Industry Foundation Classes (IFC) models, their functionality is often incomplete and their semantics not precisely defined. With the introduction of the ifcOWL ontology as an equivalent to the IFC schema in the Web Ontology Language (OWL), an option to represent such models in RDF (Resource Description Framework, a general information modeling method) is provided, and such models can be queried using SPARQL (SPARQL Protocol and RDF Query Language). The size of data sets in complex building projects, however, renders the use of clear-text encoded RDF infeasible in many cases. A SPARQL implementation, compatible with ifcOWL, is proposed, directly atop a standardized binary serialization format for IFC building models. This novel format is the binary equivalent of traditional IFC serialization formats but with more compact storage and less overhead than the graph serialization in RDF. The format is based on ISO 10303-26 and relies on an open standard for organizing large amounts of data: Hierarchical Data Format version 5 (HDF5). Due to hierarchical partitioning and fixed-length records, only small subsets of the data are read to answer queries, improving efficiency. A prototypical implementation of the query engine is provided in the Python programming language. In several realistic use cases, the proposed system performs equivalent to or better than the state of the art in SPARQL querying on building models. For large datasets, the proposed storage format results in files that are 2–3 times smaller than the current, most concise, RDF databases while offering a platform-neutral, containerized exchange file.

Efforts have been made in the Semantic Web to combine rules with ontologies. One result of these efforts is the development of the Semantic Web Rule Language (SWRL) which is designed to integrate closely with the Web Ontology Language (OWL). Both SWRL and OWL adhere to the open-world semantics of first-order logic, and thus are not suitable for modelling integrity constraints in applications where complete knowledge about some parts of the domain can be assumed. In this paper, we investigate this problem and present a practical approach to modelling and validating constraints in the Semantic Web. Building on existing work, we show that by employing a constraint semantics for both OWL and SWRL, we can model common constraints as OWL axioms or SWRL rules. We also show that by using a query reduction technique, we can validate constraints using existing OWL/SWRL reasoners. Finally, we demonstrate the usefulness of our approach via a real-world case study.

This paper introduces a novel, semantics-informed geologic mapping process, whose application domain is the production of a synthetic geologic map of a large administrative region. A number of approaches concerning the expression of geologic knowledge through UML schemata and ontologies have been around for more than a decade. These approaches have yielded resources that concern specific domains, such as, e.g., lithology. We develop a conceptual model that aims at building a digital encoding of several domains of geologic knowledge, in order to support the interoperability of the sources. We apply the devised terminological base to the classification of the elements of a geologic map of the Italian Western Alps and northern Apennines (Piemonte region). The digitally encoded knowledge base is a merged set of ontologies, called OntoGeonous. The encoding process identifies the objects of the semantic encoding, the geologic units, gathers the relevant information about such objects from authoritative resources, such as GeoSciML (giving priority to the application schemata reported in the INSPIRE Encoding Cookbook), and expresses the statements by means of axioms encoded in the Web Ontology Language (OWL). To support interoperability, OntoGeonous interlinks the general concepts by referring to the upper part level of ontology SWEET (developed by NASA), and imports knowledge that is already encoded in ontological format (e.g., ontology Simple Lithology). Machine-readable knowledge allows for consistency checking and for classification of the geological map data through algorithms of automatic reasoning.

To achieve efficient development of high-quality product, manufacturing constraints must be fully taken into account at the early design stage. However, designers lack in-depth knowledge of manufacturing and production. Many time-consuming iterations of design changes are required between designers and manufacturing engineers. In order to minimize this knowledge gap, this paper presents an ontology-based product design framework for manufacturability verification and knowledge reuse to support the sharing and reuse of design and manufacturing knowledge. It aims at providing advices and feedback of restraints of manufacturing processes to the designers during the design process. The proposed framework consists of three major layers which include a foundation layer, a domain layer, and an instance layer. We use the Web Ontology Language (OWL), a standard of ontology representation language, to formalize the foundation layer. It contains the core product model and the standard ISO 10303 AP224 application protocol. The domain layer comprises extensional concepts and relationships for design and manufacturing integration and a rule base for manufacturability verification, which is represented in Semantic Web Rule Language (SWRL). In the instance layer, an inference engine is developed based on ontology and rule inference. It provides recommendations of manufacturability. Two case studies are provided as application examples to demonstrate the effectiveness of the framework.

In this paper we introduce Eddy, a new open-source tool for the graphical editing of OWL~2 ontologies. Eddy is specifically designed for creating ontologies in Graphol, a completely visual ontology language that is equivalent to OWL~2. Thus, in Eddy ontologies are easily drawn as diagrams, rather than written as sets of formulas, as commonly happens in popular ontology design and engineering environments. This makes Eddy particularly suited for usage by people who are more familiar with diagramatic languages for conceptual modeling rather than with typical ontology formalisms, as is often required in non-academic and industrial contexts. Eddy provides intuitive functionalities for specifying Graphol diagrams, guarantees their syntactic correctness, and allows for exporting them in standard OWL 2 syntax. A user evaluation study we conducted shows that Eddy is perceived as an easy and intuitive tool for ontology specification.

Autonomous systems consist of agents that have access to interpretable information allowing them to make intelligent decisions. This requires the systems to have a good semantic knowledge base. A good semantic knowledge repository has to be backed by a well-defined domain ontology. For the sake of decidability, ontology languages do not provide the required expressiveness. Rules present an efficient support thereby enabling even better decision making. Their complexity and their exponentially growing number imply the need for an automatic management. In this paper, we introduce a new method for the automatic dependency extraction among rule bases associated to ontologies. This is founded on a novel technique of dependency extraction. A prototype of our proposal was implemented and applied on two different rule bases associated to ontologies from different domains. Our results succeeded in increasing the number of the extracted dependency relationships.

Semantic technologies have emerged as a prominent research area within Big Earth Data. These technologies have provided significant benefits for data discovery and integration. Yet, the formality of the Semantic Web, in languages such as the Web Ontology Language (OWL), does not always integrate well with the numerical, statistical, and geometric methods of the geosciences. Two prominent challenges in this area are how to semantically model individual measurements and what to do when geoscience needs are not addressed by languages such as OWL. This has led to a fragmented Big Earth Data community with either no solution or incompatible semantic solutions. We use an oceanographic example to highlight the limitations and challenges surrounding the semantic encoding of observations and the use of semantics during analysis. We then present potential solutions to each challenge showing that a full end-to-end application of semantic technologies is not only feasible, but beneficial to Big Earth Data.

The article describes the process of creating a Finnish language FrameNet or FinnFN, based on the original English language FrameNet hosted at the International Computer Science Institute in Berkeley, California. We outline the goals and results relating to the FinnFN project and especially to the creation of the FinnFrame corpus. The main aim of the project was to test the universal applicability of frame semantics by annotating real Finnish using the same frames and annotation conventions as in the original Berkeley FrameNet project. From Finnish newspaper corpora, 40,721 sentences were automatically retrieved and manually annotated as example sentences evoking certain frames. This became the FinnFrame corpus. Applying the Berkeley FrameNet annotation conventions to the Finnish language required some modifications due to Finnish morphology, and a convention for annotating individual morphemes within words was introduced for phenomena such as compounding, comparatives and case endings. Various questions about cultural salience across the two languages arose during the project, but problematic situations occurred only in a few examples, which we also discuss in the article. The article shows that, barring a few minor instances, the universality hypothesis of frames is largely confirmed for languages as different as Finnish and English.

International audience; Objective: Ontologies are widely used in the biomedical domain. While many tools exist for the edition, alignment or evaluation of ontologies, few solutions have been proposed for ontology programming interface, i.e. for accessing and modifying an ontology within a programming language. Existing query languages (such as SPARQL) and APIs (such as OWLAPI) are not as easy-to-use as object programming languages are. Moreover, they provide few solutions to difficulties encountered with biomedical ontologies. Our objective was to design a tool for accessing easily the entities of an OWL ontology, with high-level constructs helping with biomedical ontologies. Methods: From our experience on medical ontologies, we identified two difficulties: (1) many entities are represented by classes (rather than individuals), but the existing tools do not permit manipulating classes as easily as individuals, (2) ontologies rely on the open-world assumption, whereas the medical reasoning must consider only evidence-based medical knowledge as true. We designed a Python module for ontology-oriented programming. It allows access to the entities of an OWL ontology as if they were objects in the programming language. We propose a simple high-level syntax for managing classes and the associated " role-filler " constraints. We also propose an algorithm for performing local closed world reasoning in simple situations. Results: We developed Owlready, a Python module for a high-level access to OWL ontologies. The paper describes the architecture and the syntax of the module version 2. It details how we integrated the OWL ontology model with the Python object model. The paper provides examples based on Gene Ontology (GO). We also demonstrate the interest of Owlready in a use case focused on the automatic comparison of the contraindications of several drugs. This use case illustrates the use of the specific syntax proposed for manipulating classes and for performing local closed world reasoning. Conclusion: Owlready has been successfully used in a medical research project. It has been published as Open-Source software and then used by many other researchers. Future developments will focus on the support of vagueness and additional non-monotonic reasoning feature, and automatic dialog box generation.

Cloud computing is increasingly used so that the number of providers offering services is rapidly increasing. Thus, a need to organize these services and to express relations between them arises. To answer this need, ontologies are used. To query these services, the authors use query languages, such as SPARQL, that return two types of results: either a list of required services, or an empty list. However, the second result is not desired. In fact, if the required service is not available, users want to be offered by a list of similar ones instead of the empty list. It is in this sense that the similarity, which provides more results ranked according to their utilities, is used. This paper first presents the Cloud ontology on which the authors' work is based. It then defines and compares between two Cloud service discovery methods which are: the discovery based on query languages and the discovery based on similarity. To show the efficiency of the search based on similarity, the authors propose a search engine that allows the users to query services using a simple to use interface.

In the context of the Semantic Web, fuzzy extensions to OWL (the W3C standard ontology language) and Description Logics (DLs, the logical foundation of OWL) have been extensively investigated, and there are many real fuzzy DL ontology knowledge bases. Therefore, how to store fuzzy DL ontology knowledge bases has become an important issue. In this paper, we propose an approach and implement a tool for storing fuzzy DL ontology knowledge bases in fuzzy relational databases. Our chosen formalism is a fuzzy extension of the very expressive DL SHOIN(D), which is the main logical foundation of the standard ontology language OWL, so that our storage approach can store not only fuzzy DL-knowledge bases but also fuzzy ontology knowledge bases. Firstly, we give a formal definition of fuzzy DL-knowledge bases. In the definition, we consider the constructors of both fuzzy SHOIN(D) DL and fuzzy OWL ontology and add some common fuzzy datatypes (e.g., trapezoidal values, interval values, approximate values, and labels) into the knowledge bases. On this basis, we propose an approach which can store fuzzy DL-knowledge bases in fuzzy relational databases, and provide an example to well explain the approach. The correctness and quality of the storage approach are proved and analyzed. Furthermore, following the proposed approach, we implemented a prototype tool, which can automatically store fuzzy DL-knowledge bases. Finally, we make a discussion about the query problem and make a comparison with the existing works.

Definitions of ‘mixed’ or ‘intertwined’ languages derive almost entirely from studies of languages that combine elements from genetically unrelated sources. The Mayan language Tojol-ab’al displays a mixture of linguistic features from two related Mayan languages, Chuj and Tseltal. The systematic similarities found in related languages not only make it methodologically difficult to identify the source of specific linguistic features but also mean that inherited similarity can alter the processes and outcomes of language mixing in ways that parallel observed patterns of code-switching between related languages. Tojol-ab’al, therefore, arguably represents a distinct type of mixed language, one that may only result from mixture involving related languages.

In recent years, business process modeling has increasingly drawn the attention of enterprises. As a result of the wide use of business processes, redundancy problems have arisen and researchers introduced the variability management, in order to enhance the business process reuse. The most approach used in this context is the Configurable Process Model solution, which consists in representing the variable and the fixed parts together in a unique model. Due to the increasing number of variants, the configurable models become complex and incomprehensible, and their quality is therefore impacted. Most of research work is limited to the syntactic quality of process variants. The approach presented in this paper aims at providing a novel method towards syntactic verification and semantic validation of configurable process models based on ontology languages. We define validation rules for assessing the quality of configurable process models. An example in the e-healthcare domain illustrates the main steps of our approach.

For the subject-oriented (business) process modeling language PASS (Parallel Activity Specification Scheme) there are currently two kinds of formal specifications, one for the execution semantics and one for the digital exchange of model descriptions. One uses the Abstract State Machine (ASM) modeling concept, the other is created using the Web Ontology Language (OWL).

SoftwareX 12, 100571 (2020). doi:10.1016/j.softx.2020.100571, Published by Elsevier, Amsterdam [u.a.]

Knowledge bases (KBs) are not static entities: new information constantly appears and some of the previous knowledge becomes obsolete. In order to reflect this evolution of knowledge, KBs should be expanded with the new knowledge and contracted from the obsolete one. This problem is well-studied for propositional but much less for first-order KBs. In this work we investigate knowledge expansion and contraction for KBs expressed in DL-Lite, a family of description logics (DLs) that underlie the tractable fragment OWL 2 QL of the Web Ontology Language OWL 2. We start with a novel knowledge evolution framework and natural postulates that evolution should respect, and compare our postulates to the well-established AGM postulates. We then review well-known model and formula-based approaches for expansion and contraction for propositional theories and show how they can be adapted to the case of DL-Lite. In particular, we show intrinsic limitations of model-based approaches: besides the fact that some of them do not respect the postulates we have established, they ignore the structural properties of KBs. This leads to undesired properties of evolution results: evolution of DL-Lite KBs cannot be captured in DL-Lite. Moreover, we show that well-known formula-based approaches are also not appropriate for DL-Lite expansion and contraction: they either have a high complexity of computation, or they produce logical theories that cannot be expressed in DL-Lite. Thus, we propose a novel formula-based approach that respects our principles and for which evolution is expressible in DL-Lite. For this approach we also propose polynomial time deterministic algorithms to compute evolution of DL-Lite KBs when evolution affects only factual data.

© 2017, Springer International Publishing AG. Context information plays a crucial role in dynamically changing environments and the different types of contextual conditions bring new challenges to access control. This information mostly can be derived from the crisp sets. For example, we can utilize a crisp set to derive a patient and nurse are co-located in the general ward of the hospital or not. Some of the context information characterizations cannot be made using crisp sets, however, they are equally important in order to make access control decisions. For example, a patient’s current health status is “critical” or “high critical” which are imprecise fuzzy facts, whereas “95% level of maximum blood pressure allowed” is precise. Thus, there is a growing need for integrating these kinds of fuzzy and other conditions to appropriately control context-specific access to information resources at different granularity levels. Towards this goal, this paper introduces an approach to Context-Aware Access Control using Fuzzy logic (FCAAC) for information resources. It includes a formal context model to represent the fuzzy and other contextual conditions. It also includes a formal policy model to specify the policies by utilizing these conditions. Using our formal approach, we combine the fuzzy model with an ontology-based approach that captures such contextual conditions and incorporates them into the policies, utilizing the ontology languages and the fuzzy logic-based reasoning. We justify the feasibility of our approach by demonstrating the practicality through a prototype implementation and a healthcare case study, and also evaluating the performance in terms of response time.

In this chapter, we provide a detailed primer on the second version of the Web Ontology Language (OWL 2) standard. We first motivate the need for such a standard, discussing the role and importance of ontologies on the Web. We then describe how ontology languages, which themselves can be formally defined through model theory, can subsequently be used to formally define ontologies. Thereafter we discuss the OWL vocabulary used to define the semantics of classes, properties, individuals, and datatypes within ontologies. We cover some of the main reasoning tasks for ontologies and the applications in which they are used. We discuss how these core reasoning tasks are undecidable for the full OWL (2) language and outline the sub-languages (aka. profiles) proposed by the standard that allow for more efficient reasoning procedures. We conclude by reflecting on the importance of having expressive ontologies on the Web of Data, and discuss open challenges.

In this paper, we propose a new mapping technique from the OMG’s UML modeling language into the Web Ontology Language (OWL) to serve the Semantic Web. UML (Unified Modeling Language) is widely accepted and used as a standardized modeling language in Object-Oriented Analysis (OOA) and Design (OOD) approach by domain experts to model real-world objects in software development. On the other hand, the conceptualization, which is represented in OWL, is designed to process the content of information rather than just present the information. Therefore, the matter of migrating UML to OWL is becoming an energetic research domain. OWL (Web Ontology Language) is a Semantic Web language designed for defining ontologies on the Web. An ontology is a formal specification naming and definition of shared data. This technique describes how to map UML Models into OWL and allows us to keep semantic of UML sequence diagrams such as messages, the sequence of messages, guard invariant, etc. to make data of UML sequence diagrams machine-readable.

Many organizations maintain knowledge graphs that are organized according to ontologies. However, these ontologies are implemented in languages (e.g. OWL) that are difficult to understand by users who are not familiar with knowledge representation techniques. In particular, this affects web developers who want to develop ontology-based applications but may find challenging accessing ontology-based data in knowledge graphs through SPARQL queries. To address this problem, we propose an accessible layer for ontology-based knowledge graphs through REST APIs. We define a mapping specification between the Web Ontology Language (OWL) and the OpenAPI Specification (OAS) to provide ontology-based API definitions in a language well-known to web developers. Our mapping specification identifies key similarities between OWL and OAS and provides implementation guidelines and examples. We also developed a reference mapping implementation that automatically transforms OWL ontologies into OpenAPI specifications in a matter of seconds.

A second opinion about cancer stage is crucial when clinicians assess patient treatment progress. Staging is a process that takes into account description, location, characteristics, and possible metastasis of tumors in a patient. It should follow standards, such as the TNM Classification of Malignant Tumors. However, in clinical practice, the implementation of this process can be tedious and error prone. In order to alleviate these problems, we intend to assist radiologists by providing a second opinion in the evaluation of cancer stage. For doing this, we developed a TNM classifier based on semantic annotations, made by radiologists, using the ePAD tool. It transforms the annotations (stored using the AIM format), using axioms and rules, into AIM4-O ontology instances. From then, it automatically calculates the liver TNM cancer stage. The AIM4-O ontology was developed, as part of this work, to represent annotations in the Web Ontology Language (OWL). A dataset of 51 liver radiology reports with staging data, from NCI’s Genomic Data Commons (GDC), were used to evaluate our classifier. When compared with the stages attributed by physicians, the classifier stages had a precision of 85.7% and recall of 81.0%. In addition, 3 radiologists from 2 different institutions manually reviewed a random sample of 4 of the 51 records and agreed with the tool staging. AIM4-O was also evaluated with good results. Our classifier can be integrated into AIM aware imaging tools, such as ePAD, to offer a second opinion about staging as part of the cancer treatment workflow.

Along with the rapid development of remote sensing satellites and sensor network technology, vast amounts of remote sensing imagery and in situ observations have been accumulated. Further, various researchers and agencies have released a variety of thematic image products. These heterogeneous observations are therefore difficult to utilize comprehensively. In this study, an ontology-based framework for integrating remote sensing imagery, image products, and in situ observations was developed. It was extended based on the Semantic Sensor Network (SSN) ontology in the Web Ontology Language (OWL). The detailed process of ontology construction and rule establishment was demonstrated. Combined with some actual remote sensing imagery, image products, and in situ observations, semantic queries based on DL Query and SPARQL were conducted to establish the rationality and feasibility of the ontology and framework.

Ontologies must provide the entities, concepts, and relations required by the domain being represented. The domain of interest in this paper is the biochemistry experimental procedure. These procedures are composed of procedure steps which can be represented as sequences. Sequences are composed of totally ordered, partially ordered, and alternative subsequences. The ontology language being used is OWL-DL. OWL-DL was adopted due to its well-balanced flexibility among expressiveness (e.g., class description, cardinality restriction, etc.), completeness, and decidability. In the biochemistry procedure-oriented ontology presented here, subsequences are represented with two relations, directlyFollows and directlyPrecedes that are used to represent sequences. Alternative subsequences can be generated by composing a oneOf function in OWL-DL. Each alternative subsequence is referred to as optionalStepOf in this work. Two biochemistry procedures, Alkaline Agarose Gel Electrophoresis and Southern Blotting, are used to demonstrate the generality of this procedural ontology. Portions of these procedures are described in detail. SPARQL queries show the versatility of the ontology.

We present a new ontology language Pini and the PiniTree ontology editor supporting it. Despite Pini language bearing lot of similarities with RDF, UML class diagrams, Property Graphs and their frontends like Google Knowledge Graph and Protege, it is a more expressive language enabling FrameNet-style natural language annotation for Atomised journalism use case.

This study aims to improve the interoperability between models of geospatial information from the applications domains of Geographic Information Systems (GIS), Intelligent Transport Systems (ITS) and Building Information Models (BIM). A state-of-the-art analysis showed that the Unified Modelling Language (UML) and Model-Driven Architecture (MDA) are used for modelling information in a geospatial context in all three domains, but with different approaches and levels of formality. A structure of formal UML profiles for modelling of geospatial information in GIS, ITS and BIM is suggested and tested for implementation. The Core Geospatial Profile (GCP) and general encoding profiles for the Geography Markup Language (GML) and the Web Ontology Language (OWL) are based on adapted concepts from ISO/TC 211 standards. Community specific profiles for conceptual models and encodings are based on UML profiles and the use of UML for specific information models in the three application domains. The studies and related research showed that the structure of UML profiles could be implemented and used for information modelling in the UML software Enterprise Architect and that existing profiles and information models could be adapted into the framework. Integration of information models in a common approach based on MDA and UML establishes a fundament for improved interoperability through a shared understanding of the digital representation of the real world. © Author(s) 2020. This work is distributed under the Creative Commons Attribution 4.0 License.

Notwithstanding that the Semantic Web improves the information interoperability, however, the spatio-temporal knowledge representation, the description of relatively complex events – like those that can involve within smart contracts – security, reliability and trust are still difficult to achieve. In addition, Blockchain technology promotes information sharing and is supplying secure communication architecture for distributed systems. Therefore, intertwine an ontology language with Blockchain allows information interoperability and provides message-integrity checking and resolve the trust in all kinds of applications (IoT, robotic, industry 4.0, health record, etc.). In fact, ontologies facilitate the understanding and sharing of intrinsic components –smart contracts, transaction, knowledge- and relationship within a Blockchain. The main goal of this approach is to promote common data exchange, the design of decentralized, and the chronological semantic relationships on the Blockchain and Ethereum Smart Contracts making use of the narrative semantic representation foundations allowing therefore the web to survive and Blockchain technology to prosper.

For the issue that it was difficult to describe and express the dynamic, multi-dimensional and time-varying characteristics of ocean flow field by existing ontology language, by introducing spatio-temporal ontology, the paper constructed a three-tier architecture which was composed of ocean flow field concept ontology, spatio-temporal object ontology and spatio-temporal process ontology. And based on this, the paper proposed a spatio-temporal ontology model for the dynamic variability characteristics of ocean flow field, and realized the semantic expression of ocean flow domain knowledge. Based on the semantic analysis of ocean flow field spatial primitives and temporal primitives, the paper established the criteria for determining the topological relationship, the sequential relationship, the distance relationship and the temporal relationship between ocean flow field objects. In order to give the formal expression of the spatial-temporal ontology for ocean flow field, based on Web Ontology Language (OWL) syntactic rules, the paper constructed spatio-temporal predicates and terms, extended OWL spatio-temporal modeling key nodes, and formed Ocean Current Spatio-temporal Web Ontology Language (OST OWL). And taking the cold vortex as an example, the spatio-temporal process has modeled. It showed that OST OWL can express ocean flow field more effectively.

The aim of semantic web is to provide meaning to data shared by a network, therefore making it readable by humans and computer applications. The objective of this is to give the information and services a well-defined meaning by tagging web content with machine processable descriptions. Within the semantic web there are annotations, which relate data and classes offering a structured data. In addition, an ontology is an essential part of the semantic web, because it provides a vocabulary of terms and includes properties between concepts. There are several proposals over semantic annotations included in primary studies, but it is necessary to condense them in a secondary study, hence this paper presents a systematic literature review about the composition of microservices through the use of semantic annotations. This allows developers to determine which techniques are the most used in the semantic web. In order to perform this secondary study, the Kitchenham’s methodology was applied. After its application, 68 articles were firstly obtained, once the inclusion and exclusion criteria was applied, only 39 studies were selected, which include automatic and manual review.

This short course is an introduction to symbolic artificial intelligence (AI) applied to multimedia. We assume no previous knowledge of AI and only basic knowledge of multimedia. The short course is divided into three parts. In the first part, we present general notions of AI and discuss the challenges involved in the construction of intelligent multimedia applications, that is, applications enriched with the capacity for semantic query, reasoning, and recommendation. In the second part, we detail the main technologies for symbolic AI and discuss their application to multimedia. In particular, we present the ontology languages RDF(S) and OWL, the description logics (DLs) which give these languages a formal basis, the SPARQL query language, and the vocabularies and extensions that allow us to apply these technologies to multimedia data. In the third and last part, we discuss the Hyperknowledge model: a hybrid model for the representation of knowledge and content. The Hyperknowledge model extends the NCM model, a classic hypermedia model, with the notion of semantic links, which allow for the integrated representation of multimedia content together with its semantic description.

In cloud robotics environments, software components play important roles by acquiring data from heterogeneous devices and then performing context-aware computing with the help of knowledge bases organized by the data. However, there are numerous tasks that must be performed to create such components, their corresponding database schemas, services, and repositories, and these tasks can be burdensome for developers. In this paper, a framework for constructing a data acquisition system with integrated robotic technology components and modern web-based technologies is presented. Our proposed framework enables developers to construct a robot environment with data acquisition functionalities by defining scenarios in an ontology language. The framework is realized in such a way that allows it to automatically generate the required software components and their corresponding repositories, which are deployed on the cloud. A case study showcasing the proposed framework is also demonstrated.

Access control is a security technique that specifies which users can access particular resources in a computing environment. Over the years, numerous access control models have been developed to address various aspects of computer security. In this paper, we focus on a modern approach, attribute-based access control (ABAC), which has been proposed in order to overcome limitations of traditional models: discretionary access control (DAC), mandatory access control (MAC) and role-based access control (RBAC). The work on integrating access control mechanisms in semantic web technologies is developing into two directions: (1) to use semantic web technologies for modeling and analyzing access control policies and (2) to protect knowledge encoded in an ontology. In this paper we focus on the first issue and investigate how ABAC can be integrated into ontology languages.

Background Ontologies are invaluable in the life sciences, but building and maintaining ontologies often requires a challenging number of distinct tasks such as running automated reasoners and quality control checks, extracting dependencies and application-specific subsets, generating standard reports, and generating release files in multiple formats. Similar to more general software development, automation is the key to executing and managing these tasks effectively and to releasing more robust products in standard forms. For ontologies using the Web Ontology Language (OWL), the OWL API Java library is the foundation for a range of software tools, including the Protégé ontology editor. In the Open Biological and Biomedical Ontologies (OBO) community, we recognized the need to package a wide range of low-level OWL API functionality into a library of common higher-level operations and to make those operations available as a command-line tool. Results ROBOT (a recursive acronym for “ROBOT is an OBO Tool”) is an open source library and command-line tool for automating ontology development tasks. The library can be called from any programming language that runs on the Java Virtual Machine (JVM). Most usage is through the command-line tool, which runs on macOS, Linux, and Windows. ROBOT provides ontology processing commands for a variety of tasks, including commands for converting formats, running a reasoner, creating import modules, running reports, and various other tasks. These commands can be combined into larger workflows using a separate task execution system such as GNU Make, and workflows can be automatically executed within continuous integration systems. Conclusions ROBOT supports automation of a wide range of ontology development tasks, focusing on OBO conventions. It packages common high-level ontology development functionality into a convenient library, and makes it easy to configure, combine, and execute individual tasks in comprehensive, automated workflows. This helps ontology developers to efficiently create, maintain, and release high-quality ontologies, so that they can spend more time focusing on development tasks. It also helps guarantee that released ontologies are free of certain types of logical errors and conform to standard quality control checks, increasing the overall robustness and efficiency of the ontology development lifecycle.

We present WebProt\'eg\'e, a tool to develop ontologies represented in the Web Ontology Language (OWL). WebProt\'eg\'e is a cloud-based application that allows users to collaboratively edit OWL ontologies, and it is available for use at https://webprotege.stanford.edu. WebProt\'ege\'e currently hosts more than 68,000 OWL ontology projects and has over 50,000 user accounts. In this paper, we detail the main new features of the latest version of WebProt\'eg\'e.

Geometric structures of objects in traditional geometric feature modelling are obtained via several numerical calculations; however, some geometric information is lost when objects are modelled in other dimensional spaces. The study proposes the method of simplicial complexes for the representation of topological structures of plant cell shapes and their 3D formalization using the Ontology Language. The proposed method provides description and representation of the topology of cell shapes according to the local and global characteristics of computer graphics and enables to obtain semantic information about their complex relations.

Scrap steel reverse supply chain service system is a typical complex system. The realization of the service activities involves a large number of service resources. And there are multiple relationships between atomic service activities and service resources. To realize the search matching between complex service resources and service activity demand in scrap steel reverse supply chain service, the modelling method of service resource information in scrap steel reverse supply chain based on ontology is proposed. After analysing the classification method of service resource, the ontology information model of service resources and service activities is constructed. Then the search matching between service demander and service resource provider is transformed into the mapping between service resource ontology and service activity ontology to solve. Finally, the ontology model of specific instance is established, and the Semantic Web ontology language OWL is used. The model is proved to be correct and feasible by describing the instance service resource ontology and service activity ontology.

Supporters of languages planned for international communication, like Esperanto, often claim that these languages are less complex and therefore easy to learn as compared to natural languages. To what extent does this claim have empirical support? In this contribution, planned languages will be presented from the perspective of learnability. In particular, the question of language complexity will be addressed. Almost all planned languages show a high degree of morphological regularity, obtained by a drastic reduction of allomorphy and suppletion. While these morphological traits can help learners acquire the basics of the planned language more easily as compared to standard natural languages, other factors should be taken into account in order to assess the learnability of these languages, in particular their sociolinguistic status.

The focus of this paper is on an integrated approach for HVAC modeling (semantic and physical), optimization, and control. It utilizes the Building Control Virtual Test Bed (BCVTB) platform to integrate ontologies along with rule sets into Model Predictive Control (MPC) routines and Modelica-based simulations. The ontologies represent the data in the form of semantic models of the domain. They include concepts and the relationships between them, i.e., mechanical equipment, zones, and sensors. While the MPC ensures optimized physical control, the ontologies and rule sets are responsible for data-driven and inference-based semantic control. The Web Ontology Language (OWL) is used to describe the ontologies, and Jena API was used as the framework to create the ontologies and define the rule sets.

In this article, a computer tool for processing African languages has been designed. It is intended to be a contribution to the automatic processing of African languages. The current study is focused on West African languages where five main languages from Niger, two from Mali and one from Burkina Faso are considered. After a brief review of African languages processing, we designed a tool which uses minimum resources and operates essentially on a dictionary and the characteristics of the language alphabet. The dictionary is represented using a trie data structure. For the sake of application, the designed tool operates as a spell checker. To detect and correct spelling errors, the edit distance and the specificities of the language are used. Although they do not have processing tools, it was shown that existing tools for computerized languages can be adapted to African languages efficiently. To extend the designed tool to any African language, we only need to provide an appropriate dictionary and alphabet.

Representing the semantics of the interaction of two or more tolerances (i.e. composite tolerance) explicitly to make them computer-understandable is currently a challenging task in computer-aided tolerancing (CAT). We have proposed a description logic (DL) ontology based approach to complete this task recently. In this paper, the representation of the semantics of the composite positional tolerance (CPT) for patterns of holes (POHs) is used as an example to illustrate the proposed approach. This representation mainly includes: representing the structure knowledge of the CPT for POHs in DL terminological axioms; expressing the constraint knowledge with Horn rules; and describing the individual knowledge using DL assertional axioms. By implementing the representation with the web ontology language (OWL) and the semantic web rule language (SWRL), a CPT ontology is developed. This ontology has explicitly computer-understandable semantics due to the logic-based semantics of OWL and SWRL. As is illustrated by an engineering example, such semantics makes it possible to automatically check the consistency, reason out the new knowledge, and implement the semantic interoperability of CPT information. Benefiting from this, the ontology provides a semantic enrichment model for the CPT information extracted from CAD/CAM systems.

In this paper we exploit Answer Set Programming (ASP) for reasoning in a rational extension SROEL-R-T of the low complexity description logic SROEL, which underlies the OWL EL ontology language. In the extended language, a typicality operator T is allowed to define concepts T(C) (typical C's) under a rational semantics. It has been proven that instance checking under rational entailment has a polynomial complexity. To strengthen rational entailment, in this paper we consider a minimal model semantics. We show that, for arbitrary SROEL-R-T knowledge bases, instance checking under minimal entailment is \Pi^P_2-complete. Relying on a Small Model result, where models correspond to answer sets of a suitable ASP encoding, we exploit Answer Set Preferences (and, in particular, the asprin framework) for reasoning under minimal entailment. The paper is under consideration for acceptance in Theory and Practice of Logic Programming., Comment: Paper presented at the 32nd International Conference on Logic Programming (ICLP 2016), New York City, USA, 16-21 October 2016

A (factor-)reference in a word is a special symbol that refers to another factor in the same word; a reference is dereferenced by substituting it with the referenced factor. We introduce and investigate the class ref-REG of all languages that can be obtained by taking a regular language R and then dereferencing all possible references in the words of R. We show that ref-REG coincides with the class of languages defined by regular expressions as they exist in modern programming languages like Perl, Python, Java, etc. (often called REGEX languages).