Ontology Design Patterns (ODPs) have become an established and recognised practice for guaranteeing good quality ontology engineering. There are several ODP repositories where ODPs are shared as well as ontology design methodologies recommending their reuse. Performing rigorous testing is recommended as well for supporting ontology maintenance and validating the resulting resource against its motivating

Digital Libraries (DLs), especially in the Cultural Heritage domain, are rich in narratives. Every digital object in a DL tells some kind of story, regardless of the medium, the genre, or the type of the object. However, DLs do not offer services about narratives, for example it is not possible todiscover a narrative, to create one, or to compare two narratives. Certainly, DLs offer discovery functionalities

This paper presents the new developments of CRMtex, an ontological model based on CIDOC CRM, created to describe ancient texts and other semiotic features appearing on inscriptions, papyri, manuscripts and other similar supports. The model is also designed to describe in a formal way the phenomenarelated to the production, use, conservation, study and interpretation of textual entities. CRMtex was

A knowledge graph (KG) represents real-world entities and their relationships. The represented knowledge is often context-dependent, leading to the construction of contextualized KGs. The multidimensional and hierarchical nature of context invites comparison with the OLAP cube model from multidimensional data analysis. Traditional systems for online analytical processing (OLAP) employ multidimensional

Abstract This paper addresses the issue of interoperability of data generated by historical research and heritage institutions in order to make them re-usable for new research agendas according to the FAIR principles. After introducing the symogih.org project’s ontology, it proposes a description of the essential aspects of the process of historical knowledge production. It then develops an epistemological

Abstract Both keys and their generalisation, link keys, may be used to perform data interlinking, i.e. finding identical resources in different RDF datasets. However, the precise relationship between keys and link keys has not been fully determined yet. A common formal framework encompassing both keys and link keys is necessary to ensure the correctness of data interlinking tools based on them, and

Vladimir Propp’s theory Morphology of the Folktale identifies 31 invariant functions, subfunctions, and seven classes of folktale characters to describe the narrative structure of the Russian magic tale. Since it was first published in 1928, Propp’s approach has been used on various folktales of different cultural backgrounds. ProppOntology models Propp’s theory by describing narrative functions using

The process of gathering ground truth data through human annotation is a major bottleneck in the use of information extraction methods for populating the Semantic Web. Crowdsourcing-based approaches are gaining popularity in the attempt to solve the issues related to volume of data and lack of annotators. Typically these practices use inter-annotator agreement as a measure of quality. However, in many

Abstract In the last years a rapid emergence of lexical resources has evolved in the Semantic Web. Whereas most of the linguistic information is already machine-readable, we found that morphological information is mostly absent or only contained in semi-structured strings. An integration of morphemic data has not yet been undertaken due to the lack of existing domain-specific ontologies and explicit

Cooperative Intelligent Transport Systems (C-ITS) play an important role for providing the means to collect and exchange spatio-temporal data via V2X-based communication between vehicles and the infrastructure, which will become a central enabler for road safety of (semi)-autonomous vehicles. The Local Dynamic Map (LDM) is a key concept for integrating static and streamed data in a spatial context

Matching entities between datasets is a crucial step for combining multiple datasets on the semantic web. A rich literature exists on different approaches to this entity resolution problem. However, much less work has been done on how to assess the quality of such entity links once they have been generated. Evaluation methods for link quality are typically limited to either comparison with a ground

Successful exams require a balance of easy, medium, and difficult questions. Question difficulty is generally either estimated by an expert or determined after an exam is taken. The latter provides no utility for the generation of new questions and the former is expensive both in terms of time andcost. Additionally, it is not known whether expert prediction is indeed a good proxy for estimating question

The topological structure of RDF graphs inherently differs from other types of graphs, like social graphs, due to the pervasive existence of hierarchical relations (TBox), which complement transversal relations (ABox). Graph measures capture such particularities through descriptive statistics. Besides the classical set of measures established in the field of network analysis, such as size and volume

The need for recursive queries in the Semantic Web setting is becoming more and more apparent with the emergence of datasets where different pieces of information are connected by complicated patterns. This was acknowledged by the W3C committee by the inclusion of property paths in the SPARQL standard. However, as more data becomes available, it is becoming clear that property paths alone are not enough

Knowledge Graphs (KGs) are composed of structured information about a particular domain in the form of entities and relations. In addition to the structured information KGs help in facilitating interconnectivity and interoperability between different resources represented in the Linked Data Cloud.KGs have been used in a variety of applications such as entity linking, question answering, recommender

In recent years gazetteers based on semantic web technologies were discussed as an effective way to describe, formalize and standardize place data by using contextual information as a method to structure and distinguish places from each other. While research concerning semantic gazetteers with regard to historical places has pointed out the importance of enabling the creation of a global and epoch-spanning

The IoT landscape is characterized by a fragmentation of standards, platforms and technologies, often scattered among different vertical domains. To prevent the market to continue to be fragmented and power-less, a protocol-independent semantic layer can serve as enabler of interoperability among the various smart devices from different manufacturers that co-exist in a specific industry domain, but

The evolution of IoT has revolutionized industrial automation. Industrial devices at every level such as field devices, control devices, enterprise level devices etc., are connected to the Internet, where they can be accessed easily. It has significantly changed the way applications are developed on the industrial automation systems. It led to the paradigm shift where novel IoT application development

Within manufacturing processes, faults and failures may cause severe economic loss. With the vision of Industry 4.0, artificial intelligence techniques such as data mining play a crucial role in automatic fault and failure prediction. However, due to the heterogeneous nature of industrial data, data mining results normally lack both machine and human-understandable representation and interpretation

Abstract Welcome to this special issue of the Semantic Web (SWJ) journal. The special issue compiles four technical contributions that significantly advance the state-of-the-art in Semantic Web of Things for Industry 4.0 including the use of Semantic Web technologies and techniques in Industry 4.0 solutions.

The timely and efficient cooperation across sectors and borders during maritime crises is paramount for the safety of human lives. Maritime monitoring authorities are now realizing the grave importance of cross-sector and cross-border information sharing. However, this cooperation is compromised bythe diversity of existing systems and the vast volumes of heterogeneous data generated and exchanged during

The Second World War (WW2) is arguably the most devastating catastrophe of human history, a topic of great interest to not only researchers but the general public. However, data about the Second World War is heterogeneous and distributed in various organizations and countries making it hard to utilize. In order to create aggregated global views of the war, a shared ontology and data infrastructure

Actors in the Architecture, Engineering, Construction, Owner and Operation (AECOO) industry traditionally exchange building models as files. The Building Information Modelling (BIM) methodology advocates the seamless exchange of all information between related stakeholders using digital technologies. The ultimate evolution of the methodology, BIM Maturity Level 3, envisions interoperable, distributed

In this paper, we study the problem of query rewriting for disjunctive existential rules. Query rewriting is a well-known approach for query answering on knowledge bases with incomplete data. We propose a rewriting technique that uses negative constraints and conjunctive queries to remove the disjunctive components of disjunctive existential rules. This process eventually generates new non-disjunctive

The Henri Poincaré correspondence is a corpus of letters sent and received by this mathematician. The edition of this correspondence is a long-term project begun during the 1990s. Since 1999, a website is devoted to publish online this correspondence with digitized letters. In 2017, it has been decided to reforge this website using Omeka S. This content management system offers useful services but

Large scale cultural heritage datasets and computational methods for the Humanities research framework are the two pillars of Digital Humanities (DH), a research field aiming to expand Humanities studies beyond specific sources and periods to address macro-scale research questions on broad human phenomena. In this regard, the development of machine-readable semantically enriched data models based on

A lot of tabular data are being published on the Web. Semantic labeling of such data may help in their understanding and exploitation. However, many challenges need to be addressed to do this automatically. With numbers, it can be even harder due to the possible difference in measurement accuracy,rounding errors, and even the frequency of their appearance. Multiple approaches have been proposed in

RDF data has been extensively deployed describing various types of resources in a structured way. Links between data elements described by RDF models stand for the core of Semantic Web. The rising amount of structured data published in public RDF repositories, also known as Linked Open Data, elucidates the success of the global and unified dataset proposed by the vision of the Semantic Web. Nowadays

Storage and analysis of video surveillance data is a significant challenge, requiring video interpretation and event detection in the relevant context. To perform this task, the low-level features including shape, texture, and color information are extracted and represented in symbolic forms. In this work, a methodology is proposed, which extracts the salient features and properties using machine learning

Abstract RDF triplestores have become an appealing option for storing and publishing humanities data, but available technologies for querying this data have drawbacks that make them unsuitable for many applications. Gravsearch (Virtual Graph Search), a SPARQL transformer developed as part of a web-based API, is designed to support complex searches that are desirable in humanities research, while avoiding

The paper discusses a small ontology to describe the features of the execution techniques of inscriptions, based on a recent contribution discussing the classification methodologies. The modeling is done on the basis of existing recent attempts to model epigraphic documents and not on a general evaluation of existing ontologies. The ontology described is used in parallel to enrich and further structure

In the context of the Semantic Web regarded as a Web of Data, research efforts have been devoted to improving the quality of the ontologies that are used as vocabularies to enable complex services based on automated reasoning. From various surveys it emerges that many domains would require better ontologies that include non-negligible constraints for properly conveying the intended semantics. In this

Meaningful information about an RDF resource can be obtained not only by looking at its properties, but by putting it in the broader context of similar resources. Classic navigation paradigms on the Web of Data that employ a follow-your-nose strategy fail to provide such context, and put strong emphasis on first-level properties, forcing users to drill down in the graph one step at a time. We introduce

OntoAndalus aims at constituting a shared conceptualisation of the domain within a future multilingual terminological resource targeted at experts and students of Islamic archaeology. The present version of OntoAndalus is aligned with DOLCE+DnS Ultralite (DUL), an established top-level ontology forthe Semantic Web. This article describes the modelling assumptions underlying OntoAndalus, as well as

The Data Quality Vocabulary (DQV) provides a metadata model for expressing data quality. DQV was developed by the Data on the Web Best Practice (DWBP) Working Group of the World Wide Web Consortium (W3C) between 2013 and 2017. This paper aims at providing a deeper understanding of DQV. It introduces its key design principles, components, and the main discussion points that have been raised in the process

Semantics-based knowledge representations such as ontologies are found to be very useful in automatically generating meaningful factual questions. Determining the difficulty-level of these system-generated questions is helpful to effectively utilize them in various educational and professional applications. The existing approach for predicting the difficulty-level of factual questions utilizes only

The correct functioning of Semantic Web applications requires that given RDF graphs adhere to an expected shape. This shape depends on the RDF graph and the application’s supported entailments of that graph. During validation, RDF graphs are assessed against sets of constraints, and found violations help refining the RDF graphs. However, existing validation approaches cannot always explain the root

Abstract Openly shared, available, and accessible scientific resources facilitate tackling grand challenges that our society, organizations, communities and individuals are facing today. Pandemics, climate change, environmental modeling, genomics, or space exploration all create open research questions for which Artificial Intelligence – and Semantic Web in particular – have a unique potential to accelerate

The Description Logic SROIQ(D), as the logical core of the W3C standard Web Ontology Language (OWL 2), is a widely used formalism for ontologies in the life sciences. Bio-health applications including health-care and life science domains commonly have a need to represent temporal information such as medication frequency or stage-based development. Different classes of temporal phenomena may generate

Simple ontology alignments, largely studied in the literature, link a single entity of a source ontology to a single entity of a target ontology. A limitation of these alignments is their lack of expressiveness which can be overcome by complex alignments. While diverse state-of-the-art surveys mainly review the matching approaches in general, to the best of our knowledge, there is no study of the specificities

Spaces and elements in the built environment have emerged as platforms where materializations of observations and actuations promise to be very profitable. The advent of the Internet of Things (IoT) paves the way to address this challenge but the heterogeneity of the represented knowledge about these artifact systems poses a real problem. Ontologies can be considered as part of the solution to overcome

The successful deployment of the Semantic Web of Things (SWoT) requires the adaptation of the Semantic Web principles and technologies to the constraints of the IoT domain, which is the challenging research direction we address here. In this context we promote distributed reasoning approaches in IoT systems by implementing a hybrid deployment of reasoning rules relying on the complementarity of Cloud

Semantically rich descriptions of manufacturing machines, offered in a machine-interpretable code, can provide interesting benefits in Industry 4.0 scenarios. However, the lack of that type of descriptions is evident. In this paper we present the development effort made to build an ontology, calledExtruOnt, for describing a type of manufacturing machine, more precisely, a type that performs an extrusion

While workflow systems have improved the repeatability of scientific experiments, the value of the processed (intermediate) data have been overlooked so far. In this paper, we argue that the intermediate data products of workflow executions should be seen as first-class objects that need to be curated and published. Not only will this be exploited to save time and resources needed when re-executing

VocBench is an open source web platform for the collaborative development of datasets complying with Semantic Web standards. Since its public release – five years ago – as an open source platform, VocBench has attracted a growing user community consisting of public organizations, companies and independent users looking for open source solutions for maintaining their thesauri, code lists and authority

This paper presents an RDF dataset of meteorological measurements. The measurements come from one weather station at the Irstea experimental farm located in Montoldre. The measurements have been made from August 2018 until now. They have been transformed and published as Linked Open Data (LOD). Thedata schema is based on the new version of the Semantic Sensor Network ontology. This ontology version

Searching for similar documents and exploring major themes covered across groups of documents are common activities when browsing collections of scientific papers. This manual knowledge-intensive task can become less tedious and even lead to unexpected relevant findings if unsupervised algorithms are applied to help researchers. Most text mining algorithms represent documents in a common feature space

The identification of research topics and trends is an important scientometric activity, as it can help guide the direction of future research. In the Semantic Web area, initially topic and trend detection was primarily performed through qualitative, top-down style approaches, that rely on expert knowledge. More recently, data-driven, bottom-up approaches have been proposed that offer a quantitative

Quality, architecture, and process are considered the keystones of software engineering. ISO defines them in three separate standards. However, their interaction has been scarcely studied, so far. The SQuAP model (Software Quality, Architecture, Process) describes twenty-eight main factors that impact on software quality in banking systems, and each factor is described as a relation among some characteristics

Since the birth of the Semantic Web, numerous knowledge bases have appeared. The applications that exploit them rely on the quality of their data through time. In this regard, one of the main dimensions of data quality is conformance to the expected usage of the vocabulary. However, the vocabularyusage (i.e., how classes and properties are actually populated) can vary from one base to another. Moreover

Although the link prediction problem, where missing relation assertions are predicted, has been widely researched, error detection did not receive as much attention. In this paper, we investigate the problem of error detection in relation assertions of knowledge graphs, and we propose an error detection method which relies on path and type features used by a classifier for every relation in the graph

Preference representation and reasoning play a central role in supporting users with complex and multi-factorial decision processes. In fact, user tastes can be used to filter information and data in a personalized way, thus maximizing their expected utility. Over the years, many frameworks and languages have been proposed to deal with user preferences. Among them, one of the most prominent formalism

With the development of the Semantic Web, a lot of new structured data has become available on the Web in the form of knowledge bases (KBs). Making this valuable data accessible and usable for end-users is one of the main goals of question answering (QA) over KBs. Most current QA systems query oneKB, in one language (namely English). The existing approaches are not designed to be easily adaptable to

RDF generally follows the open-world assumption: information is incomplete by default. Consequently, SPARQL queries cannot retrieve with certainty complete answers, and even worse, when they involve negation, it is unclear whether they produce sound answers. Nevertheless, there is hope to lift thislimitation. On many specific topics (e.g., children of Trump, Apollo 11 crew, EU founders), RDF data sources

Domain-independent information systems like ontology editors provide only limited usability for non-experts when domain-specific linked data need to be created. On the contrary, domain-specific applications require adequate architecture for data authoring and validation, typically using the object-oriented paradigm. So far, several software libraries mapping the RDF model (representing linked data)

Data Analytics Solution (DAS) engineering often involves multiple tasks from data exploration to result presentation which are applied in various contexts and on different datasets. Semantic modeling based on the open world assumption supports flexible modeling of linked knowledge. The objective ofthis paper is to review existing techniques that leverage semantic web technologies to tackle challenges

A central problem in the context of the Web of Data as well as in data integration in general is to identify entities in different data sources that describe the same real-world object. There exists a large body of research on entity resolution. Interestingly, most of the existing research focuseson entity resolution on dense data, meaning data that does not contain too many missing values. This paper

Knowledge graph, as a backbone of many information systems, has been created to organize the rapidly growing knowledge in a semantical and visualized manner. Symbolic reasoning and statistical reasoning are current mainstream techniques that play important roles in knowledge completion, automatic schema constructing, complex question answering, explanation of AI. However, both of them have their merits

Modern life is increasingly made more comfortable, efficient, and sustainable by the smart systems that surround us: smart buildings monitor and adjust temperature levels to achieve occupant comfort while optimizing energy consumption; smart energy grids reconfigure dynamically to make the best use of ad-hoc energy produced by a host of distributed energy producers; smart factories can be reconfigured

When you meet a delivery robot in a narrow street it stops to let you pass. It was built to give you precedence. What happens if you run into a robot that was not trained by or for humans? The existence in our environment of robots which do not abide by human behavioral rules and social systems might sound odd, but is a case we may encounter in the near future. In this paper, self-taught robots are