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  • A benchmark for end-user structured data exploration and search user interfaces
    J. Web Semant. (IF 2.238) Pub Date : 2020-08-28
    Roberto García, Rosa Gil, Eirik Bakke, David R. Karger

    During the years, it has been possible to assess significant improvements in the computational efficiency of Semantic Web search and exploration systems. However, it has been much harder to assess how well different semantic systems’ user interfaces help their users. One of the key factors facilitating the advancement of research in a particular field is the ability to compare the performance of different

  • Fine-Grained Entity Linking
    J. Web Semant. (IF 2.238) Pub Date : 2020-08-26
    Henry Rosales-Méndez, Aidan Hogan, Barbara Poblete

    The Entity Linking (EL) task involves linking mentions of entities in a text with their identifier in a Knowledge Base (KB) such as Wikipedia, BabelNet, DBpedia, Freebase, Wikidata, YAGO, etc. Numerous techniques have been proposed to address this task down through the years. However, not all works adopt the same convention regarding the entities that the EL task should target; for example, while some

  • FAT-RE: A faster dependency-free model for relation extraction
    J. Web Semant. (IF 2.238) Pub Date : 2020-08-20
    Lifang Ding, Zeyang Lei, Guangxu Xun, Yujiu Yang

    Recent years have seen the dependency tree as effective information for relation extraction. Two problems still exist in previous methods: (1) dependency tree relies on external tools and needs to be carefully integrated with a trade-off between pruning noisy words and keeping semantic integrity; (2) dependency-based methods still have to encode sequential context as a supplement, which needs extra

  • GTFS-Madrid-Bench: A benchmark for virtual knowledge graph access in the transport domain
    J. Web Semant. (IF 2.238) Pub Date : 2020-08-08
    David Chaves-Fraga, Freddy Priyatna, Andrea Cimmino, Jhon Toledo, Edna Ruckhaus, Oscar Corcho

    A large number of datasets are being made available on the Web using a variety of formats and according to diverse data models. Ontology Based Data Integration (OBDI) has been traditionally proposed as a mechanism to facilitate access to such heterogeneous datasets, providing a unified view over their data by means of ontologies. Recently, the term “Virtual Knowledge Graph Access” has begun to be used

  • No one is perfect: Analysing the performance of question answering components over the DBpedia knowledge graph
    J. Web Semant. (IF 2.238) Pub Date : 2020-08-05
    Kuldeep Singh, Ioanna Lytra, Arun Sethupat Radhakrishna, Saeedeh Shekarpour, Maria-Esther Vidal, Jens Lehmann

    Question answering (QA) over knowledge graphs has gained significant momentum over the past five years due to the increasing availability of large knowledge graphs and the rising importance of Question Answering for user interaction. Existing QA systems have been extensively evaluated as black boxes and their performance has been characterised in terms of average results over all the questions of benchmarking

  • Evaluating and comparing ontology alignment systems: An MCDM approach
    J. Web Semant. (IF 2.238) Pub Date : 2020-07-12
    Majid Mohammadi, Jafar Rezaei

    Ontology alignment is vital in Semantic Web technologies with numerous applications in diverse disciplines. Due to diversity and abundance of ontology alignment systems, a proper evaluation can portray the evolution of ontology alignment and depicts the efficiency of a system for a particular domain. Evaluation can help system designers recognize the strength and shortcomings of their systems, and

  • Benchmarking neural embeddings for link prediction in knowledge graphs under semantic and structural changes
    J. Web Semant. (IF 2.238) Pub Date : 2020-06-18
    Asan Agibetov, Matthias Samwald

    Recently, link prediction algorithms based on neural embeddings have gained tremendous popularity in the Semantic Web community, and are extensively used for knowledge graph completion. While algorithmic advances have strongly focused on efficient ways of learning embeddings, fewer attention has been drawn to the different ways their performance and robustness can be evaluated. In this work we propose

  • Uncovering hidden semantics of set information in knowledge bases
    J. Web Semant. (IF 2.238) Pub Date : 2020-06-15
    Shrestha Ghosh, Simon Razniewski, Gerhard Weikum

    Knowledge Bases (KBs) contain a wealth of structured information about entities and predicates. This paper focuses on set-valued predicates, i.e., the relationship between an entity and a set of entities. In KBs, this information is often represented in two formats: (i) via counting predicates such as numberOfChildren and staffSize, that store aggregated integers, and (ii) via enumerating predicates

  • IQA: Interactive query construction in semantic question answering systems
    J. Web Semant. (IF 2.238) Pub Date : 2020-06-13
    Hamid Zafar, Mohnish Dubey, Jens Lehmann, Elena Demidova

    Semantic Question Answering (SQA) systems automatically interpret user questions expressed in a natural language in terms of semantic queries. This process involves uncertainty, such that the resulting queries do not always accurately match the user intent, especially for more complex and less common questions. In this article, we aim to empower users in guiding SQA systems towards the intended semantic

  • Chinese semantic document classification based on strategies of semantic similarity computation and correlation analysis
    J. Web Semant. (IF 2.238) Pub Date : 2020-05-23
    Shuo Yang, Ran Wei, Jingzhi Guo, Hengliang Tan

    Document classification has become an indispensable technology to realize intelligent information services. This technique is often applied to the tasks such as document organization, analysis, and archiving or implemented as a submodule to support high-level applications. It has been shown that semantic analysis can improve the performance of document classification. Although this has been incorporated

  • The role of knowledge in determining identity of long-tail entities
    J. Web Semant. (IF 2.238) Pub Date : 2020-04-25
    Filip Ilievski, Eduard Hovy, Piek Vossen, Stefan Schlobach, Qizhe Xie

    Identifying entities in text is an important step of semantic analysis. Some entity mentions comprise a name or description, but many include no information that identifies them in the system’s knowledge resources, which means that their identity cannot be established through traditional disambiguation. Consequently, such NIL (not in lexicon) entities have received little attention in entity linking

  • The enslaved ontology: Peoples of the historic slave trade
    J. Web Semant. (IF 2.238) Pub Date : 2020-04-23
    Cogan Shimizu, Pascal Hitzler, Quinn Hirt, Dean Rehberger, Seila Gonzalez Estrecha, Catherine Foley, Alicia M. Sheill, Walter Hawthorne, Jeff Mixter, Ethan Watrall, Ryan Carty, Duncan Tarr

    We present the Enslaved Ontology (V1.0) which was developed for integrating data about the historic slave trade from diverse sources in a use case driven by historians. Ontology development followed modular ontology design principles as derived from ontology design pattern application best practices and the eXtreme Design Methodology. Ontology content focuses on data about historic persons and the

  • GBKOM: A generic framework for BK-based ontology matching
    J. Web Semant. (IF 2.238) Pub Date : 2020-04-23
    Amina Annane, Zohra Bellahsene

    BK-based matching exploits external background knowledge resources (BK) to fill the semantic gap between the ontologies to align. Existing BK-based matchers implement the indirect matching approach in their internal architecture, which makes any adaptation or reuse of the code difficult. Indeed, to improve a particular step in the BK-based matching process, it is necessary to code the whole process

  • FEEL: Framework for the integration of Entity Extraction and Linking systems
    J. Web Semant. (IF 2.238) Pub Date : 2020-04-18
    Julio Hernandez, Jose L. Martinez-Rodriguez, Ivan Lopez-Arevalo, Ana B. Rios-Alvarado, Edwin Aldana-Bobadilla

    Entity extraction and linking (EEL) is an important task of the Semantic Web that allows to identify real-world objects from text and associate them with their respective resources from a Knowledge Base. Thus, one purpose of the EEL task is to extract knowledge from text. In recent years, several systems have been proposed for addressing such a task in several domains, languages, and knowledge bases

  • Relaxing relationship queries on graph data
    J. Web Semant. (IF 2.238) Pub Date : 2020-03-03
    Shuxin Li, Gong Cheng, Chengkai Li

    In many domains we have witnessed the need to search a large entity-relation graph for direct and indirect relationships between a set of entities specified in a query. A search result, called a semantic association (SA), is typically a compact (e.g., diameter-constrained) connected subgraph containing all the query entities. For this problem of SA search, efficient algorithms exist but will return

  • Curriculum learning for distant supervision relation extraction
    J. Web Semant. (IF 2.238) Pub Date : 2020-02-29
    Qiongxin Liu, Peng Wang, Jiasheng Wang, Jing Ma

    Relation extraction under distant supervision leverages the existing knowledge base to label data automatically, thus greatly reduced the consumption of human labors. Although distant supervision is an efficient method to obtain a large amount of labeled data, the training dataset labeled by distant supervision suffers from noise problem resulting in poor generalization ability of the relation extractor

  • DABGEO: A reusable and usable global energy ontology for the energy domain
    J. Web Semant. (IF 2.238) Pub Date : 2020-02-05
    Javier Cuenca, Felix Larrinaga, Edward Curry

    The heterogeneity of energy ontologies hinders the interoperability between ontology-based energy management applications to perform a large-scale energy management. Thus, there is the need for a global ontology that provides common vocabularies to represent the energy subdomains. A global energy ontology must provide a balance of reusability–usability to moderate the effort required to reuse it in

  • The Internet of Musical Things Ontology
    J. Web Semant. (IF 2.238) Pub Date : 2020-01-22
    Luca Turchet, Francesco Antoniazzi, Fabio Viola, Fausto Giunchiglia, György Fazekas

    The Internet of Musical Things (IoMusT) is an emerging research area consisting of the extension of the Internet of Things paradigm to the music domain. Interoperability represents a central issue within this domain, where heterogeneous objects dedicated to the production and/or reception of musical content (Musical Things) are envisioned to communicate between each other. This paper proposes an ontology

  • Large-scale relation extraction from web documents and knowledge graphs with human-in-the-loop
    J. Web Semant. (IF 2.238) Pub Date : 2019-12-30
    Petar Ristoski, Anna Lisa Gentile, Alfredo Alba, Daniel Gruhl, Steven Welch

    The Semantic Web movement has produced a wealth of curated collections of entities and facts, often referred as Knowledge Graphs. Creating and maintaining such Knowledge Graphs is far from being a solved problem: it is crucial to constantly extract new information from the vast amount of heterogeneous sources of data on the Web. In this work we address the task of Knowledge Graph population. Specifically

  • SOBA: Semi-automated Ontology Builder for Aspect-based sentiment analysis
    J. Web Semant. (IF 2.238) Pub Date : 2019-12-11
    Lisa Zhuang, Kim Schouten, Flavius Frasincar

    This research explores the possibility of improving knowledge-driven aspect-based sentiment analysis (ABSA) in terms of efficiency and effectiveness. This is done by implementing a Semi-automated Ontology Builder for Aspect-based sentiment analysis (SOBA). Semi-automatization of the ontology building process could produce more extensive ontologies, whilst shortening the building time. Furthermore,

  • Analysis of Ontology Competency Questions and their formalizations in SPARQL-OWL
    J. Web Semant. (IF 2.238) Pub Date : 2019-11-06
    Dawid Wiśniewski, Jedrzej Potoniec, Agnieszka Ławrynowicz, C. Maria Keet

    Competency Questions (CQs) are natural language questions outlining and constraining the scope of knowledge represented in an ontology. Despite that CQs are a part of several ontology engineering methodologies, the actual publication of CQs for the available ontologies is very limited and even scarcer is the publication of their respective formalizations in terms of, e.g., SPARQL queries. This paper

  • Automated Class Correction and Enrichment in the Semantic Web
    J. Web Semant. (IF 2.238) Pub Date : 2019-11-05
    Molood Barati, Quan Bai, Qing Liu

    The Semantic Web is an effort to interchange unstructured data over the Web into a structured format that is processable not only by human beings but also computers. The key backbones of Semantic Web are ontologies and annotations that provide semantics for data. Ontologies are usually created before actual data is populated. Subsequently, they can be incomplete and they often do not provide all aspects

  • Manual semantic annotations: User evaluation of interface and interaction designs
    J. Web Semant. (IF 2.238) Pub Date : 2019-07-25
    Annika Hinze, Ralf Heese, Alexa Schlegel, Adrian Paschke

    Semantic annotation is the process by which existing texts receive a mark-up that allows automatic identification of named entities (e.g., to distinguish between a turkey bird and the country Turkey). Manual annotation is useful both as stand-alone process in a domain-specific setting or as post-processing for automatic annotation algorithms. Development of most annotation tools strongly focuses on

  • Ontop-spatial: Ontop of geospatial databases
    J. Web Semant. (IF 2.238) Pub Date : 2019-07-01
    Konstantina Bereta, Guohui Xiao, Manolis Koubarakis

    In this paper, we propose an OBDA approach for accessing geospatial data stored in relational databases using the R2RML mappings and OGC standard GeoSPARQL. On the theoretical side, we provide a formalization of GeoSPARQL in terms of SPARQL entailment regime. For a practical query answering algorithm, we introduce an extension to the existing SPARQL-to-SQL translation method to support GeoSPARQL features

  • Implicit quantification made explicit: How to interpret blank nodes and universal variables in Notation3 Logic
    J. Web Semant. (IF 2.238) Pub Date : 2019-05-31
    Dörthe Arndt, Tom Schrijvers, Jos De Roo, Ruben Verborgh

    Since the invention of Notation3 Logic, several years have passed in which the theory has been refined and applied in different reasoning engines like Cwm, EYE, and FuXi. But despite these developments, a clear formal definition of Notation3’s semantics is still missing. This does not only form an obstacle for the formal investigation of that logic and its relations to other formalisms, it has also

  • Representing anything from scholar papers
    J. Web Semant. (IF 2.238) Pub Date : 2019-04-17
    Danhao Zhu, Xin-Yu Dai, Jiajun Chen

    Many scholar knowledge mining tasks depend on the representations of different scholar entities and their compositions, including author, publication venue and paper. However, the existing methods always tried to learn different kinds of scholar representations individually. The citation relationships among different types of entities are sometimes ignored. Moreover, the separated learned representations

  • Evaluating the impact of semantic technologies on bibliographic systems: A user-centred and comparative approach
    J. Web Semant. (IF 2.238) Pub Date : 2019-03-19
    Mariano Rico, Daniel Vila-Suero, Iuliana Botezan, Asunción Gómez-Pérez

    Semantic and linked-data technologies are currently used by several cultural heritage institutions to make their content available through the Web. Although these technologies are heavily oriented towards data reuse and integration, one clear benefit highlighted by recent literature is the enhancement of human cultural consumption and user experience through the development of novel cultural end-user

  • Extending WordNet with UFO foundational ontology
    J. Web Semant. (IF 2.238) Pub Date : 2019-03-15
    Felipe Leão, Kate Revoredo, Fernanda Baião

    WordNet is a large lexical database used by an uncountable number of applications for computational linguistics. Many proposals have attempted to better describe it in a semantic perspective, especially addressing synonymy, taxonomy and mereology properties, which led to very good results in domain-specific applications. A philosophical shift on this semantic description could, however, improve the

  • Knowledge graph fact prediction via knowledge-enriched tensor factorization
    J. Web Semant. (IF 2.238) Pub Date : 2019-02-15
    Ankur Padia, Konstantinos Kalpakis, Francis Ferraro, Tim Finin

    We present a family of novel methods for embedding knowledge graphs into real-valued tensors. These tensor-based embeddings capture the ordered relations that are typical in the knowledge graphs represented by semantic web languages like RDF. Unlike many previous models, our methods can easily use prior background knowledge provided by users or extracted automatically from existing knowledge graphs

  • Reasoning and querying web-scale open data based on DL-LiteA in a divide-and-conquer way
    J. Web Semant. (IF 2.238) Pub Date : 2019-02-06
    Zhenzhen Gu, Songmao Zhang, Cungen Cao

    We propose to use DL-LiteA techniques to reason and query the Web-scale Open Data (knowledge bases) described by Semantic Web standards like RDF and OWL due to the low reasoning complexity and suitable expressivity of the language. When facing the real-life scalability challenge, the actual reasoning and query answering may become infeasible by the following two factors. Firstly, for both satisfiability

  • BNO—An ontology for understanding the transittability of complex biomolecular networks
    J. Web Semant. (IF 2.238) Pub Date : 2019-01-21
    Ali Ayadi, Cecilia Zanni-Merk, François de Bertrand de Beuvron, Julie Thompson, Saoussen Krichen

    Analysis of biological systems is being progressively facilitated by computational tools. Most of these tools are based on qualitative and numerical methods. However, they are not always evident, and there is an increasing need to provide an additional semantic layer. Semantic technologies, especially ontologies, are one of the tools frequently used for this purpose. Indeed, they are indispensable

  • An ontology-mediated analytics-aware approach to support monitoring and diagnostics of static and streaming data
    J. Web Semant. (IF 2.238) Pub Date : 2019-01-21
    Evgeny Kharlamov, Yannis Kotidis, Theofilos Mailis, Christian Neuenstadt, Charalampos Nikolaou, Özgür Özçep, Christoforos Svingos, Dmitriy Zheleznyakov, Yannis Ioannidis, Steffen Lamparter, Ralf Möller, Arild Waaler

    Streaming analytics that requires integration and aggregation of heterogeneous and distributed streaming and static data is a typical task in many industrial scenarios including the case of industrial IoT where several pieces of industrial equipment such as turbines in Siemens are integrated into an IoT. The OBDA approach has a great potential to facilitate such tasks; however, it has a number of limitations

  • Tolstoy semanticized: Constructing a digital edition for knowledge discovery
    J. Web Semant. (IF 2.238) Pub Date : 2019-01-17
    Anastasia Bonch-Osmolovskaya, Daniil Skorinkin, Irina Pavlova, Matvey Kolbasov, Boris Orekhov

    The paper presents the results of a project devoted to the creation of a digital edition of Leo Tolstoy’s complete works.1 Our primary source is the 90-volume critical print edition of Tolstoy’s oeuvre. We discuss the rationale for semantic markup of metadata for three classes of texts: works, letters and diaries. We extract information from the critical apparatus and supplement it with some new additional

  • On expansion and contraction of DL-Lite knowledge bases
    J. Web Semant. (IF 2.238) Pub Date : 2019-01-03
    Dmitriy Zheleznyakov, Evgeny Kharlamov, Werner Nutt, Diego Calvanese

    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

  • Linking and disambiguating entities across heterogeneous RDF graphs
    J. Web Semant. (IF 2.238) Pub Date : 2019-01-02
    Manel Achichi, Zohra Bellahsene, Mohamed Ben Ellefi, Konstantin Todorov

    Establishing identity links across RDF datasets is a central and challenging task on the way to realising the Data Web project. It is well-known that data supplied by different sources can be highly heterogeneous—two entities referring to the same real world object are often described, structured and valued differently, or in a complementary fashion. In this paper, we explore the origins and the multiplicity

  • Enabling Spatio-Temporal Search in Open Data
    J. Web Semant. (IF 2.238) Pub Date : 2018-12-27
    Sebastian Neumaier, Axel Polleres

    Intuitively, most datasets found on governmental Open Data portals are organized by spatio-temporal criteria, that is, single datasets provide data for a certain region, valid for a certain time period. Likewise, for many use cases (such as, for instance, data journalism and fact checking) a pre-dominant need is to scope down the relevant datasets to a particular period or region. Rich spatio-temporal

  • Why are ontologies not reused across the same domain?
    J. Web Semant. (IF 2.238) Pub Date : 2018-12-27
    Mariano Fernández-López, María Poveda-Villalón, Mari Carmen Suárez-Figueroa, Asunción Gómez-Pérez

    Even though one of the main characteristics of ontologies has always been claimed to be their reusability, throughout this paper it will be shown that ontology reuse across a given domain is not a consolidated practice. We have carried out a statistical study on ontology reuse in the ontologies collected in Linked Open Vocabularies (LOV), in addition to a particular analysis of a use case. The results

  • Improving discoverability of open government data with rich metadata descriptions using semantic government vocabulary
    J. Web Semant. (IF 2.238) Pub Date : 2018-12-26
    Petr Křemen, Martin Nečaský

    The descriptive metadata gathered by open data catalogs are often simple key–value pairs that describe provenance information, but not concepts from the domain of the described dataset. Search engines relying on such metadata cannot make use of semantic connections among datasets. In this paper, we present a Semantic Government Vocabulary that is used for creating rich annotations of Open Government

  • Embedding models for episodic knowledge graphs
    J. Web Semant. (IF 2.238) Pub Date : 2018-12-24
    Yunpu Ma, Volker Tresp, Erik A. Daxberger

    In recent years a number of large-scale triple-oriented knowledge graphs have been generated and various models have been proposed to perform learning in those graphs. Most knowledge graphs are static and reflect the world in its current state. In reality, of course, the state of the world is changing: a healthy person becomes diagnosed with a disease and a new president is inaugurated. In this paper

  • Grounding knowledge acquisition with ontology explanation:A case study
    J. Web Semant. (IF 2.238) Pub Date : 2018-12-23
    Ana Cristina B. Garcia, Adriana S. Vivacqua

    Knowledge validation is still a challenge when constructing knowledge-based systems. It is one of the major reasons for user rejection and disagreement between project participants. Systematic and periodic reviews of the domain ontology, with a formal agreement of the whole development team (including the experts) are a recommended good practice. Nevertheless, these reviews do not guarantee system

  • Leopard — A baseline approach to attribute prediction and validation for knowledge graph population
    J. Web Semant. (IF 2.238) Pub Date : 2018-12-19
    René Speck, Axel-Cyrille Ngonga Ngomo

    In this paper, we report on the participation of Leopard to the Semantic Web Challenge at the 16th International Semantic Web Conference. Leopard is a baseline approach to predict and validate attributes for knowledge graph population. The approach was designed as a baseline for the challenge. It combines diverse text extraction methods with a simple precision ranking and utilizes sources from the

  • User-centric pattern mining on knowledge graphs: An archaeological case study
    J. Web Semant. (IF 2.238) Pub Date : 2018-12-13
    W.X. Wilcke, V. de Boer, M.T.M. de Kleijn, F.A.H. van Harmelen, H.J. Scholten

    In recent years, there has been a growing interest from the digital humanities in knowledge graphs as data modelling paradigm. Already, this has led to the creation of many such knowledge graphs, many of which are now available as part of the Linked Open Data cloud. This presents new opportunities for data mining. In this work, we develop, implement, and evaluate (both data-driven and user-driven)

  • On modeling linked open statistical data
    J. Web Semant. (IF 2.238) Pub Date : 2018-11-28
    Evangelos Kalampokis, Dimitris Zeginis, Konstantinos Tarabanis

    A major part of Open Data concerns statistics such as economic and social indicators. Statistical data are structured in a multidimensional manner creating data cubes. Recently, National Statistical Institutes and public authorities adopted the Linked Data paradigm to publish their statistical data on the Web. Many vocabularies have been created to enable modeling data cubes as RDF graphs, and thus

  • Completeness and consistency analysis for evolving knowledge bases
    J. Web Semant. (IF 2.238) Pub Date : 2018-11-22
    Mohammad Rifat Ahmmad Rashid, Giuseppe Rizzo, Marco Torchiano, Nandana Mihindukulasooriya, Oscar Corcho, Raúl García-Castro

    Assessing the quality of an evolving knowledge base is a challenging task as it often requires to identify correct quality assessment procedures. Since data is often derived from autonomous, and increasingly large data sources, it is impractical to manually curate the data, and challenging to continuously and automatically assess their quality. In this paper, we explore two main areas of quality assessment

  • Semantically-enhanced rule-based diagnostics for industrial Internet of Things: The SDRL language and case study for Siemens trains and turbines
    J. Web Semant. (IF 2.238) Pub Date : 2018-11-20
    Evgeny Kharlamov, Gulnar Mehdi, Ognjen Savković, Guohui Xiao, Elem Güzel Kalaycı, Mikhail Roshchin

    An Industrial Internet of Things (IoT) is a network of intelligent industrial equipment such as trains and power generating turbines that collect and share large amounts of data. These data are either generated by various sensors deployed in the equipment or captures equipment specific information such as configurations, history of use, and manufacturer. Diagnostics of the industrial IoT is critical

  • Characterising dataset search—An analysis of search logs and data requests
    J. Web Semant. (IF 2.238) Pub Date : 2018-11-19
    Emilia Kacprzak, Laura Koesten, Luis-Daniel Ibáñez, Tom Blount, Jeni Tennison, Elena Simperl

    Large amounts of data are becoming increasingly available online. In order to benefit from it we need tools to retrieve the most relevant datasets that match ones data needs. Several vocabularies have been developed to describe datasets in order to increase their discoverability, but for data publishers is costly to cumbersome to annotate them using all, leading to the question of what properties are

  • DCAT-AP representation of Czech National Open Data Catalog and its impact
    J. Web Semant. (IF 2.238) Pub Date : 2018-11-16
    Jakub Klímek

    Open data is now a heavily discussed topic around the world and in the European Union. In the Czech Republic, open data is a term anchored in legislation, which includes the requirement of registration of all open data in the Czech National Open Data Portal (NODC). In this paper we describe the NODC, its architecture, dataset registration processes including the harvesting of Local Open Data Catalogs

  • Raising interoperability among base registries: The evolution of the Linked Base Registry for addresses in Flanders
    J. Web Semant. (IF 2.238) Pub Date : 2018-11-08
    Raf Buyle, Ziggy Vanlishout, Serena Coetzee, Dieter De Paepe, Mathias Van Compernolle, Geert Thijs, Bert Van Nuffelen, Laurens De Vocht, Peter Mechant, Björn De Vidts, Erik Mannens

    The transformation of society towards a digital economy and government austerity creates a new context leading to changing roles for both government and private sector. Boundaries between public and private services are blurring, enabling government and private sector to collaborate and share responsibilities. In Belgium, the regional Government of Flanders embedded the re-use of public sector information

  • Expressive ontology learning as neural machine translation
    J. Web Semant. (IF 2.238) Pub Date : 2018-11-02
    Giulio Petrucci, Marco Rospocher, Chiara Ghidini

    Automated ontology learning from unstructured textual sources has been proposed in literature as a way to support the difficult and time-consuming task of knowledge modeling for semantic applications. In this paper we propose a system, based on a neural network in the encoder–decoder configuration, to translate natural language definitions into Description Logics formulæ through syntactic transformation

  • Parallel tractability of ontology materialization: Technique and practice
    J. Web Semant. (IF 2.238) Pub Date : 2018-10-26
    Zhangquan Zhou, Guilin Qi, Birte Glimm

    Materialization is an important reasoning service for many ontology-based applications, but the rapid growth of semantic data poses the challenge to efficiently perform materialization on large-scale ontologies. Parallel materialization algorithms work well for some ontologies, although the reasoning problem for the used ontology language is not in NC, i.e., the theoretical complexity class for parallel

  • Automating ontology engineering support activities with OnToology
    J. Web Semant. (IF 2.238) Pub Date : 2018-10-09
    Ahmad Alobaid, Daniel Garijo, María Poveda-Villalón, Idafen Santana-Perez, Alba Fernández-Izquierdo, Oscar Corcho

    Due to the increasing uptake of semantic technologies, ontologies are now part of a good number of information systems. As a result, software development teams that have to combine ontology engineering activities with software development practices are facing several challenges, since these two areas have evolved, in general, separately. In this paper we present OnToology, an approach to manage ontology

  • TISCO: Temporal scoping of facts
    J. Web Semant. (IF 2.238) Pub Date : 2018-10-01
    Anisa Rula, Matteo Palmonari, Simone Rubinacci, Axel-Cyrille Ngonga Ngomo, Jens Lehmann, Andrea Maurino, Diego Esteves

    Some facts in the Web of Data are only valid within a certain time interval. However, most of the knowledge bases available on the Web of Data do not provide temporal information explicitly. Hence, the relationship between facts and time intervals is often lost. A few solutions are proposed in this field. Most of them are concentrated more in extracting facts with time intervals rather than trying

  • Comparing ontology authoring workflows with Protégé: In the laboratory, in the tutorial and in the ‘wild’
    J. Web Semant. (IF 2.238) Pub Date : 2018-10-01
    Markel Vigo, Nicolas Matentzoglu, Caroline Jay, Robert Stevens

    The development of ontology engineering tools has traditionally lacked a user-centred perspective, instead being guided by the need to address particular gaps indicated by anecdotal evidence. This has typically resulted in prototypes that do not obtain traction beyond a narrow scope. Understanding the authoring patterns of ontology engineers is crucial to informing the development of ontology engineering

  • Entity set expansion with semantic features of knowledge graphs
    J. Web Semant. (IF 2.238) Pub Date : 2018-09-26
    Jun Chen, Yueguo Chen, Xiangling Zhang, Xiaoyong Du, Ke Wang, Ji-Rong Wen

    A large-scale knowledge graph contains a huge number of path-based semantic features, which provides a flexible mechanism to assign and expand semantics/attributes to entities. A particular set of these semantic features can be exploited on the fly, to support particular entity-oriented semantic search tasks. In this paper, we use entity set expansion as an example to show how these path-based semantic

  • Decentralized Collaborative Knowledge Management Using Git
    J. Web Semant. (IF 2.238) Pub Date : 2018-09-11
    Natanael Arndt, Patrick Naumann, Norman Radtke, Michael Martin, Edgard Marx

    The World Wide Web and the Semantic Web are designed as a network of distributed services and datasets. The distributed character of the Web brings manifold collaborative possibilities to interchange data. The commonly adopted collaborative solutions for RDF data are centralized (e. g. SPARQL endpoints and wiki systems). But to support distributed collaboration, a system is needed, that supports divergence

  • GeoTriples: Transforming geospatial data into RDF graphs using R2RML and RML mappings
    J. Web Semant. (IF 2.238) Pub Date : 2018-09-11
    Kostis Kyzirakos, Dimitrianos Savva, Ioannis Vlachopoulos, Alexandros Vasileiou, Nikolaos Karalis, Manolis Koubarakis, Stefan Manegold

    A lot of geospatial data has become available at no charge in many countries recently. Geospatial data that is currently made available by government agencies usually do not follow the linked data paradigm. In the few cases where government agencies do follow the linked data paradigm (e.g., Ordnance Survey in the United Kingdom), specialized scripts have been used for transforming geospatial data into

  • Measuring expert performance at manually classifying domain entities under upper ontology classes
    J. Web Semant. (IF 2.238) Pub Date : 2018-09-06
    Robert Stevens, Phillip Lord, James Malone, Nicolas Matentzoglu

    Background: Classifying entities in domain ontologies under upper ontology classes is a recommended task in ontology engineering to facilitate semantic interoperability and modelling consistency. Integrating upper ontologies this way is difficult and, despite emerging automated methods, remains a largely manual task. Problem: Little is known about how well experts perform at upper ontology integration

  • Triple storage for random-access versioned querying of RDF archives
    J. Web Semant. (IF 2.238) Pub Date : 2018-09-03
    Ruben Taelman, Miel Vander Sande, Joachim Van Herwegen, Erik Mannens, Ruben Verborgh

    When publishing Linked Open Datasets on the Web, most attention is typically directed to their latest version. Nevertheless, useful information is present in or between previous versions. In order to exploit this historical information in dataset analysis, we can maintain history in RDF archives. Existing approaches either require much storage space, or they expose an insufficiently expressive or efficient

  • Neural Wikipedian: Generating Textual Summaries from Knowledge Base Triples
    J. Web Semant. (IF 2.238) Pub Date : 2018-07-30
    Pavlos Vougiouklis, Hady Elsahar, Lucie-Aimée Kaffee, Christophe Gravier, Frédérique Laforest, Jonathon Hare, Elena Simperl

    Most people need textual or visual interfaces in order to make sense of Semantic Web data. In this paper, we investigate the problem of generating natural language summaries for Semantic Web data using neural networks. Our end-to-end trainable architecture encodes the information from a set of triples into a vector of fixed dimensionality and generates a textual summary by conditioning the output on

  • Machine Translation using Semantic Web Technologies: A Survey
    J. Web Semant. (IF 2.238) Pub Date : 2018-07-17
    Diego Moussallem, Matthias Wauer, Axel-Cyrille Ngonga Ngomo

    A large number of machine translation approaches have recently been developed to facilitate the fluid migration of content across languages. However, the literature suggests that many obstacles must still be dealt with to achieve better automatic translations. One of these obstacles is lexical and syntactic ambiguity. A promising way of overcoming this problem is using Semantic Web technologies. This

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