-
Conjunctive query answering over unrestricted OWL 2 ontologies Semant. Web (IF 3.0) Pub Date : 2023-12-13 Federico Igne, Stefano Germano, Ian Horrocks
Abstract Conjunctive Query (CQ) answering is a primary reasoning task over knowledge bases. However, when considering expressive description logics, query answering can be computationally very expensive; reasoners for CQ answering, although heavily optimized, often sacrifice expressive power of the input ontology or completeness of the computed answers in order to achieve tractability and scalability
-
A conceptual model for ontology quality assessment Semant. Web (IF 3.0) Pub Date : 2023-12-13 R.S.I. Wilson, J.S. Goonetillake, W.A. Indika, Athula Ginige
Abstract With the continuous advancement of methods, tools, and techniques in ontology development, ontologies have emerged in various fields such as machine learning, robotics, biomedical informatics, agricultural informatics, crowdsourcing, database management, and the Internet of Things. Nevertheless, the nonexistence of a universally agreed methodology for specifying and evaluating the quality
-
DegreEmbed: Incorporating entity embedding into logic rule learning for knowledge graph reasoning Semant. Web (IF 3.0) Pub Date : 2023-12-13 Haotian Li, Hongri Liu, Yao Wang, Guodong Xin, Yuliang Wei
Abstract Knowledge graphs (KGs), as structured representations of real world facts, are intelligent databases incorporating human knowledge that can help machine imitate the way of human problem solving. However, KGs are usually huge and there are inevitably missing facts in KGs, thus undermining applications such as question answering and recommender systems that are based on knowledge graph reasoning
-
Optimizing SPARQL queries over decentralized knowledge graphs Semant. Web (IF 3.0) Pub Date : 2023-12-13 Christian Aebeloe, Gabriela Montoya, Katja Hose
Abstract While the Web of Data in principle offers access to a wide range of interlinked data, the architecture of the Semantic Web today relies mostly on the data providers to maintain access to their data through SPARQL endpoints. Several studies, however, have shown that such endpoints often experience downtime, meaning that the data they maintain becomes inaccessible. While decentralized systems
-
Quantifiable integrity for Linked Data on the web Semant. Web (IF 3.0) Pub Date : 2023-12-13 Christoph H.-J. Braun, Tobias Käfer
Abstract We present an approach to publish Linked Data on the Web with quantifiable integrity using Web technologies, and in which rational agents are incentivised to contribute to the integrity of the link network. To this end, we introduce self-verifying resource representations, that include Linked Data Signatures whose signature value is used as a suffix in the resource’s URI. Links among such
-
Focused categorization power of ontologies: General framework and study on simple existential concept expressions Semant. Web (IF 3.0) Pub Date : 2023-12-13 Vojtěch Svátek, Ondřej Zamazal, Viet Bach Nguyen, Jiří Ivánek, Ján Kľuka, Miroslav Vacura
Abstract When reusing existing ontologies for publishing a dataset in RDF (or developing a new ontology), preference may be given to those providing extensive subcategorization for important classes (denoted as focus classes). The subcategories may consist not only of named classes but also of compound class expressions. We define the notion of focused categorization power of a given ontology, with
-
Using semantic story maps to describe a territory beyond its map Semant. Web (IF 3.0) Pub Date : 2023-12-13 Valentina Bartalesi, Gianpaolo Coro, Emanuele Lenzi, Nicolò Pratelli, Pasquale Pagano, Francesco Felici, Michele Moretti, Gianluca Brunori
Abstract The paper presents the Story Map Building and Visualizing Tool (SMBVT) that allows users to create story maps within a collaborative environment and a usable Web interface. It is entirely open-source and published as a free-to-use solution. It uses Semantic Web technologies in the back-end system to represent stories through a reference ontology for representing narratives. It builds up a
-
Sem@ K: Is my knowledge graph embedding model semantic-aware? Semant. Web (IF 3.0) Pub Date : 2023-12-13 Nicolas Hubert, Pierre Monnin, Armelle Brun, Davy Monticolo
Abstract Using knowledge graph embedding models (KGEMs) is a popular approach for predicting links in knowledge graphs (KGs). Traditionally, the performance of KGEMs for link prediction is assessed using rank-based metrics, which evaluate their ability to give high scores to ground-truth entities. However, the literature claims that the KGEM evaluation procedure would benefit from adding supplementary
-
What is in your cookie box? Explaining ingredients of web cookies with knowledge graphs Semant. Web (IF 3.0) Pub Date : 2023-08-21 Geni Bushati, Sven Carsten Rasmusen, Anelia Kurteva, Anurag Vats, Petraq Nako, Anna Fensel
Abstract The General Data Protection Regulation (GDPR) has imposed strict requirements for data sharing, one of which is informed consent. A common way to request consent online is via cookies. However, commonly, users accept online cookies being unaware of the meaning of the given consent and the following implications. Once consent is given, the cookie “disappears”, and one forgets that consent was
-
Searching for explanations of black-box classifiers in the space of semantic queries Semant. Web (IF 3.0) Pub Date : 2023-08-02 Jason Liartis, Edmund Dervakos, Orfeas Menis-Mastromichalakis, Alexandros Chortaras, Giorgos Stamou
Abstract Deep learning models have achieved impressive performance in various tasks, but they are usually opaque with regards to their inner complex operation, obfuscating the reasons for which they make decisions. This opacity raises ethical and legal concerns regarding the real-life use of such models, especially in critical domains such as in medicine, and has led to the emergence of the eXplainable
-
Deriving semantic validation rules from industrial standards: An OPC UA study Semant. Web (IF 3.0) Pub Date : 2023-06-19 Yashoda Saisree Bareedu, Thomas Frühwirth, Christoph Niedermeier, Marta Sabou, Gernot Steindl, Aparna Saisree Thuluva, Stefani Tsaneva, Nilay Tufek Ozkaya
Abstract Industrial standards provide guidelines for data modeling to ensure interoperability between stakeholders of an industry branch (e.g., robotics). Most frequently, such guidelines are provided in an unstructured format (e.g., pdf documents) which hampers the automated validations of information objects (e.g., data models) that rely on such standards in terms of their compliance with the modeling
-
A benchmark dataset with Knowledge Graph generation for Industry 4.0 production lines Semant. Web (IF 3.0) Pub Date : 2023-06-13 Muhammad Yahya, Aabid Ali, Qaiser Mehmood, Lan Yang, John G. Breslin, Muhammad Intizar Ali
Abstract Industry 4.0 (I4.0) is a new era in the industrial revolution that emphasizes machine connectivity, automation, and data analytics. The I4.0 pillars such as autonomous robots, cloud computing, horizontal and vertical system integration, and the industrial internet of things have increased the performance and efficiency of production lines in the manufacturing industry. Over the past years
-
Separability and Its Approximations in Ontology-based Data Management Semant. Web (IF 3.0) Pub Date : 2023-06-08 Gianluca Cima, Federico Croce, Maurizio Lenzerini
Abstract Given two datasets, i.e., two sets of tuples of constants, representing positive and negative examples, logical separability is the reasoning task of finding a formula in a certain target query language that separates them. As already pointed out in previous works, this task turns out to be relevant in several application scenarios such as concept learning and generating referring expressions
-
Dynamic system models and their simulation in the Semantic Web Semant. Web (IF 3.0) Pub Date : 2023-06-08 Moritz Stüber, Georg Frey
Abstract Modelling and Simulation (M&S) are core tools for designing, analysing and operating today’s industrial systems. They often also represent both a valuable asset and a significant investment. Typically, their use is constrained to a software environment intended to be used by engineers on a single computer. However, the knowledge relevant to a task involving modelling and simulation is in general
-
Incremental schema integration for data wrangling via knowledge graphs Semant. Web (IF 3.0) Pub Date : 2023-06-08 Javier Flores, Kashif Rabbani, Sergi Nadal, Cristina Gómez, Oscar Romero, Emmanuel Jamin, Stamatia Dasiopoulou
Abstract Virtual data integration is the current approach to go for data wrangling in data-driven decision-making. In this paper, we focus on automating schema integration, which extracts a homogenised representation of the data source schemata and integrates them into a global schema to enable virtual data integration. Schema integration requires a set of well-known constructs: the data source schemata
-
Enhancing awareness of industrial robots in collaborative manufacturing Semant. Web (IF 3.0) Pub Date : 2023-06-08 Alessandro Umbrico, Amedeo Cesta, Andrea Orlandini
Abstract The diffusion of Human-Robot Collaborative cells is prevented by several barriers. Classical control approaches seem not yet fully suitable for facing the variability conveyed by the presence of human operators beside robots. The capabilities of representing heterogeneous knowledge representation and performing abstract reasoning are crucial to enhance the flexibility of control solutions
-
A neuro-symbolic system over knowledge graphs for link prediction Semant. Web (IF 3.0) Pub Date : 2023-06-07 Ariam Rivas, Diego Collarana, Maria Torrente, Maria-Esther Vidal
Abstract Neuro-Symbolic Artificial Intelligence (AI) focuses on integrating symbolic and sub-symbolic systems to enhance the performance and explainability of predictive models. Symbolic and sub-symbolic approaches differ fundamentally in how they represent data and make use of data features to reach conclusions. Neuro-symbolic systems have recently received significant attention in the scientific
-
MuHeQA: Zero-shot question answering over multiple and heterogeneous knowledge bases Semant. Web (IF 3.0) Pub Date : 2023-06-07 Carlos Badenes-Olmedo, Oscar Corcho
Abstract There are two main limitations in most of the existing Knowledge Graph Question Answering (KGQA) algorithms. First, the approaches depend heavily on the structure and cannot be easily adapted to other KGs. Second, the availability and amount of additional domain-specific data in structured or unstructured formats has also proven to be critical in many of these systems. Such dependencies limit
-
Reason-able embeddings: Learning concept embeddings with a transferable neural reasoner Semant. Web (IF 3.0) Pub Date : 2023-06-02 Dariusz Max Adamski, Jędrzej Potoniec
Abstract We present a novel approach for learning embeddings of ALC knowledge base concepts. The embeddings reflect the semantics of the concepts in such a way that it is possible to compute an embedding of a complex concept from the embeddings of its parts by using appropriate neural constructors. Embeddings for different knowledge bases are vectors in a shared vector space, shaped in such a way that
-
Evaluating the usability of a semantic environmental health data framework: Approach and study Semant. Web (IF 3.0) Pub Date : 2023-05-08 Albert Navarro-Gallinad, Fabrizio Orlandi, Jennifer Scott, Mark Little, Declan O’Sullivan
Abstract Environmental exposures transported across air, land and water can affect our health making us more susceptible to developing a disease. Therefore, researchers need to face the complex task of integrating environmental exposures and linking them to health events with the relevant spatiotemporal and health context for individuals or populations. We present a usability evaluation approach and
-
Terminology and ontology development for semantic annotation: A use case on sepsis and adverse events Semant. Web (IF 3.0) Pub Date : 2023-05-08 Melissa Y. Yan, Lise Tuset Gustad, Lise Husby Høvik, Øystein Nytrø
Abstract Annotations enrich text corpora and provide necessary labels for natural language processing studies. To reason and infer underlying implicit knowledge captured by labels, an ontology is needed to provide a semantically annotated corpus with structured domain knowledge. Utilizing a corpus of adverse event documents annotated for sepsis-related signs and symptoms as a use case, this paper details
-
Context-aware query derivation for IoT data streams with DIVIDE enabling privacy by design Semant. Web (IF 3.0) Pub Date : 2023-05-08 Mathias De Brouwer, Bram Steenwinckel, Ziye Fang, Marija Stojchevska, Pieter Bonte, Filip De Turck, Sofie Van Hoecke, Femke Ongenae
Abstract Integrating Internet of Things (IoT) sensor data from heterogeneous sources with domain knowledge and context information in real-time is a challenging task in IoT healthcare data management applications that can be solved with semantics. Existing IoT platforms often have issues with preserving the privacy of patient data. Moreover, configuring and managing context-aware stream processing
-
Knowledge graphs for enhancing transparency in health data ecosystems 1 Semant. Web (IF 3.0) Pub Date : 2023-05-08 Fotis Aisopos, Samaneh Jozashoori, Emetis Niazmand, Disha Purohit, Ariam Rivas, Ahmad Sakor, Enrique Iglesias, Dimitrios Vogiatzis, Ernestina Menasalvas, Alejandro Rodriguez Gonzalez, Guillermo Vigueras, Daniel Gomez-Bravo, Maria Torrente, Roberto Hernández López, Mariano Provencio Pulla, Athanasios Dalianis, Anna Triantafillou, Georgios Paliouras, Maria-Esther Vidal
Abstract Tailoring personalized treatments demands the analysis of a patient’s characteristics, which may be scattered over a wide variety of sources. These features include family history, life habits, comorbidities, and potential treatment side effects. Moreover, the analysis of the services visited the most by a patient before a new diagnosis, as well as the type of requested tests, may uncover
-
ciTIzen-centric DAta pLatform (TIDAL): Sharing distributed personal data in a privacy-preserving manner for health research Semant. Web (IF 3.0) Pub Date : 2023-05-08 Chang Sun, Marc Gallofré Ocaña, Johan van Soest, Michel Dumontier
Abstract Developing personal data sharing tools and standards in conformity with data protection regulations is essential to empower citizens to control and share their health data with authorized parties for any purpose they approve. This can be, among others, for primary use in healthcare, or secondary use for research to improve human health and well-being. Ensuring that citizens are able to make
-
Publishing public transport data on the Web with the Linked Connections framework Semant. Web (IF 3.0) Pub Date : 2023-04-24 Julián Andrés Rojas, Harm Delva, Pieter Colpaert, Ruben Verborgh
Abstract Publishing transport data on the Web for consumption by others poses several challenges for data publishers. In addition to planned schedules, access to live schedule updates (e.g. delays or cancellations) and historical data is fundamental to enable reliable applications and to support machine learning use cases. However publishing such dynamic data further increases the computational burden
-
Building spatio-temporal knowledge graphs from vectorized topographic historical maps Semant. Web (IF 3.0) Pub Date : 2023-04-05 Basel Shbita, Craig A. Knoblock, Weiwei Duan, Yao-Yi Chiang, Johannes H. Uhl, Stefan Leyk
Abstract Historical maps provide rich information for researchers in many areas, including the social and natural sciences. These maps contain detailed documentation of a wide variety of natural and human-made features and their changes over time, such as changes in transportation networks or the decline of wetlands or forest areas. Analyzing changes over time in such maps can be labor-intensive for
-
Empowering machine learning models with contextual knowledge for enhancing the detection of eating disorders in social media posts Semant. Web (IF 3.0) Pub Date : 2023-03-13 José Alberto Benítez-Andrades, María Teresa García-Ordás, Mayra Russo, Ahmad Sakor, Luis Daniel Fernandes Rotger, Maria-Esther Vidal
Abstract Social networks have become information dissemination channels, where announcements are posted frequently; they also serve as frameworks for debates in various areas (e.g., scientific, political, and social). In particular, in the health area, social networks represent a channel to communicate and disseminate novel treatments’ success; they also allow ordinary people to express their concerns
-
Understanding the structure of knowledge graphs with ABSTAT profiles Semant. Web (IF 3.0) Pub Date : 2023-03-09 Blerina Spahiu, Matteo Palmonari, Renzo Arturo Alva Principe, Anisa Rula
Abstract While there has been a trend in the last decades for publishing large-scale and highly-interconnected Knowledge Graphs (KGs), their users often get overwhelmed by the task of understanding their content as a result of their size and complexity. Data profiling approaches have been proposed to summarize large KGs into concise and meaningful representations, so that they can be better explored
-
Towards a formal ontology of engineering functions, behaviours, and capabilities Semant. Web (IF 3.0) Pub Date : 2023-03-09 Francesco Compagno, Stefano Borgo
Abstract In both applied ontology and engineering, functionality is a well-researched topic, since it is through teleological causal reasoning that domain experts build mental models of engineering systems, giving birth to functions. These mental models are important throughout the whole lifecycle of any product, being used from the design phase up to diagnosis activities. Though a vast amount of work
-
Helio: A framework for implementing the life cycle of knowledge graphs Semant. Web (IF 3.0) Pub Date : 2023-01-12 Andrea Cimmino, Raúl García-Castro
Abstract Building and publishing knowledge graphs (KG) as Linked Data, either on the Web or in private companies, has become a relevant and crucial process in many domains. This process requires that users perform a wide number of tasks conforming to the life cycle of a KG, and these tasks usually involve different unrelated research topics, such as RDF materialisation or link discovery. There is already
-
An ontological approach for representing declarative mapping languages Semant. Web (IF 3.0) Pub Date : 2022-12-29 Ana Iglesias-Molina, Andrea Cimmino, Edna Ruckhaus, David Chaves-Fraga, Raúl García-Castro, Oscar Corcho
Abstract Knowledge Graphs are currently created using an assortment of techniques and tools: ad hoc code in a programming language, database export scripts, OpenRefine transformations, mapping languages, etc. Focusing on the latter, the wide variety of use cases, data peculiarities, and potential uses has had a substantial impact in how mappings have been created, extended, and applied. As a result
-
A systematic overview of data federation systems Semant. Web (IF 3.0) Pub Date : 2022-12-06 Zhenzhen Gu, Francesco Corcoglioniti, Davide Lanti, Alessandro Mosca, Guohui Xiao, Jing Xiong, Diego Calvanese
Abstract Data federation addresses the problem of uniformly accessing multiple, possibly heterogeneous data sources, by mapping them into a unified schema, such as an RDF(S)/OWL ontology or a relational schema, and by supporting the execution of queries, like SPARQL or SQL queries, over that unified schema. Data explosion in volume and variety has made data federation increasingly popular in many application
-
Learning SHACL shapes from knowledge graphs Semant. Web (IF 3.0) Pub Date : 2022-11-30 Pouya Ghiasnezhad Omran, Kerry Taylor, Sergio Rodríguez Méndez, Armin Haller
Abstract Knowledge Graphs (KGs) have proliferated on the Web since the introduction of knowledge panels to Google search in 2012. KGs are large data-first graph databases with weak inference rules and weakly-constraining data schemes. SHACL, the Shapes Constraint Language, is a W3C recommendation for expressing constraints on graph data as shapes. SHACL shapes serve to validate a KG, to underpin manual
-
The OneGraph vision: Challenges of breaking the graph model lock-in 1 Semant. Web (IF 3.0) Pub Date : 2022-11-30 Ora Lassila, Michael Schmidt, Olaf Hartig, Brad Bebee, Dave Bechberger, Willem Broekema, Ankesh Khandelwal, Kelvin Lawrence, Carlos Manuel Lopez Enriquez, Ronak Sharda, Bryan Thompson
Abstract Amazon Neptune is a graph database service that supports two graph models: W3C’s Resource Description Framework (RDF) and Labeled Property Graphs (LPG). Customers choose one or the other model. This choice determines which data modeling features can be used and – perhaps more importantly – which query languages are available. The choice between the two technology stacks is difficult and time
-
LSQ 2.0: A linked dataset of SPARQL query logs Semant. Web (IF 3.0) Pub Date : 2022-11-29 Claus Stadler, Muhammad Saleem, Qaiser Mehmood, Carlos Buil-Aranda, Michel Dumontier, Aidan Hogan, Axel-Cyrille Ngonga Ngomo
Abstract We present the Linked SPARQL Queries (LSQ) dataset, which currently describes 43.95 million executions of 11.56 million unique SPARQL queries extracted from the logs of 27 different endpoints. The LSQ dataset provides RDF descriptions of each such query, which are indexed in a public LSQ endpoint, allowing interested parties to find queries with the characteristics they require. We begin by
-
Is neuro-symbolic AI meeting its promises in natural language processing? A structured review Semant. Web (IF 3.0) Pub Date : 2022-11-09 Kyle Hamilton, Aparna Nayak, Bojan Božić, Luca Longo
Abstract Advocates for Neuro-Symbolic Artificial Intelligence (NeSy) assert that combining deep learning with symbolic reasoning will lead to stronger AI than either paradigm on its own. As successful as deep learning has been, it is generally accepted that even our best deep learning systems are not very good at abstract reasoning. And since reasoning is inextricably linked to language, it makes intuitive
-
Creating occupant-centered digital twins using the Occupant Feedback Ontology implemented in a smartwatch app Semant. Web (IF 3.0) Pub Date : 2022-11-08 Alex Donkers, Bauke de Vries, Dujuan Yang
Abstract Occupant feedback enables building managers to improve occupants’ health, comfort, and satisfaction. However, acquiring continuous occupant feedback and integrating this feedback with other building information is challenging. This paper presents a scalable method to acquire continuous occupant feedback and directly integrate this with other building information. Semantic web technologies
-
Food process ontology requirements Semant. Web (IF 3.0) Pub Date : 2022-11-04 Damion Dooley, Magalie Weber, Liliana Ibanescu, Matthew Lange, Lauren Chan, Larisa Soldatova, Chen Yang, Robert Warren, Cogan Shimizu, Hande K. McGinty, William Hsiao
Abstract People often value the sensual, celebratory, and health aspects of food, but behind this experience exists many other value-laden agricultural production, distribution, manufacturing, and physiological processes that support or undermine a healthy population and a sustainable future. The complexity of such processes is evident in both every-day food preparation of recipes and in industrial
-
ImageSchemaNet: A framester graph for embodied commonsense knowledge Semant. Web (IF 3.0) Pub Date : 2022-11-03 Stefano De Giorgis, Aldo Gangemi, Dagmar Gromann
Abstract Commonsense knowledge is a broad and challenging area of research which investigates our understanding of the world as well as human assumptions about reality. Deriving directly from the subjective perception of the external world, it is intrinsically intertwined with embodied cognition. Commonsense reasoning is linked to human sense-making, pattern recognition and knowledge framing abilities
-
MADLINK: Attentive multihop and entity descriptions for link prediction in knowledge graphs Semant. Web (IF 3.0) Pub Date : 2022-10-28 Russa Biswas, Harald Sack, Mehwish Alam
Abstract Knowledge Graphs (KGs) comprise of interlinked information in the form of entities and relations between them in a particular domain and provide the backbone for many applications. However, the KGs are often incomplete as the links between the entities are missing. Link Prediction is the task of predicting these missing links in a KG based on the existing links. Recent years have witnessed
-
Editorial of the Special Issue on Latest Advancements in Linguistic Linked Data Semant. Web (IF 3.0) Pub Date : 2022-09-26 Julia Bosque-Gil, Philipp Cimiano, Milan Dojchinovski
Abstract Since the inception of the Open Linguistics Working Group in 2010, there have been numerous efforts in transforming language resources into Linked Data. The research field of Linguistic Linked Data (LLD) has gained in importance, visibility and impact, with the Linguistic Linked Open Data (LLOD) cloud gathering nowadays over 200 resources. With this increasing growth, new challenges have emerged
-
Background knowledge in ontology matching: A survey Semant. Web (IF 3.0) Pub Date : 2022-09-08 Jan Portisch, Michael Hladik, Heiko Paulheim
Abstract Ontology matching is an integral part for establishing semantic interoperability. One of the main challenges within the ontology matching operation is semantic heterogeneity, i.e. modeling differences between the two ontologies that are to be integrated. The semantics within most ontologies or schemas are, however, typically incomplete because they are designed within a certain context which
-
Bilingual dictionary generation and enrichment via graph exploration Semant. Web (IF 3.0) Pub Date : 2022-09-07 Shashwat Goel, Jorge Gracia, Mikel L. Forcada
Abstract In recent years, we have witnessed a steady growth of linguistic information represented and exposed as linked data on the Web. Such linguistic linked data have stimulated the development and use of openly available linguistic knowledge graphs, as is the case with the Apertium RDF, a collection of interconnected bilingual dictionaries represented and accessible through Semantic Web standards
-
A survey on knowledge-aware news recommender systems Semant. Web (IF 3.0) Pub Date : 2022-09-06 Andreea Iana, Mehwish Alam, Heiko Paulheim
Abstract News consumption has shifted over time from traditional media to online platforms, which use recommendation algorithms to help users navigate through the large incoming streams of daily news by suggesting relevant articles based on their preferences and reading behavior. In comparison to domains such as movies or e-commerce, where recommender systems have proved highly successful, the characteristics
-
Characteristic sets profile features: Estimation and application to SPARQL query planning Semant. Web (IF 3.0) Pub Date : 2022-09-05 Lars Heling, Maribel Acosta
Abstract RDF dataset profiling is the task of extracting a formal representation of a dataset’s features. Such features may cover various aspects of the RDF dataset ranging from information on licensing and provenance to statistical descriptors of the data distribution and its semantics. In this work, we focus on the characteristics sets profile features that capture both structural and semantic information
-
Semantic Web technologies and bias in artificial intelligence: A systematic literature review Semant. Web (IF 3.0) Pub Date : 2022-09-05 Paula Reyero Lobo, Enrico Daga, Harith Alani, Miriam Fernandez
Abstract Bias in Artificial Intelligence (AI) is a critical and timely issue due to its sociological, economic and legal impact, as decisions made by biased algorithms could lead to unfair treatment of specific individuals or groups. Multiple surveys have emerged to provide a multidisciplinary view of bias or to review bias in specific areas such as social sciences, business research, criminal justice
-
RelTopic: A graph-based semantic relatedness measure in topic ontologies and its applicability for topic labeling of old press articles Semant. Web (IF 3.0) Pub Date : 2022-09-01 Mirna El Ghosh, Nicolas Delestre, Jean-Philippe Kotowicz, Cecilia Zanni-Merk, Habib Abdulrab
Abstract Graph-based semantic measures have been used to solve problems in several domains. They tend to compare semantic entities in order to estimate their similarity or relatedness. While semantic similarity is applicable to hierarchies or taxonomies, semantic relatedness is adapted to ontologies. In this work, we propose a novel semantic relatedness measure, named RelTopic, within topic ontologies
-
Analyzing biography collections historiographically as Linked Data: Case National Biography of Finland Semant. Web (IF 3.0) Pub Date : 2022-08-30 Minna Tamper, Petri Leskinen, Eero Hyvönen, Risto Valjus, Kirsi Keravuori
Abstract Biographical collections are available on the Web for close reading. However, the underlying texts can also be used for data analysis and distant reading, if the documents are available as data. Such data is usable for creating intelligent user interfaces to biographical data, including Digital Humanities tooling for visualizations, data analysis, and knowledge discovery in biographical and
-
Paving the way for enriched metadata of linguistic linked data Semant. Web (IF 3.0) Pub Date : 2022-08-29 Maria Pia di Buono, Hugo Gonçalo Oliveira, Verginica Barbu Mititelu, Blerina Spahiu, Gennaro Nolano
Abstract The need for reusable, interoperable, and interlinked linguistic resources in Natural Language Processing downstream tasks has been proved by the increasing efforts to develop standards and metadata suitable to represent several layers of information. Nevertheless, despite these efforts, the achievement of full compatibility for metadata in linguistic resource production is still far from
-
Security approaches for electronic health data handling through the Semantic Web: A scoping review Semant. Web (IF 3.0) Pub Date : 2022-08-29 Vinícius Costa Lima, Domingos Alves, Filipe Andrade Bernardi, Rui Pedro Charters Lopes Rijo
Abstract Integration of health information systems are crucial to advance the effective delivery of healthcare for individuals and communities across organizational boundaries. Semantic Web technologies may be used to connect, correlate, and integrate heterogeneous datasets spread over the internet. However, when working with sensitive data, such as health data, security mechanisms are needed. A scoping
-
Digital humanities on the Semantic Web: Sampo model and portal series Semant. Web (IF 3.0) Pub Date : 2022-08-29 Eero Hyvönen
Abstract Cultural heritage (CH) contents are typically strongly interlinked, but published in heterogeneous, distributed local data silos, making it difficult to utilize the data on a global level. Furthermore, the content is usually available only for humans to read, and not as data for Digital Humanities (DH) analyses and application development. This application report addresses these problems by
-
Blue Brain Nexus: An open, secure, scalable system for knowledge graph management and data-driven science Semant. Web (IF 3.0) Pub Date : 2022-08-30 Mohameth François Sy, Bogdan Roman, Samuel Kerrien, Didac Montero Mendez, Henry Genet, Wojciech Wajerowicz, Michaël Dupont, Ian Lavriushev, Julien Machon, Kenneth Pirman, Dhanesh Neela Mana, Natalia Stafeeva, Anna-Kristin Kaufmann, Huanxiang Lu, Jonathan Lurie, Pierre-Alexandre Fonta, Alejandra Garcia Rojas Martinez, Alexander D. Ulbrich, Carolina Lindqvist, Silvia Jimenez, David Rotenberg, Henry Markram
Abstract Modern data-driven science often consists of iterative cycles of data discovery, acquisition, preparation, analysis, model building and validation leading to knowledge discovery as well as dissemination at scale. The unique challenges of building and simulating the whole rodent brain in the Swiss EPFL Blue Brain Project (BBP) required a solution to managing large-scale highly heterogeneous
-
Move cultural heritage knowledge graphs in everyone’s pocket Semant. Web (IF 3.0) Pub Date : 2022-08-29 Maria Angela Pellegrino, Vittorio Scarano, Carmine Spagnuolo
Abstract Last years witnessed a shift from the potential utility in digitisation to a crucial need to enjoy activities virtually. In fact, before 2019, data curators recognised the utility of performing data digitisation, while during the lockdown caused by the COVID-19, investing in virtual and remote activities to make culture survive became crucial as no one could enjoy Cultural Heritage in person
-
Typed properties and negative typed properties: Dealing with type observations and negative statements in the CIDOC CRM Semant. Web (IF 3.0) Pub Date : 2022-08-29 Athanasios Velios, Carlo Meghini, Martin Doerr, Stephen Stead
Abstract A typical case of producing records within the domain of conservation of cultural heritage is considered. During condition and collection surveys in memory organisations, surveyors observe types of multiple components of an object but without creating a record for each one. They also observe the absence of components. Such observations are significant to researchers and are documented in registration
-
MTab4D: Semantic annotation of tabular data with DBpedia Semant. Web (IF 3.0) Pub Date : 2022-08-25 Phuc Nguyen, Natthawut Kertkeidkachorn, Ryutaro Ichise, Hideaki Takeda
Abstract Semantic annotation of tabular data is the process of matching table elements with knowledge graphs. As a result, the table contents could be interpreted or inferred using knowledge graph concepts, enabling them to be useful in downstream applications such as data analytics and management. Nevertheless, semantic annotation tasks are challenging due to insufficient tabular data descriptions
-
Morph-KGC: Scalable knowledge graph materialization with mapping partitions Semant. Web (IF 3.0) Pub Date : 2022-08-25 Julián Arenas-Guerrero, David Chaves-Fraga, Jhon Toledo, María S. Pérez, Oscar Corcho
Abstract Knowledge graphs are often constructed from heterogeneous data sources, using declarative rules that map them to a target ontology and materializing them into RDF. When these data sources are large, the materialization of the entire knowledge graph may be computationally expensive and not suitable for those cases where a rapid materialization is required. In this work, we propose an approach
-
Transdisciplinary approach to archaeological investigations in a Semantic Web perspective Semant. Web (IF 3.0) Pub Date : 2022-08-22 Vincenzo Lombardo, Tugce Karatas, Monica Gulmini, Laura Guidorzi, Debora Angelici
Abstract In recent years, the transdisciplinarity of archaeological studies has greatly increased because of the mature interactions between archaeologists and scientists from different disciplines (called “archaeometers”). A number of diverse scientific disciplines collaborate to get an objective account of the archaeological records. A large amount of digital data support the whole process, and there
-
Semantic models and services for conservation and restoration of cultural heritage: A comprehensive survey Semant. Web (IF 3.0) Pub Date : 2022-08-22 Efthymia Moraitou, Yannis Christodoulou, George Caridakis
Abstract Over the last decade, the Cultural Heritage (CH) domain has gradually adopted Semantic Web (SW) technologies for organizing information and for tackling interoperability issues. Several semantic models have been proposed which accommodate essential aspects of information management: retrieval, integration, reuse and sharing. In this context, the CH subdomain of Conservation and Restoration
-
Generation of training data for named entity recognition of artworks Semant. Web (IF 3.0) Pub Date : 2022-08-08 Nitisha Jain, Alejandro Sierra-Múnera, Jan Ehmueller, Ralf Krestel
Abstract As machine learning techniques are being increasingly employed for text processing tasks, the need for training data has become a major bottleneck for their application. Manual generation of large scale training datasets tailored to each task is a time consuming and expensive process, which necessitates their automated generation. In this work, we turn our attention towards creation of training
-
Linking discourse-level information and the induction of bilingual discourse connective lexicons Semant. Web (IF 3.0) Pub Date : 2022-06-20 Sibel Özer, Murathan Kurfalı, Deniz Zeyrek, Amália Mendes, Giedrė Valūnaitė Oleškevičienė
Abstract The single biggest obstacle in performing comprehensive cross-lingual discourse analysis is the scarcity of multilingual resources. The existing resources are overwhelmingly monolingual, compelling researchers to infer the discourse-level information in the target languages through error-prone automatic means. The current paper aims to provide a more direct insight into the cross-lingual variations