Adoption Of Web Technologies Research Articles

Enhancing News Articles: Automatic SEO Linked Data Injection for Semantic Web Integration

This paper presents a novel solution aimed at enhancing news web pages for seamless integration into the Semantic Web. By utilizing advanced pattern mining techniques alongside OpenAI’s GPT-3, we rewrite news articles to improve their readability and accessibility for Google News aggregators. Our approach is characterized by its methodological rigour and is evaluated through quantitative metrics, validated using Google’s Rich Results Test API to confirm adherence to Google’s structured data guidelines. In this process, a “Pass” in the Rich Results Test is taken as an indication of eligibility for rich results, demonstrating the effectiveness of our generated structured data. The impact of our work is threefold: it advances the technological integration of a substantial segment of the web into the Semantic Web, promotes the adoption of Semantic Web technologies within the news sector, and significantly enhances the discoverability of news articles in aggregator platforms. Furthermore, our solution facilitates the broader dissemination of news content to diverse audiences. This submission introduces an innovative solution substantiated by empirical evidence of its impact and methodological soundness, thereby making a significant contribution to the field of Semantic Web research, particularly in the context of news and media articles.

Recording gender in the person entity

The discussion on the gender registration of person-type entities (agents) is part of the broader context of new approaches to bibliographic cataloguing proposed by libraries' adoption of web technologies and languages. Cataloguing is increasingly becoming an activity of identifying and describing entities, with their multiple faces, or even through the different points of view from which that entity can be observed (entity modelling). Identifying the boundary of an entity and the different profiles with which it can present itself to the world becomes one of the most complex and significant moments in the new way of cataloguing resources. The profile of a person-type entity is traced by identifying its characteristics and extending the investigation to relations with other entities. The reflection on the effectiveness of intrinsic properties and extrinsic or relational properties in identifying an entity introduces the topic of the registration of the property relating to the gender of a person, a topic widely discussed in the library and web community. The study analyses the positions taken on this issue by two communities active in the cataloguing field, the PCC Ad Hoc Task Group on Gender in Authority Records and the ISNI International Agency, with references also to the positions expressed on the same issue by the Wikidata community.

Digitalisation in European regions: unravelling the impact of relatedness and complexity on digital technology adoption and productivity growth

ABSTRACT Digital technologies are the cornerstone of platform, knowledge, and network economies, driving the interconnectedness, innovation, and efficiency that define these economic models. Consequently, digitalisation has recently become a key policy objective for regional economies. This paper provides empirical evidence on how the adoption of new digital web technologies is shaped by previous regional digital capabilities. The analysis is based upon an economic complexity and relatedness framework using novel data on digital web technologies’ adoption for 278 European NUTS-2 regions between the years 2000 and 2022. Results show that regions tend to adopt new digital web technologies when they already master related digital capabilities. This paper also shows how digital complexity is associated with labour productivity gains at the regional level. Conclusions shed light on how regions adopt digital web technologies and serve as a tool for policymakers.

FAIR and Structured Data: A Domain Ontology Aligned with Standard‐Compliant Tensile Testing

The digitalization of materials science and engineering (MSE) is currently leading to remarkable advancements in materials research, design, and optimization, fueled by computer‐driven simulations, artificial intelligence, and machine learning. While these developments promise to accelerate materials innovation, challenges in quality assurance, data interoperability, and data management have to be addressed. In response, the adoption of semantic web technologies has emerged as a powerful solution in MSE. Ontologies provide structured and machine‐actionable knowledge representations that enable data integration, harmonization, and improved research collaboration. This study focuses on the tensile test ontology (TTO), which semantically represents the mechanical tensile test method and is developed within the project Plattform MaterialDigital (PMD) in connection with the PMD Core Ontology. Based on ISO 6892‐1, the test standard‐compliant TTO offers a structured vocabulary for tensile test data, ensuring data interoperability, transparency, and reproducibility. By categorizing measurement data and metadata, it facilitates comprehensive data analysis, interpretation, and systematic search in databases. The path from developing an ontology in accordance with an associated test standard, converting selected tensile test data into the interoperable resource description framework format, up to connecting the ontology and data is presented. Such a semantic connection using a data mapping procedure leads to an enhanced ability of querying. The TTO provides a valuable resource for materials researchers and engineers, promoting data and metadata standardization and sharing. Its usage ensures the generation of finable, accessible, interoperable, and reusable data while maintaining both human and machine actionability.

Knowledge Representation and The Semantic Web: An Historical Overview of Influences on Emerging Tools

Abstract: suite of standards known as the Semantic Web is transforming the Internet into a semantic graph rather than a graph of hypertext links. This paper will describe how various ideas and initiatives in artificial intelligence knowledge representation influenced its design. We begin with the seminal work by Alan Turing and Alonzo Church that led to the definition of Turing Machines, enabled digital computing, and provided the mathematical theory of computation, which has been one of the determining factors for Artificial Intelligence knowledge representation. We then provide a brief history of artificial intelligence knowledge representation, starting with groundbreaking researchers, such as Newell and Simon, then to the first "AI boom" driven primarily by rule-based expert systems, followed by major initiatives such as Cyc and the DARPA Knowledge Sharing Initiative. We will discuss how innovations from these initiatives affected standards that, in turn, led to the suite of standards known as the Semantic Web. We conclude with a brief overview of the most important issues currently facing those who wish to see widespread adoption of Semantic Web technology in the industry.

Building linked lexicography applications with LexO-server

Abstract The adoption of Semantic Web technologies in the lexicographic field, has been driven by the need to ensure the construction of lexical resources that are interoperable and can be shared and reused by the scientific communities. In this context, the OntoLex W3C working group proposed the OntoLex-Lemon model aimed at providing rich linguistic grounding for ontologies. It includes the representation of morphological and syntactic properties of lexical entries as well as their meaning with respect to an ontology or vocabulary. This article aims at presenting LexO-server, a set of REST services for the management of OntoLex-Lemon modeled lexical resources. LexO-server comes as a software backend providing data access and manipulation to frontend developers. The set of services are general enough to make possible the construction of applications oriented at different tasks, such as editing, linking, dictionary making, linguistic annotation, or NLP ones. As a demonstration of the versatility and the potential of LexO-server, we will present three web applications that rely on it.

Does Social Media use Impact Small Agribusiness Exploitation and Exploration Capability? Perspectives and Recommendations from the UT of J&K

For businesses functioning in complex environments where destabilizing factors are exacerbated, ambidexterity, or the ability of an organization to exploit and explore, becomes essential. Due to this, businesses are on the lookout for newer procedures that are practical both now and in the future. The utilization of digital and social media for marketing forms a subset of such practices that are contemporary yet pervasive. In fact, Whatsapp and Facebook have become the spearhead platforms for information dissemination, relationship building, and transaction handling for businesses around the globe. While considerable research provides insights into the adoption and acceptance of web technologies in different sectors, studies investigating the role of social media in developing dynamic capabilities for agribusinesses are scarce. Data inputs were drawn from 73 agribusinesses primarily using a quantitative approach and interpreted using partial least squares structural equation modeling (PLS-SEM) to address this issue. A qualitative inquiry through post-survey interviews was also used to strengthen the research outcomes. The findings pointed out that social media use results in greater exploitation over exploration capabilities in the study area. The possible reasons for this one-sided usage, such as lack of awareness and technical and human incapacities are explored, and a suggestion for developing ambidexterity is presented. The study’s outcome can help small business owners, employees, and the government capitalize on the different social technology tools to their most significant advantage.

A core ontology for modeling life cycle sustainability assessment on the Semantic Web

AbstractThe use of Semantic Web and linked data increases the possibility of data accessibility, interpretability, and interoperability. It supports cross‐domain data and knowledge sharing and avoids the creation of research data silos. Widely adopted in several research domains, the use of the Semantic Web has been relatively limited with respect to sustainability assessments. A primary barrier is that the framework of the principles and technologies required to link and query data from the Semantic Web is often beyond the scope of industrial ecologists. Linking of a dataset to Semantic Web requires the development of a semantically linked core ontology in addition to the use of existing ontologies. Ontologies provide logical meaning to the data and the possibility to develop machine‐readable data format. To enable and support the uptake of semantic ontologies, we present a core ontology developed specifically to capture the data relevant for life cycle sustainability assessment. We further demonstrate the utility of the ontology by using it to integrate data relevant to sustainability assessments, such as EXIOBASE and the Yale Stocks and Flow Database to the Semantic Web. These datasets can be accessed by the machine‐readable endpoint using SPARQL, a semantic query language. The present work provides the foundation necessary to enhance the use of Semantic Web with respect to sustainability assessments. Finally, we provide our perspective on the challenges toward the adoption of Semantic Web technologies and technical solutions that can address these challenges.

KNOWLEDGE GRAPH CONSTRUCTION FOR SUBSURFACE OBJECTS INCLUDING UNCERTAINTY AND TIME VARIATION

Abstract. In the recent years the concept of knowledge graph has emerged as a way to aggregate information from various sources without imposing too strict data modelling constraints. Several graph models have been proposed during the years, ranging from the “standard” RDF to more expressive ones, such as Neo4J and RDF-star. The adoption of knowledge graph has become established in several domains. It is for instance the case of the 3D geoinformation domain, where the adoption of semantic web technologies has led to several works in data integration and publishing. However, yet there is not a well-defined model or technique to represent 3D geoinformation including uncertainty and time variation in knowledge graphs. In this paper we propose a model to represent parameterized geometries of subsurface objects. The vocabulary of the model has been defined as an OWL ontology and it extends existing ontologies by adding classes and properties to represent the uncertainty and the spatio-temporal behaviour of a geometry, as well as additional attributes, such as the data provenance. The model has been validated on significant use cases showing different types of uncertainties on 3D subsurface objects. A possible implementation is also presented, using RDF-star for the data representation.

Corago in LOD. The debut of an Opera repository into the Linked Data arena

The paper examines the adoption of the Semantic Web (SW) technologies and Linked Data (LD) principles to manage a knowledge base about opera. The Corago repository collects historical data and documentation about opera works, performances and librettos from the 16th to the 20th century. We experimented the use of semantic technologies to manage the repository’s knowledge catalogued following the Functional Requirements for Bibliographic Records (FRBR) relational model. Cultural Heritage Knowledge Bases (CHKB) as Corago could leverage SW and LD to overcome proprietary models and to introduce new information to better satisfy user’s requirements. Two well-established reference ontologies as CIDOC Conceptual Reference Model (CIDOC CRM) and FRBR Object Oriented (FRBRoo) are adopted to transpose contents form the legacy conceptual model to RDF. Through the process, we observed that formal semantics allow, not only to adequately represent the opera domain, but also enable to define the way information is being presented to users. This led to the definition of “reception pathways” which become themselves part of the knowledge about opera within the KB. This novel semantic approach is introduced with the Corago Semantic Model (Corago SM), a domain ontology dedicated to functional representation of opera’s historical data. Advancements have been tested with an experimental system and assessed through a questionnaire submitted to a panel of users.

A study of librarians' perceptions and adoption of Web 2.0 technologies in academic libraries in Akwa Ibom State, Nigeria

This paper surveyed the librarians' perceptions and adoption of Web 2.0 technologies in academic libraries in public institutions in Akwa Ibom State, Nigeria. The study specifically examined the constructs of librarians' perceptions of Web 2.0 Technologies in line with a model modified by the researcher; assessed the Web 2.0 tools adopted in the libraries; and identified the constraints to the adoption of the Web 2.0 technologies in the six (6) academic libraries in public institutions in Akwa Ibom State, Nigeria. The entire population was 60 professional librarians with at least a bachelor's degree in Library and Information Science. The study targeted professional librarians because it is assumed they have the qualifications, experience and exposure needed in the adoption of Web technologies. The population was used as sample since the size was small and manageable. The data collected using researcher-developed questionnaire was analyzed with descriptive statistics in form of frequency counts, simple percentage and chart. The findings revealed that majority of librarians have the perception that Web 2.0 technologies are useful and could enhance their job performance; that Web tools are clear and easy to understand; that fellow librarians, library users, host institutions, etc., expect them to use the tools. However, the result showed a low level of web technologies adoption across the libraries. The major constraints to adoption of Web 2.0 technologies in academic libraries in Akwa Ibom State include high cost of technology, poor access to web tools, budget constraints, inadequate training for librarians, and restrictive ICT policies. The recommendations made were proper funding, staff training and re-training, update of library facilities to include web 2.0 offerings, etc. Areas for further studies were also suggested.

Fine-Grained, Aspect-Based Sentiment Analysis on Economic and Financial Lexicon

The last two decades have seen a tremendous increase in the adoption of Semantic Web technologies as a result of the availability of big data, the growth in computational power and the advancement of artificial intelligence (AI) technologies. Cutting-edge semantic techniques are now able to capture sentiments more accurately in various practical applications, including economic and financial forecasting. In particular, the extraction of sentiment from news text, social media and blogs for the prediction of economic and financial variables has attracted attention in recent years. Despite many successful applications of sentiment analysis (SA) in these domains, the range of semantic techniques employed is still limited and mostly focused on the detection of sentiment at a coarse-grained level, that is, whether the sentiment expressed by the entire text of a sentence is either positive or negative. This paper proposes a novel methodology for Fine-Grained Aspect-based Sentiment (FiGAS) analysis. The aim of the approach is to identify the sentiment associated to specific topics of interest in each sentence of a document and assigning real-valued polarity scores between -1 and +1 to those topics. The proposed approach is completely unsupervised and customized to the economic and financial domains by using a specialized lexicon make available along with the source code of FiGAS. Our lexicon-based SA approach relies on a detailed set of semantic polarity rules that allow understanding the origin of sentiment, in the spirit of the recent trend on \textit{Interpretable AI}. We provide an in-depth comparison of the performance of the FiGAS algorithm relative to other popular lexicon-based SA approaches in predicting a humanly annotated data set in the economic and financial domains. Our results indicate that FiGAS statistically outperforms the other methods by providing a sentiment score that is closer to one of the human annotators.

Формальные правила продукции объектной нотации для данных, определяемых EXPRESS схемой

Recently, product data management systems (PDM) are widely used to conduct complex multidisciplinary projects in various industrial domains. The PDM systems enable teams of designers, engineers, and managers to remotely communicate on a network, exchange and share common product information. To integrate CAD/CAM/CAE applications with the PDM systems and ensure their interoperability, a dedicated family of standards STEP (ISO 10303) has been developed and employed. The STEP defines an object-oriented language EXPRESS to formally specify information schemas as well as file formats to store and transfer product data driven by these schemas. These are clear text encoding format SPF and STEP-XML. Nowadays, with the development and widespread adoption of Web technologies, the JSON language is getting increasingly popular due to it being apropos for the tasks of object-oriented data exchange and storage, as well as its simple, easy to parse syntax. The paper explores the topic of the suitability of the JSON language for the unambiguous representation, storage and interpretation of product data. Under the assumption that the product data can be described by arbitrary information schemas in EXPRESS, formal rules for the producing JSON notation are proposed and presented. Explanatory examples are provided to illustrate the proposed rules. The results of computational experiments conducted confirm the advantages of the JSON format compared to SPF and STEP-XML, and motivate its widespread adoption when integrating software applications.

Enhancing bibliographic records in academic library catalogs: An empirical study

AbstractThis poster presents preliminary findings of a study which examines users' needs and requirements for bibliographic enhancement data (B.E.D.) in academic library catalogs. Qualitative data were collected through eight participants' activity logs and follow‐up interviews. This study identified 17 types of B.E.D. useful for supporting the user tasks defined in the Library Reference Model and in six other contexts, such as enhancing users' reading interpretation. Participants reported nine quality criteria important for B.E.D. Findings suggest that adoption of BIBFRAME and Semantic Web technologies may enable academic library catalogs to provide B.E.D. to support users in various contexts.

Determinants of semantic web technology adoption from IT professionals’ perspective: Industry competition, organization innovativeness, and data management capability

Determinants of semantic web technology adoption from IT professionals’ perspective: Industry competition, organization innovativeness, and data management capability

A framework development for the adoption of information and communication technology web technologies in higher education systems

Background: The adoption of information and communication technology (ICT) tools into educational systems has been at the forefront of the educational sector for decades. The integration of Web 2.0 and Web 3.0 technologies is progressively being encouraged worldwide across several universities to support teaching and learning processes and to offer students the possibility of learning experiences and engagements to suit their digital needs. Objectives: This article probes a framework development for the adoption of ICT web technologies in higher education systems (HES) and further suggests a framework for adoption with the aim of enhancing the mode of education delivery and improving business processes. An understanding of the benefits associated with Web 2.0 and Web 3.0 tools adoption is gained to support collaboration between students and educators and to build social presence through interactive learning. South African universities continue to experience circumstances in which many learners who enrol are novice users of Web 2.0 and Web 3.0 tools and require optimal support to bridge the gaps and the knowledge and skills exposure required. The problem with educators’ inability to incorporate Web 2.0 and Web 3.0 tools in their teaching and learning practices exists. Method: A mixed-method approach was applied in this study. The researchers conducted 15 separate interviews with educators coupled with randomly distributed questionnaires to students across three universities (North-West University [NWU], University of South Africa [UNISA] and University of Pretoria [UP]), a total of 969 was recoverable and analysed using analytical tool ATLAS.ti and SPSS. The researchers further validated the data consolidating both techniques used to generate a holistic assessment of the data analysed from the quantitative to support the qualitative findings. Results: Findings revealed that these tools are useful and will have a positive effect on the pedagogical environment, although there are challenges that may be considered during the adoption. These challenges relate to human factors (e.g. technophobia and cultural beliefs), security issues (e.g. privacy and intellectual property rights [IPRs]), ethical and legal issues, ICT infrastructures (e.g. cost implication, risk and ICT teaching facilities); and university policy frameworks. Conclusion: Despite these challenges, Web 2.0 and Web 3.0 technologies in HES offer varieties of teaching and learning platforms and an improved business administration process.

Using Semantic Web technologies in the development of data warehouses: A systematic mapping

The exploration and use of Semantic Web technologies have attracted considerable attention from researchers examining data warehouse (DW) development. However, the impact of this research and the maturity level of its results are still unclear. The objective of this study is to examine recently published research articles that take into account the use of Semantic Web technologies in the DW arena with the intention of summarizing their results, classifying their contributions to the field according to publication type, evaluating the maturity level of the results, and identifying future research challenges. Three main conclusions were derived from this study: (a) there is a major technological gap that inhibits the wide adoption of Semantic Web technologies in the business domain;(b) there is limited evidence that the results of the analyzed studies are applicable and transferable to industrial use; and (c) interest in researching the relationship between DWs and Semantic Web has decreased because new paradigms, such as linked open data, have attracted the interest of researchers.This article is categorized under: Fundamental Concepts of Data and Knowledge > Information Repositories Fundamental Concepts of Data and Knowledge > Knowledge Representation Algorithmic Development > Web Mining

Profiling Web Technology Adoption of English Language Instructors in Malaysian Universities

Undeniably the use of web technology in language teaching and learning has advanced by leaps and bounds. It not only provides effective learning experiences to the present digitally-inclined students but also assists teachers in creating interesting content and activities as well as in monitoring and evaluating students. Teachers at all educational levels employ web technology in their teaching. However, it has been reported that its potential has not been fully reaped. This paper presents findings from a study investigating the nature and extent of web technologies used by Malaysian tertiary English language instructors. The aim was to examine the nature and extent of using such tools in language teaching. Profiling the web technology adoption by these instructors would provide insights on the degree of use and the range of web potentialities that has been explored; providing vital information to all key players regarding support and training needs, among others. The findings of the study revealed that the English instructors employed a myriad of web tools. They demonstrated a high level of use of these tools for teaching but only a medium level for communication and evaluation.

Exploring Determinants of Semantic Web Technology Adoption from IT Professionals' Perspective: Industry Competition, Organization Innovativeness, and Data Management Capability

The scale and complexity of big data quickly exceed the reach of direct human comprehension and increasingly require machine assistance to semantically analyze, organize, and interpret vast and diverse sources of big data in order to unlock its strategic value. Due to its volume, velocity, variety, and veracity, big data integration challenges overwhelm traditional integration approaches leaving many integration possibilities out of reach. Unlocking the value of big data requires innovative technology. Organizations must have the innovativeness and data capability to adopt the technology and harness its potential value. The Semantic Web (SW) technology has demonstrated its potential for integrating big data and has become important technology for tackling big data. Despite its importance to manage big data, little research has examined the determinants affecting SW adoption. Drawing upon the technology–organization–environment framework as a theory base, this study develops a research model explaining the factors affecting the adoption of SW technology from IT professionals' perspective, specifically in the context of corporate computing enterprises. We validate the proposed model using a set of empirical data collected from IT professionals including IT managers, system architects, software developers, and web developers. The findings suggest that perceived usefulness, perceived ease of use, organization's innovativeness, organization's data capability, and applicability to data management are important drivers of SW adoption. This study provides new insights on theories of organizational IT adoption from IT professionals' perspectives tailored to the context of SW technology.

A Web of Things Framework for RESTful Applications and Its Experimentation in a Smart City

The Web of Things is an active research field which aims at promoting the easy access and handling of smart things' digital representations through the adoption of Web standards and technologies. While huge research and development efforts have been spent on lower level networks and software technologies, it has been recognized that little experience exists instead in modeling and building applications for the Web of Things. Although several works have proposed Representational State Transfer (REST) inspired approaches for the Web of Things, a main limitation is that poor support is provided to web developers for speeding up the development of Web of Things applications while taking full advantage of REST benefits. In this paper, we propose a framework which supports developers in modeling smart things as web resources, exposing them through RESTful Application Programming Interfaces (APIs) and developing applications on top of them. The framework consists of a Web Resource information model, a middleware, and tools for developing and publishing smart things' digital representations on the Web. We discuss the framework compliance with REST guidelines and its major implementation choices. Finally, we report on our test activities carried out within the SmartSantander European Project to evaluate the use and proficiency of our framework in a smart city scenario.