Natural Language Annotations for the Semantic Web

PurposeThe purpose of this paper is to explore useful Semantic Web technologies and ontology-based applications for digital libraries. It also investigates the perceptions of university librarians and academicians in Pakistan about Semantic Web technologies and their use in digital libraries.Design/methodology/approachAn exploratory research design based on Delphi research strategy was conducted to answer the research questions. Interviews were conducted with a purposive sample of 50 key informants including university librarians and academicians to explore their perceptions about Semantic Web technologies and their use in digital libraries. Thematic analysis of interview data was conducted to obtain results.FindingsThe results of this paper showed that DuraCloud, Semantic information mashup, OntoEdit and resource description framework (RDF) are the various Semantic Web applications which are useful for digital libraries to develop semantic relationships among digital contents and increase their accessibility in the web environment. Findings revealed that Semantic Web provides precise results and meets user information needs in an effective way. Results also showed that next-generation digital libraries use context-awareness technology, intelligent agent software and detecting sensors to analyze user information needs and provide dynamic information services. This paper recommended that librarians should embrace the use of emerging web technologies in libraries and offer library services through the medium of the web.Practical implicationsThis paper envisaged the future of digital library services and Semantic Web applications that can be used to re-structure metadata of digital library. This paper has practical implications for librarians to consider the useful applications of Semantic Web for digital library and enhance the interoperability of metadata among heterogeneous information systems. Practically, results obtained from this paper are highly useful for library schools and LIS teachers to up-date their curriculum by incorporating new contents related to web languages and Semantic Web applications for digital libraries.Originality/valueThis paper identifies various Semantic Web applications which are useful for developing Semantic Digital Libraries.

EUROLAN, which has been held biennially since 1993, is one of the most significant European summer schools in the area of natural language processing. Each of the EUROLAN sessions has focused on an area of timely interest to researchers in the field; this year's EUROLAN involved students in tutorials and hands-on sessions concerned with semantic web technologies as applied to language processing, ontology creation and use, and consideration of the semantic web's potential and limitations.

With the development of information technology, the resource description framework (RDF) occupies very important position in structure of the semantic web. An effective way to enhance the efficiency of the RDF data query is RDF closures. Our work is improve the RDF reasoning in MapReduce framework. The algorithm is based on packet classification efficiency of a few of candidate rules, as well as the NoSQL data storage avoiding repetition, corresponding to the RDF properties and concepts. The optimization algorithm of MapReduce is given a new closure generation process. Our approach use RDFS inference rules and the RDF triples in relationship between Map and Reduce operations and generate the RDF closures, improve the generate efficiency of closure. Based on RDF MapReduce algorithm for RDF closure, look forward more suitable RDF closure computing scheme on cloud computing environment.

Ontology is adopted as a standard for knowledge representation on the Semantic Web, and Resource Description Framework (RDF) is used to add structure and meaning to Web applications. In order to incorporate fuzzy systems into the Semantic Web, this paper utilizes fuzzy ontology to represent formally the fuzzy linguistic variables, considering the semantic relationships between fuzzy concepts. Then fuzzy rule is described as a RDF resource with properties: “IF” and “THEN”, and rule's antecedent and consequent is represented in RDF statement. Taking the fuzzy control system of industrial washing machine for example, the fuzzy system with ontology and RDF is built, which shows that this research enables distributed fuzzy applications on the Semantic Web.

A semi-automatic system to evaluate the performance and scalability of ontology persistent APIs

Availability at large-scale semantic web data can be considered as an opportunity to be used in data source analysis. This analysis process might not obtain data as required since the data is extracted from external sources. This incompleteness of data source can affect analysis result. To resolve this problem, this paper proposed a method for generating data from a transformation process that built based on semantic web technology (ontologies). The application will apply an algorithm that can find a superclass and a subclass of superclass ontology, by mapping the instances of relevant object property to the ontology classes. The classes are then added to the source as a data object instances. In the mapping process, the data is represented by using semi structured format RDF (Resource Description Framework). Data instances generated from this mapping process will complete the semantic data sources and then support the analysis process.

In the Semantic Web, items are represented by uniform resource identifiers (URIs) on the Web in order to describe relationships between things in resource description framework (RDF) graphs. Large scale open RDF data (linked data) describing information about various things are available. Hence, relational discovery research has been conducted using RDF data to explore relationships between things. The SPARQL protocol and RDF query language (SPARQL) is usually employed to process RDF data; however, SPARQL is not suitable for relational discovery using linked data because it is difficult to describe unknown vocabularies and relationships in SPARQL queries. In this paper, we propose an aggregation path search for RDF graphs as an extension of shortest path keyword search. The aggregation path search is devised to find RDF paths by merging multiple resource URIs into commonly reachable nodes in an RDF graph. This search method can discover new relationships between items that are connected by a common node. We present a method for treating equivalent resource URIs as a single resource URI; these equivalent URIs essentially represent the same thing based on equivalence relations in different RDF datasets. In our experiments, we show in the integration of multiple large scale RDF datasets that the integration of equivalent resources enables richer retrieval of aggregated paths.

Resource Description Framework (RDF) and SPARQL are some of the common terms we hear with the Semantic Web. RDF is the de-facto standard for data representation on the Semantic Web. The universal adoption of this standard can be attributed to the fact that it has a flexible model. Due to the widespread adoption of Semantic web, a sudden steep increase in the amount of RDF data has been witnessed. This massive volume of RDF data can't be handled by the traditional Centralized RDF management systems. Thus comes into the picture the need for Distributed RDF data management systems which can distribute this RDF data on a cluster of nodes. So, the bottlenecks of the Centralized RDF systems regarding volume and efficient querying can be overcome. This paper presents a detailed description and comparison of the different Centralized and Distributed RDF data management systems.

Internet search is done by exploring the link and keyword frequency. In 2012, Google released Knowledge Graph --Semantic Web. The human reasoning can be enhanced by the use semantic web an emerging area. Most of the current applications link open data views due to which there is huge flow of data in semantic web, particularly Resource Description Framework (RDF) data. In the semantic web research community this leads to design and development of scalable data processing techniques for RDF data. The aim of semantic web is to make available semantically connected data across the globe. This is a review paper giving analysis of techniques implemented to achieve the aim of semantic web, various approaches to processes RDF data. Within the semantic web community, RDF is a common acronym because it forms one of the basic building blocks for forming the web of semantic data, called a graph database. This paper compares various methodologies followed by different researchers along with the results analysis of implemented techniques over different datasets.

Semantic Web for Health Care and Life Sciences: a review of the state of the art

Business Intelligence (BI) plays important roles in executive decision making in organizations. Up-to-date information from good data sources always gives advantages to the organization. Nowadays, information in Semantic Webs is considered important source of BI data. It provides machine readable information using the Resource Description Framework (RDF). To perform BI activities on RDF documents, many research works propose direct mining on RDF documents. This paper presents a different approach for preparing BI project information from RDF data sources. A conceptual meta schema is used to describe RDF information. The meta schema is transformed into meta tables which are used to keep both RDF schema and document information. A transformation algorithm is proposed to transform the information into 5NF relational database Schemas and relations which are finally transformed into BI project data structures.

Decision-making based on so-called medical guidelines supported by semantic AI solutions is an essential and significant task for medical personnel in both a pre-clinical setting and an inner-clinical environment. Semantic representations of medical guidelines and Fast Healthcare Interoperability Resources (FHIR) using Semantic Web technologies, i.e., Resource Description Framework (RDF), rules (RuleML and Prova), and Shape Constraint Language (SHACL), provide a semantic knowledge base for the decision-making process and ease technical implementation and automation tasks. Current medical decision support systems lack Semantic Web integration using FHIR-RDF representations as a data source. In this paper, we implement a particular medical guideline using two different approaches: Prova [8] and SHACL [13]. We generate a series of raw FHIR-data for a selected guideline, the ABCDE approach, and compare the implemented two programs' (Prova and SHACL) results. Both approaches deliver the same results in terms of content. Both may be used within a distributed medical environment depending on the need of organizations.

The traditional Web stores huge amount of data in the form of Relational Databases (RDB) as it is good at storing objects and relationships between them.Relational Databases are dynamic in nature which allows bringing tables together helping user to search for related material across multiple tables.RDB are scalable to expand as the data grows.The RDB uses a Structured Query Language called SQL to access the databases for several data retrieval purposes.As the world is moving today from the Syntactic form to Semantic form and the Web is also taking its new form of Semantic Web.The Structured Query of the RDB on web can be a Semantic Query on Semantic Web.The SPARQL is the Query Language recommended by W3C for the RDF(Resource Description Framework).RDF is a directed, labeled graph data format for representing information in the Web and is a very important layer of the Semantic Web Architecture.In this paper we consider the Library Management System (LMS) database, taking some tuples of the LMS Relational Schema.We discuss how the RDF code is scripted and validated using RDF Validator and how RDF Triples are generated.Later we give the graphical representation of the RDF triples and see the process of extracting ontology from the RDF Schema and application of the Semantic Query.

The Internet is not just used for communication, transactions, and cloud storage; it also serves as a massive knowledge store where both people and machines can create, analyze, and use data and information. The Semantic Web was designed to enable machines to interpret the meaning of data, facilitating more informed and autonomous decision-making. The foundation of the Semantic Web is the Resource Description Framework (RDF). The standard RDF is limited to representing simple binary relationships in the form of the <subjectpredicateobject> triple. In this paper, we present a new data model called BiTemporal RDF (BiTRDF), which adds valid time and transaction time to the standard RDF. Our approach treats temporal information as references instead of attributes, simplifying the semantics while enhancing the model’s expressiveness and consistency. BiTRDF treats all resources and relationships as inherently bitemporal, enabling the representation and reasoning of complex temporal relationships in RDF. Illustrative examples demonstrate the model’s support for type propagation, domain-range inference, and transitive relationships in a temporal setting. While this work lays a theoretical foundation, future research will address implementation, query language support, and compatibility with RDF streams and legacy systems.

Alternatives for facilitating automatic transformation of BIM data using semantic query languages