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Nowadays, the use of WCMS (web content management systems) is widespread. The conversion of this infrastructure into its semantic equivalent (semantic WCMS) is a critical issue, as this enables the benefits of the semantic web to be extended. The purpose of this paper is to present a FLERSA (Flexible Range Semantic Annotation) for flexible range semantic annotation.

A FLERSA is presented as a user‐centred annotation tool for Web content expressed in natural language. The tool has been built in order to illustrate how a WCMS called Joomla! can be converted into its semantic equivalent.

The development of the tool shows that it is possible to build a semantic WCMS through a combination of semantic components and other resources such as ontologies and emergence technologies, including XML, RDF, RDFa and OWL.

The paper provides a starting‐point for further research in which the principles and techniques of the FLERSA tool can be applied to any WCMS.

The tool allows both manual and automatic semantic annotations, as well as providing enhanced search capabilities. For manual annotation, a new flexible range markup technique is used, based on the RDFa standard, to support the evolution of annotated Web documents more effectively than XPointer. For automatic annotation, a hybrid approach based on machine learning techniques (Vector‐Space Model + n‐grams) is used to determine the concepts that the content of a Web document deals with (from an ontology which provides a taxonomy), based on previous annotations that are used as a training corpus.

The purpose of this paper is to investigate indexers’ evaluation on the usability of ontology vs thesaurus in representation of concepts and semantic relations. To do so, “searching” category of ASIS&T thesaurus was selected and ASIS&TOnto was built based on it.

The usability examination method is used in order to compare the two semantic tools. Nine indexers were recruited as participants, who were proficient in English language, had experience in using the thesaurus and all had successfully passed the course of “information representation.” They were asked to think aloud while working with the tools and to answer a semi-structured interview. The data gathering was continued until it reached its saturation point.

The results of this study revealed that the definitions and scope notes represented in indexing tools such as thesauri and ontologies have an important role in improvement of indexers’ understanding. On comparing the hierarchical relations, results show that converting the structure of hierarchical relationships of ASIS&T thesaurus can enhance the indexers understanding of them, and also enriching the associative relations of ASIS&T thesaurus can cause indexers to have a better understanding and evaluation of the presented concepts and relations.

This study shares our findings on the usability of ASIS&T thesaurus as a core set of vocabulary for building a “searching” domain as a prototype ontology in the area of library and information science and provides the indexers viewpoints of the two semantic tools in this area.

Considering the shortcomings of the ASIS&T Web-based thesaurus in representing concepts and semantic relations, there is a need to use more effective semantic tools, such as ontologies. The purpose of this paper is to build a prototype ontology (ASIS&TOnto) based on a Web-based thesaurus.

The prototype ontology was built based on the ASIS&T Web-based thesaurus by using the methodology developed by Noy and McGuinness (2001) and with the use of Protégé 4.3.3. With regard to the purpose of the study and the massive amount of concepts represented in the ASIS&T thesaurus, the focus of term selection for creating the core source of vocabulary for the prototype ontology was the “searching” area. The knowledge engineering approach (Na and Neoh, 2008) was used to extract concepts and semantic relations. The criterion for extracting semantic relations from each concept pair was one-sentence statement, one-paragraph statement and one-page statement. Finally, the extracted relations were analysed by subject experts.

Based on the findings of this research, the possibility of using the methodology developed by Noy and McGuinness (2001) for building an ontology based on a Web-based thesaurus in the field of LIS was investigated and the prototype ontology (ASIS&TOnto) was constructed in the area of “searching”.

The primary implication of ASIS&TOnto is aligned with Web 3.0 research where implications of semantic modelling are a priority for community equity of access to information as a basic human right. ASIS&TOnto ends up with an ontology that is comprehensive, at least with respect to expressivity of the current ASIS&T thesaurus user interface definition languages; that is, it can be universal and can be extendable to future user interfaces that do not exist at the moment.

For the first time, a new enriched semantic tool (ASIS&TOnto) was constructed based on the ASIS&T Web-based thesaurus.

The purpose of this paper is to present extensions of Semantic MediaWiki for the purpose of technology forecast and technology monitoring. The user friendliness and applicability of the components is evaluated by task-based user studies.

Based on the requirements given by potential end users (technology experts), visualization possibilities were designed and implemented. Potential users used the new features of technology forecast and monitoring within a semantic wiki and were controlled regarding the effectiveness.

Although semantic wikis are ideal tools for knowledge management in industry settings, especially due to their user-friendly way of storing and retrieving knowledge, they have rarely been used for technology forecast and monitoring purposes so far. The authors show that the additional requirements for such purposes can be met and provide established technology analysis possibilities within Semantic MediaWiki. In that way, a new application area of Semantic MediaWiki is introduced.

Tools and techniques for Semantic MediaWiki are presented, opening the application area of Semantic MediaWiki for technology and innovation management. The research provides evidence that the open-source implemented visualization and storage techniques can be applied in real-world settings, where so far mainly costly dedicated software has had to be used.

This research aimed to visualize and analyze the co-word network and thematic clusters of the intellectual structure in the field of linked data during 1900–2021.

This applied research employed a descriptive and analytical method, scientometric indicators, co-word techniques, and social network analysis. VOSviewer, SPSS, Python programming, and UCINet software were used for data analysis and network structure visualization.

The top ranks of the Web of Science (WOS) subject categorization belonged to various fields of computer science. Besides, the USA was the most prolific country. The keyword ontology had the highest frequency of co-occurrence. Ontology and semantic were the most frequent co-word pairs. In terms of the network structure, nine major topic clusters were identified based on co-occurrence, and 29 thematic clusters were identified based on hierarchical clustering. Comparisons between the two clustering techniques indicated that three clusters, namely semantic bioinformatics, knowledge representation, and semantic tools were in common. The most mature and mainstream thematic clusters were natural language processing techniques to boost modeling and visualization, context-aware knowledge discovery, probabilistic latent semantic analysis (PLSA), semantic tools, latent semantic indexing, web ontology language (OWL) syntax, and ontology-based deep learning.

This study adopted various techniques such as co-word analysis, social network analysis network structure visualization, and hierarchical clustering to represent a suitable, visual, methodical, and comprehensive perspective into linked data.

A fine‐grained video content indexing, retrieval, and adaptation requires accurate metadata describing the video structure and semantics to the lowest granularity, i.e. to the object level. The authors address these requirements by proposing semantic video content annotation tool (SVCAT) for structural and high‐level semantic video annotation. SVCAT is a semi‐automatic MPEG‐7 standard compliant annotation tool, which produces metadata according to a new object‐based video content model introduced in this work. Videos are temporally segmented into shots and shots level concepts are detected automatically using ImageNet as background knowledge. These concepts are used as a guide to easily locate and select objects of interest which are then tracked automatically to generate an object level metadata. The integration of shot based concept detection with object localization and tracking drastically alleviates the task of an annotator. The paper aims to discuss these issues.

A systematic keyframes classification into ImageNet categories is used as the basis for automatic concept detection in temporal units. This is then followed by an object tracking algorithm to get exact spatial information about objects.

Experimental results showed that SVCAT is able to provide accurate object level video metadata.

The new contribution in this paper introduces an approach of using ImageNet to get shot level annotations automatically. This approach assists video annotators significantly by minimizing the effort required to locate salient objects in the video.

In this presentation I shall be concerned with only one aspect of information science and its relation with linguistics: namely document analysis (for a broader survey of ‘Linguistics and information science’, see the recent article published under that title by C. Montgomery (1972); also M. Kay and K. Sparck Jones (1971), and the report prepared for F.I.D. by the same authors, forthcoming; M. Coyaud (1972), in French, deals with many separate facets of the same subject).

To identify cases related to design of ICT platforms for industrial alliances, where the use of Ontology‐driven architectures based on Semantic web standards is more advantageous than application of conventional modeling together with XML standards.

A comparative analysis of the two latest and the most obvious use cases (NASA and Nordic Process Industry Data Exchange Alliance) concerned with development of an environment for integration and collaboration of industrial partners, has been used as a basis for the research results. Additionally, dynamics of changes in a domain data model and their consequences have been analyzed on a couple of typical use cases.

Ontology‐driven architectures of a collaboration and integration ICT platforms have been recognized as more appropriate for a technical support of industrial alliances around a supply‐chains with a long life cycles.

More typical cases related to changes in domain data/knowledge models and to necessity of their integration, have to be considered and analyzed in search of advantageous of ontological modeling over conventional modeling approaches. Ways of a gradual change from conventional domain models to ontological ones in ICT systems have to be studied. The significance of existing XML‐based tools and the popularity of XML has to be estimated for the wide adoption of Semantic web principles.

The modeling approach which will be used as a core for building a collaboration and integration ICT platforms has to be carefully selected. Incorrect choice (e.g. UML together with XML) can cause consequences that will be hard to reform. The paper is anticipated to facilitate faster adoption of the Semantic web approach by industry.

The serious revision of existing and emerging domain modeling approaches has been undertaken. More unique arguments in favor of ontological modeling have been discovered. The paper is intended for serious consideration by emerging industrial alliances with regard to their choice in a core technology that will technically enable integration and collaboration between partners.

With the rapid development of materials informatics and the Semantic Web, the semantic-driven solution has emerged to improve traditional query technology, which is hard to discover implicit knowledge from materials data. However, it is a nontrivial thing for materials scientists to construct a semantic query, and the query results are usually presented in RDF/XML format which is not convenient for users to understand. This paper aims to propose an approach to construct semantic query and visualize the query results for metallic materials domain.

The authors design a query builder to generate SPARQL query statements automatically based on domain ontology and query conditions inputted by users. Moreover, a semantic visualization model is defined based on the materials science tetrahedron to support the visualization of query results in an intuitive, dynamic and interactive way.

Based on the Semantic Web technology, the authors design an automatic semantic query builder to help domain experts write the normative semantic query statements quickly and simply, as well as a prototype (named MatViz) is developed to visually show query results, which could help experts discover implicit knowledge from materials data. Moreover, the experiments demonstrate that the proposed system in this paper can rapidly and effectively return visualized query results over the metallic materials data set.

This paper mainly discusses an approach to support semantic query and visualization of metallic materials data. The implementation of MatViz will be a meaningful work for the research of metal materials data integration.

Library Director Jarmo Saarti introduced a wide or ideal model for fiction in literature in his dissertation, published in 1999. It introduces those aspects that should be included in an information system for fiction. Such aspects include literary prose and its intertextual references to other works, the writer, readers' and critics' receptions of the work as well as a researcher's view. It is also important to note how libraries approach a literary work by means of inventory, classification and content description. The most ambiguous of the aspects relates to that context in cultural history, which the work reflects and is a part of. The paper aims to discuss these issues.

Since the model consists of several components which are not found in present library information systems and cannot be implemented by them, a new way had to be found to produce, save, process and present fiction‐related metadata. The Semantic Computing Research Group of Aalto University has developed several Semantic Web services for use in the field of culture, so cooperation with it and the use of Semantic Web tools were a natural starting point for the construction of the new service. Kirjasampo will be based on the Semantic Web RDF data model. The model enables a flexible linking of metadata derived from different sources, and it can be used to build a Semantic Web that can be approached contextually from different angles.

The “semantically enriched” ideal model for fiction has hence been realised, at least to some extent: Kirjasampo supports literature‐related metadata that is more varied than earlier and aims to account for different contexts within literature and connections with regard to other cultural phenomena. It also includes contemporary reviews of works and, as such, readers' receptions as well. Modern readers can share their views on works, once the user interface of the server is completed. It will include several features from the Kirjasto 2.0‐application, which enables the evaluation, description and recommendations of works. The service should be online by the end of Spring 2011.

The project involves novel collaboration between a public library and a computer science research unit, and utilises a novel approach to the description of fiction.

The system encourages user participation in the description of fiction and is of practical benefit to librarians in understanding both how fiction is organised and how users interpret the same.

Upon completion, the service will be the first Finnish information system for libraries built with the tools of the Semantic Web which offers a completely new user environment and application for data produced by libraries. It also strives to create a new model for saving and producing data, available to both library professionals and readers. The aim is to save, accumulate and distribute literary knowledge, experiences and silent information.