Search results

This study aims to collect distributed knowledge organization systems (KOSs) from various domains, enrich each with meta information and link them to the multilingual KOS registry, facilitating integrated search alongside KOSs from various languages and regions.

This research involved collecting and organizing KOS information through three primary steps. The initial phase involved finding KOSs from Web search results, supplemented by the Korea ON-line E-Procurement System (KONEPS) and the National R&D Integrated Notification Service. After obtaining these KOSs, they were enriched by structuring contextual meta information using Basic Register of Thesauri, Ontologies and Classification (BARTOC) metadata elements and established dedicated media wiki pages for each. Finally, the KOSs were linked to the multilingual KOS registry, BARTOC, ensuring seamless integration with KOSs from various languages and regions and creating connections between each registry entry and its associated KOS wiki page.

The research findings revealed several insights, as follows: (1) importance of a stable source for collecting KOS: no national body currently oversees KOS registration, underscoring the need for a systematic approach to collect dispersed KOSs. For Korean KOSs (K-KOSs), KONEPS and National R&D Integrated Notification Service are effective data sources. (2) Importance of enhanced metadata: merely collecting KOSs were not enough. Enhanced metadata bridges access gaps and dedicated wiki pages aid user identification and understanding. (3) Observations from multilingual registry uploads: When adding KOSs to a multilingual registry, similarities were observed across languages and regions. Recognizing this, the K-KOSs were linked with their international counterparts, fostering potential global collaboration.

Due to the absence of a dedicated KOS registry agency, the study might have missed KOSs from certain fields or potentially over-collected from others. Furthermore, this study primarily focused on K-KOSs and their integration into the BARTOC registry, which might influence the methods and perspectives on collecting and establishing links among analogous KOSs in the registry.

This research pursued a stable method to detect KOS development and revisions across various fields. To facilitate this, we used the integrated e-procurement and R&D notification system and added meta information to aid in the identification and understanding of KOSs, which includes media wiki pages. Furthermore, link information was provided between the BARTOC registry and the Korean KOS websites and media wiki pages.

The purpose of this article is to report on sessions the author attended at the 2013 ASIS&T Conference.

The approach is an informal review of sessions and events the author attended.

This report condenses the author's notes from various events and sessions at the conference.

This is an original conference report written after attending the conference.

The main objective of the AGROVOC Concept Server (CS) is to create a collaborative reference platform and a “one‐stop” shop for a pool of commonly used concepts related to agriculture, containing terms, definitions and relationships between terms in multiple languages derived from various sources. This paper aims to address the issues.

The CS offers a centralised facility where the agricultural information management community can build and share agricultural knowledge in a collaborative environment.

The advantages of the CS are its extensibility and modularity that provide the possibility to extend the type of information that can be stored in this system based on user/community needs.

Further investigation still needs to be done on the modularisation of the CS (i.e. the creation of separated ontologies that can still be connected, in order to have domain‐related ontologies and to allow for better performance of the CS).

The CS serves as starting point for the development of specific domain ontologies where multilinguality and the localised representation of knowledge are essential issues. Furthermore, it will offer additional services in order to expose the knowledge to be consumed by other applications.

The CS Workbench provides the AGROVOC partners with the possibility to directly and collaboratively edit the AGROVOC CS. It thus provides the opportunity for direct and open “many‐to‐many” communication links between communities, avoiding decentralised communication between partners and duplication of effort. For the international community, it may allow users to manage, re‐use or extend agriculture‐related knowledge for better interoperability and for improved services.

The purpose of this paper is to identify the concepts, component parts and relationships between vocabularies, linked data and knowledge graphs (KGs) from the perspectives of data and knowledge transitions.

This paper uses conceptual analysis methods. This study focuses on distinguishing concepts and analyzing composition and intercorrelations to explore data and knowledge transitions.

Vocabularies are the cornerstone for accurately building understanding of the meaning of data. Vocabularies provide for a data-sharing model and play an important role in supporting the semantic expression of linked data and defining the schema layer; they are also used for entity recognition, alignment and linkage for KGs. KGs, which consist of a schema layer and a data layer, are presented as cubes that organically combine vocabularies, linked data and big data.

This paper first describes the composition of vocabularies, linked data and KGs. More importantly, this paper innovatively analyzes and summarizes the interrelatedness of these factors, which comes from frequent interactions between data and knowledge. The three factors empower each other and can ultimately empower the Semantic Web.

The paper aims to develop a prototype middleware framework between different terminology resources in order to provide a subject cross‐browsing service for library portal systems.

Nine terminology experts were interviewed to collect appropriate knowledge to support the development of a theoretical framework for the research. Based on this, a simplified software‐based prototype system was constructed incorporating the knowledge acquired. The prototype involved mappings between the computer science schedule of the Dewey Decimal Classification (which acted as a spine) and two controlled vocabularies, UKAT and ACM Computing Classification. Subsequently, six further experts in the field were invited to evaluate the prototype system and provide feedback to improve the framework.

The major findings showed that, given the large variety of terminology resources distributed throughout the web, the proposed middleware service is essential to integrate technically and semantically the different terminology resources in order to facilitate subject cross‐browsing. A set of recommendations are also made, outlining the important approaches and features that support such a cross‐browsing middleware service.

Cross‐browsing features are lacking in current library portal meta‐search systems. Users are therefore deprived of this valuable retrieval provision. This research investigated the case for such a system and developed a prototype to fill this gap.

The paper aims to investigate issues surrounding publishing thesauri as linked data and explores a systematic way for publishing linked open thesauri

Based on the four principles of linked data, a novel approach is proposed to incorporate terminology services with thesauri and provide more descriptive information about thesauri and relating services. A proof-of-concept system was built for demonstrating the approach.

Carefully designed URIs and terminology services are necessary for publishing linked open thesauri. However, there is still a lack of standards for describing linked open thesauri and terminology services. Since it is possible to publish thesauri at the hands of creators and maintainers, distributed thesauri may be a good complement to the traditional registry approach.

Only a simple knowledge organisation system (SKOS) core model is considered in the paper. There may be some adjustment for applying the findings to thesauri using the SKOS extended model and other models.

The paper proposes a more systematic way for publishing linked open thesauri. It is important to consider a linked open thesaurus as a dynamic system rather than a static data dump. In addition, functionality for using thesauri is equally important for publishing thesauri.

The purpose of this paper is to examine and provide an insight into Canadian post‐secondary institutional repositories (IRs) with respect to user interface features and knowledge organization systems (KOS) used.

The approach is to explore all Canadian post‐secondary institutions and their user interfaces to establish the type of searching and browsing features they have used and whether or not they have made use of KOS such as subject heading lists or classification schemes.

A directory of 27 IRs in Canada is created. Incorporation of KOS in institutional repository is evaluated. The examination is focuses on accessibility, searching, KOS use, and retrieval. Evaluation shows that few IRs have incorporated complex KOS such as controlled vocabularies. Browsing and searching options are available, but user interfaces are usually not modified to enhance information retrieval.

This is the first paper examining Canadian IRs from the perspectives of searching, browsing and the use of KOS.

Through a theoretical review of the literature, this chapter assesses the potential of different knowledge organisation systems (KOS) to support corporate knowledge management systems (KMS), namely digital libraries (DL) in companies and other institutions. Questions are framed through which the chapter discusses how classical KOS, such as nomenclatures, classification systems, thesauri and ontologies, are able to reflect explicit knowledge in sense of the Semantic Web and also introduces persons as documents along with folksonomies as a means for externalising implicit knowledge in sense of the Web 2.0.

This paper aims to delve into the complexities of terminology mapping and annotation, particularly within the context of the COVID-19 pandemic. It underscores the criticality of harmonizing clinical knowledge organization systems (KOS) through a cohesive clinical knowledge representation approach. Central to the study is the pursuit of a novel method for integrating emerging COVID-19-specific vocabularies with existing systems, focusing on simplicity, adaptability and minimal human intervention.

A design science research (DSR) methodology is used to guide the development of a terminology mapping and annotation workflow. The KNIME data analytics platform is used to implement and test the mapping and annotation techniques, leveraging its powerful data processing and analytics capabilities. The study incorporates specific ontologies relevant to COVID-19, evaluates mapping accuracy and tests performance against a gold standard.

The study demonstrates the potential of the developed solution to map and annotate specific KOS efficiently. This method effectively addresses the limitations of previous approaches by providing a user-friendly interface and streamlined process that minimizes the need for human intervention. Additionally, the paper proposes a reusable workflow tool that can streamline the mapping process. It offers insights into semantic interoperability issues in health care as well as recommendations for work in this space.

The originality of this study lies in its use of the KNIME data analytics platform to address the unique challenges posed by the COVID-19 pandemic in terminology mapping and annotation. The novel workflow developed in this study addresses known challenges by combining mapping and annotation processes specifically for COVID-19-related vocabularies. The use of DSR methodology and relevant ontologies with the KNIME tool further contribute to the study’s originality, setting it apart from previous research in the terminology mapping and annotation field.

The Integrative Levels Classification (ILC) is a comprehensive “freely faceted” knowledge organization system not previously expressed as SKOS (Simple Knowledge Organization System). This paper reports and reflects on work converting the ILC to SKOS representation.

The design of the ILC representation and the various steps in the conversion to SKOS are described and located within the context of previous work considering the representation of complex classification schemes in SKOS. Various issues and trade-offs emerging from the conversion are discussed. The conversion implementation employed the STELETO transformation tool.

The ILC conversion captures some of the ILC facet structure by a limited extension beyond the SKOS standard. SPARQL examples illustrate how this extension could be used to create faceted, compound descriptors when indexing or cataloguing. Basic query patterns are provided that might underpin search systems. Possible routes for reducing complexity are discussed.

Complex classification schemes, such as the ILC, have features which are not straight forward to represent in SKOS and which extend beyond the functionality of the SKOS standard. The ILC's facet indicators are modelled as rdf:Property sub-hierarchies that accompany the SKOS RDF statements. The ILC's top-level fundamental facet relationships are modelled by extensions of the associative relationship – specialised sub-properties of skos:related. An approach for representing faceted compound descriptions in ILC and other faceted classification schemes is proposed.