International Journal of Metadata, Semantics and Ontologies
These articles have been peer-reviewed and accepted for publication but are pending final changes, are not yet published and may not appear here in their final order of publication until they are assigned to issues. Therefore, the content conforms to our standards but the presentation (e.g. typesetting and proof-reading) is not necessarily up to the Inderscience standard. Additionally, titles, authors, abstracts and keywords may change before publication. Articles will not be published until the final proofs are validated by their authors.
Forthcoming articles must be purchased for the purposes of research, teaching and private study only. These articles can be cited using the expression "in press". For example: Smith, J. (in press). Article Title. Journal Title.
Articles marked with this shopping trolley icon are available for purchase - click on the icon to send an email request to purchase.
International Journal of Metadata, Semantics and Ontologies (3 papers in press)
Modelling weightlifting 'training-diet-competition' cycle following a modular and scalable approach by Piyaporn Tumnark, Paulo Cardoso, Jorge Cabral, Filipe Conceicao Abstract: Studies in weightlifting have been characterised by unclear results and information paucity, mainly owing to the lack of information sharing between athletes, coaches, biomechanists, physiologists and nutritionists. These experts knowledges are not captured, classified or integrated into an information system for decision-making. An ontology-driven knowledge model for Olympic weightlifting was developed to leverage a better understanding of the weightlifting domain as a whole, bringing together related knowledge domains of training methodology, weightlifting biomechanics, and dietary, while modelling the synergy among them. It unifies terminology, semantics, and concepts among sport scientists, coaches, nutritionists, and athletes to partially obviate the recognised limitations and inconsistencies, leading to the provision of superior coaching and a research environment that promotes better understanding and more conclusive results. The ontology-assisted weightlifting knowledge base consists of 110 classes, 50 object properties, 92 data properties, and 167 inheritance relationships concepts, in a total of 1761 axioms, alongside 23 SWRL rules. Keywords: ontology; nutrition; weightlifting; biomechanics; semantics; reasoning.
An algorithm to generate short sentences in natural language from linked open data based on linguistic templates by Augusto Lopes Da Silva, Sandro Rigo, Jéssica Moraes Abstract: The generation of natural language phrases from linked open data can benefit from a significant amount of information available on the internet, as well as from the existence of properties within them, which appears, mostly, in the RDF format. These properties can represent semantic relationships between concepts that might help in creating sentences in natural language. Nevertheless, research in this field tends not to use the information in RDF. We support that this is a factor that might foster the generation of more natural phrases. In this scenario, this research explores these RDF properties for the generation of natural language phrases. The short sentences generated by the algorithm implementation were evaluated regarding their fluency by linguists and native English speakers. The results show that the sentences generated are promising regarding sentence fluency. Keywords: linked open data; natural language generation; RDF; ontologies; linguistic templates; fluency.
Towards linked open government data in Canada by Enayat Rajabi Abstract: Governments are publishing enormous amounts of open data on the web every day in an effort to increase transparency and reusability. Linking data from multiple sources on the web enables the performance of advanced data analytics, which can lead to the development of valuable services and data products. However, Canadas open government data portals are isolated from one another and remain unlinked to other resources on the web. In this paper, we first expose the statistical datasets in Canadian provincial open data portals such as Linked Data, and then integrate them using RDF Cube vocabulary, thereby making different open data portals available through a single search endpoint. We leverage semantic web technologies to publish open data sets taken from two provincial portals (Nova Scotia and Alberta) as RDF (the Linked Data format), and to connect them to one another. The success of our approach illustrates its high potential for linking open government datasets across Canada, which will in turn enable greater data accessibility and improved search results. Keywords: open data; RDF cube; linked data; semantic web.