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Systematic reviewing is a time-consuming and resource-intensive process. Information specialists are maintaining study-based registers to facilitate efficient conduct of systematic reviews. Classification of study-level meta-data -such as interventions –can result in much more accurate searches, saving time in the early steps of systematic reviewing.
To classify all pharmacological interventions from all schizophrenia trials.
We used Cochrane Schizophrenia's Study-based Register as the source of trials, Emtree and MeSH for synonyms, AdisInsight and CT.gov for research drugs and WHO ATC for marketed drugs.
One third of tested interventions on patients with schizophrenia are pharmacological (816; belonging to 106 clinical classes) with antipsychotic drugs being the most researched (15.1%). Only 528 of these medications are listed in WHO ATC. Around one third of these drug interventions are seen only in research (236; from 21 pharmacological/biochemical classes). Within the pharmacological interventions, we identified 28 ‘qualifiers’ including dose, route and timing of drug delivery.
Identification and classification of pharmacological interventions from trials require use of many sources of information none of which are inclusive of all drugs. Limitations of each source are helpful to understand. Classification of non-pharmacological interventions is now a priority for clinical and information scientists and professionals.
Semantic similarity measurement: an intrinsic information content model
Abhijit Adhikari; Biswanath Dutta; Animesh Dutta; Deepjyoti Mondal
International Journal of Metadata, Semantics and Ontologies, Vol. 14, No. 3 (2020) pp. 218 - 233
Ontology dependent Semantic Similarity (SS) measurement has emerged as a new research paradigm in finding the semantic strength between any two entities. In this regard, as observed, the information theoretic intrinsic approach yields better accuracy in correlation with human cognition. The precision of such a technique highly depends on how accurately we calculate Information Content (IC) of concepts and its compatibility with a SS model. In this work, we develop an intrinsic IC model to facilitate better SS measurement. The proposed model has been evaluated using three vocabularies, namely SNOMED CT, MeSH and WordNet against a set of benchmark data sets. We compare the results with the state-of-the-art IC models. The results show that the proposed intrinsic IC model yields a high correlation with human assessment. The article also evaluates the compatibility of the proposed IC model and the other existing IC models in combination with a set of state-of-the-art SS models.
Formalisation and classification of grammar and template-mediated techniques to model and ontology verbalisation
Zola Mahlaza; C. Maria Keet
International Journal of Metadata, Semantics and Ontologies, Vol. 14, No. 3 (2020) pp. 249 - 262
Computational tools that translate modelling languages to a restricted natural language can improve end-user involvement in modelling. Templates are a popular approach for such a translation and are often paired with computational grammar rules to support grammatical complexity to obtain better quality sentences. There is no explicit specification of the relations used for the pairing of templates with grammar rules, so it is challenging to compare the latter templates' suitability for less-resourced languages, where grammar reuse is vital in reducing development effort. In order to enable such comparisons, we devise a model of pairing templates and rules, and assess its applicability by considering 54 existing systems for classification, and 16 of them in detail. Our classification shows that most grammar-infused template systems support detachable grammar rules and half of them introduce syntax trees for multilingualism or error checking. Furthermore, out of the 16 considered grammar-infused template systems, most do not currently support any of form of aggregation (63%) or the embedding of verb conjugation rules (81%); hence, if such features would be required, then they would need to be implemented from the ground up.
Automatic classification of digital objects for improved metadata quality of electronic theses and dissertations in institutional repositories
Lighton Phiri
International Journal of Metadata, Semantics and Ontologies, Vol. 14, No. 3 (2020) pp. 234 - 248
Higher education institutions typically employ Institutional Repositories (IRs) in order to curate and make available Electronic Theses and Dissertations (ETDs). While most of these IRs are implemented with self-archiving functionalities, self-archiving practices are still a challenge. This arguably leads to inconsistencies in the tagging of digital objects with descriptive metadata, potentially compromising searching and browsing of scholarly research output in IRs. This paper proposes an approach to automatically classify ETDs in IRs, using supervised machine learning techniques, by extracting features from the minimum possible input expected from document authors: the ETD manuscript. The experiment results demonstrate the feasibility of automatically classifying IR ETDs and, additionally, ensuring that repository digital objects are appropriately structured. Automatic classification of repository objects has the obvious benefit of improving the searching and browsing of content in IRs and further presents opportunities for the implementation of third-party tools and extensions that could potentially result in effective self-archiving strategies.
Modelling weightlifting 'Training-Diet-Competition' cycle following a modular and scalable approach
Piyaporn Tumnark; Paulo Cardoso; Jorge Cabral; Filipe Conceição
International Journal of Metadata, Semantics and Ontologies, Vol. 14, No. 3 (2020) pp. 185 - 196
Studies in weightlifting have been characterised by unclear results and information paucity, mainly due to the lack of information sharing between athletes, coaches, biomechanists, physiologists and nutritionists. These experts' knowledge is 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 regimes, 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 which promotes better understanding and more conclusive results. The ontology-assisted weightlifting knowledge base consists of 110 classes, 50 object properties, 92 data properties, 167 inheritance relationships concepts, in a total of 1761 axioms, alongside 23 SWRL rules.
An algorithm to generate short sentences in natural language from linked open data based on linguistic templates
Augusto Lopes Da Silva; Sandro José Rigo; Jéssica Braun De Moraes
International Journal of Metadata, Semantics and Ontologies, Vol. 14, No. 3 (2020) pp. 197 - 208
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.
Towards linked open government data in Canada
Enayat Rajabi
International Journal of Metadata, Semantics and Ontologies, Vol. 14, No. 3 (2020) pp. 209 - 217
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, Canada's 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 data sets in Canadian provincial open data portals 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 data sets across Canada, which will in turn enable greater data accessibility and improved search results.
Academic library is the heart of an educational institution. It is a services centre and always eager to satisfy its user by providing quality services. The evaluation studies of library user’ satisfaction has been in focus for the librarians to improve library infrastructure, resources, and services. This study is an attempt on the same lines to know the satisfaction of library users at Al-Kabir Polytechnic, Jamshedpur (India). A survey was conducted and questionnaire was used a tool for data collection. Data collected from 160 students was analysed and found that majority of the users are satisfied with the library infrastructure, resources and services. It is suggested that library should organize awareness as well as orientation-cum-training programmes to attract more and more users.
This study investigated Information and communication technology and cataloguers’ information needs and seeking behaviour in university libraries in Edo and Delta states, Nigeria. The study employed a descriptive survey method and questionnaire was the instrument used for data collection. The population of this study consisted of fifty-two (52) cataloguers in all the university libraries in Edo and Delta States. The population of this study is relatively small and as such the entire population was used as representative sample using purposeful sampling techniques. The researchers visited the sample institutions to administer the questionnaire. It was revealed from the study. The study revealed that Library of congress website, google.com and IFLANET.com are the ICT tools use by cataloguers for seeking information. The study also indicates that cataloguers used information and communication technology to make work done easily and faster, access to current information, professional development, increase work output, Improve my skills in the use of OPAC and improve my knowledge and skills in databases. The study recommended that there should be adequate information and communication technology (ICT) facilities should be put in place by the library managements to enable cataloguers make use of library of congress website, google.com and IFLANET.com as this will enhance the performance of cataloguers in rendering efficient and effective services.
The main purpose of this study is to find the awareness of digital information literacy skills among the students of Royal Global University, Guwahati. In today’s digital society it is very much essential to have good skills to procure information as the maximum number of information sources are available in digital format. Students should know how to access or use information. Many new generation students are very much self-confident about their information skills but it is also observed that they are not always capable to evaluate the authenticity of that information. The study examines the literacy level to search, locate and use digital information. The present study also helps us to know the IT skills of the students. A structured questionnaire was prepared and personally distributed among 100 respondents. Most of them are aware of digital information literacy. For better use of digital resources, almost all the respondents stress that they require training.
The 21st century is widely known as the networking age which is an age of internet where almost everything is available on World Wide Web(WWW). The advances in the WWW have tremendously changed the way how people access information and communicate with one another. Social networking tools have become popular among the students for resource sharing. End number of users are connecting globally through Social Networking Sites (SNSs) as a medium for communicating, entertainment, news and updates, information etc which serve as a platform to be used by users to retrieve their respective objective. The study primarily focuses on finding out the opportunities provided by SNSs as well as the benefits received by the students and research scholars of Assam Agricultural University, Jorhat, Assam.
The paper focused on the bibliometric study on the articles published in the Journal of Information Technology Management for the period from 2012 to 2019. During this period, there were 123 articles published by the researchers from various parts of the world. In this paper, various aspects related to the bibliometric analysis were analyzed such as year-wise distribution of articles, degree of collaboration amid authors, authorship pattern, issue-wise distribution of articles, length of the articles, institution affiliation of authors, geographical distribution of articles, and range of reference of articles. During that period, the journal was published nearly 8 volumes with 31 issues having 123 articles. It also found that the journal was published more number of articles in year 2013 and 2014 with 20 articles (16.3%). It was revealed that the highest contributions were published by three authors with 41 articles (33.33%). It was also identified that the overall degree of collaboration average for the period of study was 0.77. The study demonstrates that the maximum numbers of articles published during the study were having the length of 11 – 20 pages with 88 articles (71.54%). The maximum number of 42 articles with 34.15% was published with the range of references of 50 and above. It was exposed from the analysis that the greater part of the articles published by the authors affiliated to universities with 104 articles (84.55%).
Citation content/context data as a source for research cooperation analysis
Sergey Parinov; Victoria Antonova
International Journal of Metadata, Semantics and Ontologies, Vol. 14, No. 2 (2020) pp. 149 - 157
Using citation relationships, one can build three groups of papers: (1) the papers of a selected author; (2) those papers cited by the author; (3) papers citing the author. Authors of papers from these three groups can be presented as a fragment of a research cooperation network, because they use/cite research outputs of each other. Their papers' full texts and especially the contexts of their in-text citations contain some information about the character of this research cooperation. We present a concept of research cooperation, based on publications and the current results of the Cirtec project for building the research cooperation characteristics. This work is based on the processing of citation content/context data. The results include an on-line service for authors to monitor the citation content data extractions and three types of built indicators/parameters: co-citation statistics, spatial distribution of citations over papers' body and topic models for citation contexts.
From the web of bibliographic data to the web of bibliographic meaning: structuring, interlinking and validating ontologies on the semantic web
Helena Simões PatrÃcio; Maria Inês Cordeiro; Pedro Nogueira Ramos
International Journal of Metadata, Semantics and Ontologies, Vol. 14, No. 2 (2020) pp. 124 - 134
Bibliographic data sets have revealed good levels of technical interoperability observing the principles and good practices of linked data. However, they have a low level of quality from the semantic point of view, due to many factors: lack of a common conceptual framework for a diversity of standards often used together, reduced number of links between the ontologies underlying data sets, proliferation of heterogeneous vocabularies, underuse of semantic mechanisms in data structures, "ontology hijacking" (Feeney et al., 2018), point-to-point mappings, as well as limitations of semantic web languages for the requirements of bibliographic data interoperability. After reviewing such issues, a research direction is proposed to overcome the misalignments found by means of a reference model and a superontology, using Shapes Constraint Language (SHACL) to solve current limitations of RDF languages.
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