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Informatics
Volume 7
Issue 2
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Informatics, Volume 7, Issue 2 (June 2020) – 11 articles

Cover Story (view full-size image): Professional translators increasingly use neural machine translation because of its expected efficiency gains. This is also true in the Directorate-General for Translation (DGT), the European Commission’s translation service. The standardized process used in DGT offered the opportunity to measure the efficiency gains of machine translation (MT) based on the actual production of translators in a real-life high-quality translation workflow. This was complemented with a survey addressed to the participating translators to gain insight into the perceived usefulness of MT. View this paper.
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5 pages, 188 KiB  
Editorial
Gamification and Advanced Technology to Enhance Motivation in Education
by Rafael Molina-Carmona and Faraón Llorens-Largo
Informatics 2020, 7(2), 20; https://doi.org/10.3390/informatics7020020 - 23 Jun 2020
Cited by 8 | Viewed by 5371
Abstract
The aim of this Special Issue is to compile a set of research works that highlight the use of gamification and other advanced technologies as powerful tools for motivation during learning. We have been fortunate to obtain a representative sample of the current [...] Read more.
The aim of this Special Issue is to compile a set of research works that highlight the use of gamification and other advanced technologies as powerful tools for motivation during learning. We have been fortunate to obtain a representative sample of the current research activity in this field. Full article
(This article belongs to the Special Issue Gamification and Advanced Technology to Enhance Motivation in Education)
21 pages, 528 KiB  
Article
Rapid Development of Competitive Translation Engines for Access to Multilingual COVID-19 Information
by Andy Way, Rejwanul Haque, Guodong Xie, Federico Gaspari, Maja Popović and Alberto Poncelas
Informatics 2020, 7(2), 19; https://doi.org/10.3390/informatics7020019 - 17 Jun 2020
Cited by 12 | Viewed by 5615
Abstract
Every day, more people are becoming infected and dying from exposure to COVID-19. Some countries in Europe like Spain, France, the UK and Italy have suffered particularly badly from the virus. Others such as Germany appear to have coped extremely well. Both health [...] Read more.
Every day, more people are becoming infected and dying from exposure to COVID-19. Some countries in Europe like Spain, France, the UK and Italy have suffered particularly badly from the virus. Others such as Germany appear to have coped extremely well. Both health professionals and the general public are keen to receive up-to-date information on the effects of the virus, as well as treatments that have proven to be effective. In cases where language is a barrier to access of pertinent information, machine translation (MT) may help people assimilate information published in different languages. Our MT systems trained on COVID-19 data are freely available for anyone to use to help translate information (such as promoting good practice for symptom identification, prevention, and treatment) published in German, French, Italian, Spanish into English, as well as the reverse direction. Full article
(This article belongs to the Special Issue Feature Paper in Informatics)
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21 pages, 616 KiB  
Article
Machine Learning for Identifying Medication-Associated Acute Kidney Injury
by Sheikh S. Abdullah, Neda Rostamzadeh, Kamran Sedig, Daniel J. Lizotte, Amit X. Garg and Eric McArthur
Informatics 2020, 7(2), 18; https://doi.org/10.3390/informatics7020018 - 31 May 2020
Cited by 8 | Viewed by 5242
Abstract
One of the prominent problems in clinical medicine is medication-induced acute kidney injury (AKI). Avoiding this problem can prevent patient harm and reduce healthcare expenditures. Several researches have been conducted to identify AKI-associated medications using statistical, data mining, and machine learning techniques. However, [...] Read more.
One of the prominent problems in clinical medicine is medication-induced acute kidney injury (AKI). Avoiding this problem can prevent patient harm and reduce healthcare expenditures. Several researches have been conducted to identify AKI-associated medications using statistical, data mining, and machine learning techniques. However, these studies are limited to assessing the impact of known nephrotoxic medications and do not comprehensively explore the relationship between medication combinations and AKI. In this paper, we present a population-based retrospective cohort study that employs automated data analysis techniques to identify medications and medication combinations that are associated with a higher risk of AKI. By integrating multivariable logistic regression, frequent itemset mining, and stratified analysis, this study is designed to explore the complex relationships between medications and AKI in such a way that has never been attempted before. Through an analysis of prescription records of one million older patients stored in the healthcare administrative dataset at ICES (an independent, non-profit, world-leading research organization that uses population-based health and social data to produce knowledge on a broad range of healthcare issues), we identified 55 AKI-associated medications among 595 distinct medications and 78 AKI-associated medication combinations among 7748 frequent medication combinations. In addition, through a stratified analysis, we identified 37 cases where a particular medication was associated with increasing the risk of AKI when used with another medication. We have shown that our results are consistent with previous studies through consultation with a nephrologist and an electronic literature search. This research demonstrates how automated analysis techniques can be used to accomplish data-driven tasks using massive clinical datasets. Full article
(This article belongs to the Special Issue Feature Papers: Health Informatics)
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30 pages, 4668 KiB  
Article
Visual Analytics for Dimension Reduction and Cluster Analysis of High Dimensional Electronic Health Records
by Sheikh S. Abdullah, Neda Rostamzadeh, Kamran Sedig, Amit X. Garg and Eric McArthur
Informatics 2020, 7(2), 17; https://doi.org/10.3390/informatics7020017 - 27 May 2020
Cited by 24 | Viewed by 7404
Abstract
Recent advancement in EHR-based (Electronic Health Record) systems has resulted in producing data at an unprecedented rate. The complex, growing, and high-dimensional data available in EHRs creates great opportunities for machine learning techniques such as clustering. Cluster analysis often requires dimension reduction to [...] Read more.
Recent advancement in EHR-based (Electronic Health Record) systems has resulted in producing data at an unprecedented rate. The complex, growing, and high-dimensional data available in EHRs creates great opportunities for machine learning techniques such as clustering. Cluster analysis often requires dimension reduction to achieve efficient processing time and mitigate the curse of dimensionality. Given a wide range of techniques for dimension reduction and cluster analysis, it is not straightforward to identify which combination of techniques from both families leads to the desired result. The ability to derive useful and precise insights from EHRs requires a deeper understanding of the data, intermediary results, configuration parameters, and analysis processes. Although these tasks are often tackled separately in existing studies, we present a visual analytics (VA) system, called Visual Analytics for Cluster Analysis and Dimension Reduction of High Dimensional Electronic Health Records (VALENCIA), to address the challenges of high-dimensional EHRs in a single system. VALENCIA brings a wide range of cluster analysis and dimension reduction techniques, integrate them seamlessly, and make them accessible to users through interactive visualizations. It offers a balanced distribution of processing load between users and the system to facilitate the performance of high-level cognitive tasks in such a way that would be difficult without the aid of a VA system. Through a real case study, we have demonstrated how VALENCIA can be used to analyze the healthcare administrative dataset stored at ICES. This research also highlights what needs to be considered in the future when developing VA systems that are designed to derive deep and novel insights into EHRs. Full article
(This article belongs to the Special Issue Feature Papers: Health Informatics)
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22 pages, 1072 KiB  
Article
Architecture-Centric Evaluation of Blockchain-Based Smart Contract E-Voting for National Elections
by Olawande Daramola and Darren Thebus
Informatics 2020, 7(2), 16; https://doi.org/10.3390/informatics7020016 - 20 May 2020
Cited by 45 | Viewed by 11792
Abstract
E-voting is one of the valid use cases of blockchain technology with many blockchain e-voting systems already proposed. But efforts that focus on critical analysis of blockchain e-voting architectures for national elections from stakeholders’ perspectives are mostly lacking in the literature. Therefore, government [...] Read more.
E-voting is one of the valid use cases of blockchain technology with many blockchain e-voting systems already proposed. But efforts that focus on critical analysis of blockchain e-voting architectures for national elections from stakeholders’ perspectives are mostly lacking in the literature. Therefore, government decision-makers and election stakeholders do not yet have a sufficient basis to understand the potential risks, challenges, and prospects that are associated with blockchain e-voting. This paper demonstrates how the use of the Architecture Trade-off Analysis Method (ATAM) can enable stakeholders in national elections to understand the risks, prospects, and challenges that could be associated with a blockchain e-voting system for national elections. By using a study context of South Africa, a proposed blockchain e-voting architecture was used as a basis to aid election stakeholders to reason on the concept of blockchain e-voting to get them to understand the potential risks, security threats, critical requirements attributes, and weaknesses that could be associated with using blockchain e-voting for national elections. The study found that blockchain e-voting can prevent many security attacks, internal vote manipulation, and promote transparency. However, voter validation and the security of the blockchain architecture are potential weaknesses that will need significant attention. Full article
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25 pages, 349 KiB  
Review
What the Web Has Wrought
by Antony Bryant
Informatics 2020, 7(2), 15; https://doi.org/10.3390/informatics7020015 - 19 May 2020
Cited by 1 | Viewed by 5164
Abstract
In 1989, Sir Tim Berners-Lee proposed the development of ‘a large hypertext database with typed links’, which eventually became The World Wide Web. It was rightly heralded at the time as a significant development and a boon for one-and-all as the digital [...] Read more.
In 1989, Sir Tim Berners-Lee proposed the development of ‘a large hypertext database with typed links’, which eventually became The World Wide Web. It was rightly heralded at the time as a significant development and a boon for one-and-all as the digital age flourished both in terms of universal accessibility and affordability. The general anticipation was that this could herald an era of universal friendship and knowledge-sharing, ushering in global cooperation and mutual regard. In November 2019, marking 30 years of the Web, Berners-Lee lamented that its initial promise was being largely undermined, and that we were in danger of heading towards a ‘digital dystopia’: What happened? Full article
(This article belongs to the Special Issue Feature Paper in Informatics)
13 pages, 799 KiB  
Article
The Effects of Perceived Quality of Augmented Reality in Mobile Commerce—An Application of the Information Systems Success Model
by Jungmin Yoo
Informatics 2020, 7(2), 14; https://doi.org/10.3390/informatics7020014 - 15 May 2020
Cited by 33 | Viewed by 8029
Abstract
Augmented reality (AR) enables consumers to browse and try products virtually by providing additional information and functionality to mobile shopping. Retailers continue to develop AR technology to engage consumers and enhance their digital shopping experiences. However, despite the growing interest in this technology, [...] Read more.
Augmented reality (AR) enables consumers to browse and try products virtually by providing additional information and functionality to mobile shopping. Retailers continue to develop AR technology to engage consumers and enhance their digital shopping experiences. However, despite the growing interest in this technology, consumers rarely rely on AR due to the quality of its content. This study applies an information systems success model to examine the antecedents that influence the adoption of mobile technology, specifically focusing on consumers’ perception of AR quality and its effect on perceived diagnosticity and consumer satisfaction when using AR technology. Moreover, the study examines how perceived diagnosticity and satisfaction influence loyalty. The study participants were 283 shoppers in Korea who have previously experienced mobile shopping, with data collected through an online survey. The results show that when using AR, (1) the consumer’s perceptions of information quality and visual quality positively influence perceived diagnosticity and satisfaction, (2) perceived diagnosticity positively influences satisfaction and (3) satisfaction positively influences loyalty. These results have practical implications for mobile retailers seeking to develop effective product presentation strategies using innovative technologies. Full article
(This article belongs to the Section Human-Computer Interaction)
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11 pages, 1627 KiB  
Article
Digital Learning Demand for Future Education 4.0—Case Studies at Malaysia Education Institutions
by Siti Dianah Abdul Bujang, Ali Selamat, Ondrej Krejcar, Petra Maresova and Ngoc Thanh Nguyen
Informatics 2020, 7(2), 13; https://doi.org/10.3390/informatics7020013 - 30 Apr 2020
Cited by 53 | Viewed by 18044
Abstract
The rapid growth of the Industrial Revolution (IR) 4.0 has prompted the Malaysian Education Institution to transform the current education system into the future education system 4.0. The impact of IR 4.0 has opened a new paradigm for the Malaysian Educational Institution to [...] Read more.
The rapid growth of the Industrial Revolution (IR) 4.0 has prompted the Malaysian Education Institution to transform the current education system into the future education system 4.0. The impact of IR 4.0 has opened a new paradigm for the Malaysian Educational Institution to ensure that all lecturers are capable of using information and communication technologies (ICT) in teaching and learning. However, there is a challenge in identifying appropriate digital learning platforms and tools to engage students in learning at their own pace. In this paper, we aimed to investigate the demand for digital learning platforms and tools according to the needs of students in Polytechnic Malaysia. The study was conducted randomly among 320 students from various fields of study in selected polytechnics. The analysis method used in this study was a quantitative method using questionnaires as an instrument. The results of our study indicated that e-learning platforms were the highest demand students’ preferred compared to other learning platforms and tools. Hence, the implications of this study could be useful as a guideline to assist Malaysian Polytechnic lecturers in strengthening the practice of using digital learning and develop digital proficiency for enabling education 4.0 in the future. Full article
(This article belongs to the Section Social Informatics and Digital Humanities)
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19 pages, 611 KiB  
Article
Quantifying the Effect of Machine Translation in a High-Quality Human Translation Production Process
by Lieve Macken, Daniel Prou and Arda Tezcan
Informatics 2020, 7(2), 12; https://doi.org/10.3390/informatics7020012 - 23 Apr 2020
Cited by 26 | Viewed by 13450
Abstract
This paper studies the impact of machine translation (MT) on the translation workflow at the Directorate-General for Translation (DGT), focusing on two language pairs and two MT paradigms: English-into-French with statistical MT and English-into-Finnish with neural MT. We collected data from 20 professional [...] Read more.
This paper studies the impact of machine translation (MT) on the translation workflow at the Directorate-General for Translation (DGT), focusing on two language pairs and two MT paradigms: English-into-French with statistical MT and English-into-Finnish with neural MT. We collected data from 20 professional translators at DGT while they carried out real translation tasks in normal working conditions. The participants enabled/disabled MT for half of the segments in each document. They filled in a survey at the end of the logging period. We measured the productivity gains (or losses) resulting from the use of MT and examined the relationship between technical effort and temporal effort. The results show that while the usage of MT leads to productivity gains on average, this is not the case for all translators. Moreover, the two technical effort indicators used in this study show weak correlations with post-editing time. The translators’ perception of their speed gains was more or less in line with the actual results. Reduction of typing effort is the most frequently mentioned reason why participants preferred working with MT, but also the psychological benefits of not having to start from scratch were often mentioned. Full article
(This article belongs to the Special Issue Feature Paper in Informatics)
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10 pages, 225 KiB  
Article
Impact of Information and Communication Technology Diffusion on HIV and Tuberculosis Health Outcomes among African Health Systems
by Sunny Ibeneme, Frances Lee Revere, Lu-Yu Hwang, Suja Rajan, Joseph Okeibunor, Derrick Muneene and James Langabeer
Informatics 2020, 7(2), 11; https://doi.org/10.3390/informatics7020011 - 9 Apr 2020
Cited by 5 | Viewed by 5542
Abstract
Debate regarding the impact of information and communication technology (ICT) on health outcomes has prompted researchers to conduct analyses across many parts of the globe, yet, still little is known about the ICT impact in the African continent. Using a robust multivariate approach, [...] Read more.
Debate regarding the impact of information and communication technology (ICT) on health outcomes has prompted researchers to conduct analyses across many parts of the globe, yet, still little is known about the ICT impact in the African continent. Using a robust multivariate approach, this study examined system-wide impact of ICT diffusion on multiple health outcomes for HIV and tuberculosis among sovereign countries of Africa. This study utilized longitudinal panel data from the World Bank and International Telecommunication Union databases between 2000 and 2016. We relied on a robust linear dynamic panel model to incorporate lagged time variables to estimate the relationships between ICT infrastructure (mobile phone use, internet access, and fixed-telephone subscriptions) and HIV and tuberculosis outcomes. Econometric analyses found that the coefficients of the aggregate ICT variables were all negative (except for fixed telephones) for tuberculosis health measures and HIV prevalence, and positive for access to antiretroviral therapy. The diffusion of mobile phones and internet was associated with decreased incidence of tuberculosis, HIV prevalence, and tuberculosis mortality rates. However, increased diffusion of these three ICT tools was associated with increased access to antiretroviral therapy. Thus, African governments should identify investment strategies for adopting and implementing ICT to improve population health outcomes. Full article
(This article belongs to the Section Health Informatics)
15 pages, 754 KiB  
Article
A Snapshot of Bystander Attitudes about Mobile Live-Streaming Video in Public Settings
by Cori Faklaris, Francesco Cafaro, Asa Blevins, Matthew A. O’Haver and Neha Singhal
Informatics 2020, 7(2), 10; https://doi.org/10.3390/informatics7020010 - 27 Mar 2020
Cited by 10 | Viewed by 6656
Abstract
With the advent of mobile apps such as Periscope, Facebook Live, and now TikTok, live-streaming video has become a commonplace form of social computing. It has not been clear, however, to what extent the current ubiquity of smartphones is impacting this technology’s acceptance [...] Read more.
With the advent of mobile apps such as Periscope, Facebook Live, and now TikTok, live-streaming video has become a commonplace form of social computing. It has not been clear, however, to what extent the current ubiquity of smartphones is impacting this technology’s acceptance in everyday social situations, and how mobile contexts or affordances will affect and be affected by shifts in social norms and policy debates regarding privacy, surveillance, and intellectual property. This ethnographic-style research provides a snapshot of attitudes about the technology among a sample of US participants in two public contexts, both held outdoors in August 2016: A sports tailgating event and a meeting event. Interviews with n = 20 bystanders revealed that many are not fully aware of when their image or speech is being live-streamed in a casual context, and some want stronger notifications of and ability to consent to such broadcasting. We offer design recommendations to help bridge this socio-technical gap. Full article
(This article belongs to the Special Issue Feature Paper in Informatics)
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