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Adequate means for easily viewing, browsing and searching knowledge graphs (KGs) are a crucial, still limiting factor. Therefore, this paper aims to present virtual properties as valuable user interface (UI) concept for ontologies and KGs able to improve these issues. Virtual properties provide shortcuts on a KG that can enrich the scope of a class with other information beyond its direct neighborhood.

Virtual properties can be defined as enhancements of shapes constraint language (SHACL) property shapes. Their values are computed on demand via protocol and RDF query language (SPARQL) queries. An approach is demonstrated that can help to identify suitable virtual property candidates. Virtual properties can be realized as integral functionality of generic, frame-based UIs, which can automatically provide views and masks for viewing and searching a KG.

The virtual property approach has been implemented at Bosch and is usable by more than 100,000 Bosch employees in a productive deployment, which proves the maturity and relevance of the approach for Bosch. It has successfully been demonstrated that virtual properties can significantly improve KG UIs by enriching the scope of a class with information beyond its direct neighborhood.

SHACL-defined virtual properties and their automatic identification are a novel concept. To the best of the author’s knowledge, no such approach has been established nor standardized so far.

Light field images (LFIs) have gained popularity as a technology to increase the field of view (FoV) of plenoptic cameras since they can capture information about light rays with a large FoV. Wide FoV causes light field (LF) data to increase rapidly, which restricts the use of LF imaging in image processing, visual analysis and user interface. Effective LFI coding methods become of paramount importance. This paper aims to eliminate more redundancy by exploring sparsity and correlation in the angular domain of LFIs, as well as mitigate the loss of perceptual quality of LFIs caused by encoding.

This work proposes a new efficient LF coding framework. On the coding side, a new sampling scheme and a hierarchical prediction structure are used to eliminate redundancy in the LFI's angular and spatial domains. At the decoding side, high-quality dense LF is reconstructed using a view synthesis method based on the residual channel attention network (RCAN).

In three different LF datasets, our proposed coding framework not only reduces the transmitted bit rate but also maintains a higher view quality than the current more advanced methods.

(1) A new sampling scheme is designed to synthesize high-quality LFIs while better ensuring LF angular domain sparsity. (2) To further eliminate redundancy in the spatial domain, new ranking schemes and hierarchical prediction structures are designed. (3) A synthetic network based on RCAN and a novel loss function is designed to mitigate the perceptual quality loss due to the coding process.

Gender and geographical imbalance in production and impact levels is a pressing issue in global knowledge production. Within Health Sciences, while some studies found stark gender and geographical biases and inequalities, others found little empirical evidence of this marginalization. The purpose of the study is to clear the ambiguity concerning the topic.

Based on a comprehensive and systematic analysis of Health Sciences research data downloaded from the Scival (Scopus/Scimago) database from 2017 to 2020 (n = 7,990), this study first compares gender representation in research productivity, as well as differences in terms of citation per document, citations per document view and view per document scores according to geographical location. Additionally, the study clarifies whether there is a geographic bias in productivity and impact measures (i.e. citation per document, citations per document view and view per document) moderated by gender.

Results indicate that gender inequalities in productivity are systematic at the overall disciplinary, as well as the subfield levels. Findings also suggest statistically significant geographical differences in citation per document, citations per document view, and view per document scores, and interaction effect of gender over the relation between geography and (1) the number of citations per view and (2) the number of views per document.

This study contributes to scientometric studies in health sciences by providing insightful findings about the geographical and gender bias in productivity and impact across world regions.

Multi-view fuzzy clustering algorithms are not widely used in image segmentation, and many of these algorithms are lacking in robustness. The purpose of this paper is to investigate a new algorithm that can segment the image better and retain as much detailed information about the image as possible when segmenting noisy images.

The authors present a novel multi-view fuzzy c-means (FCM) clustering algorithm that includes an automatic view-weight learning mechanism. Firstly, this algorithm introduces a view-weight factor that can automatically adjust the weight of different views, thereby allowing each view to obtain the best possible weight. Secondly, the algorithm incorporates a weighted fuzzy factor, which serves to obtain local spatial information and local grayscale information to preserve image details as much as possible. Finally, in order to weaken the effects of noise and outliers in image segmentation, this algorithm employs the kernel distance measure instead of the Euclidean distance.

The authors added different kinds of noise to images and conducted a large number of experimental tests. The results show that the proposed algorithm performs better and is more accurate than previous multi-view fuzzy clustering algorithms in solving the problem of noisy image segmentation.

Most of the existing multi-view clustering algorithms are for multi-view datasets, and the multi-view fuzzy clustering algorithms are unable to eliminate noise points and outliers when dealing with noisy images. The algorithm proposed in this paper has stronger noise immunity and can better preserve the details of the original image.

Contemporary cities are the subject of new forms of visualization that are not only changing how we see the urban world but how it operates as a social environment. This chapter explores Google's Street View database and the Google Maps platform as sites for the production of distinctive new streams of visual data about cities around the world. I argue that this kind of digital infrastructure presents urban researchers with both new opportunities and new challenges, raising complex questions about the role of visual images in the context of the ongoing transition to a digital, computational, and networked image world.

This study provides a framework to explain the attitude–intention gap in viewing advertisements in social networks. Going beyond the literal and evaluative inconsistency issues in measuring factors with theory of planned behavior (TPB), the authors propose and test a theoretical framework with possible moderators to the relationship between the attitude and behavioral intention.

Two surveys were conducted to test the theoretical framework, one with students and the other with working people in Hanoi, Vietnam. After testing measure reliabilities and validities, hypotheses were tested with regressions using SPSS.

In general, the attitude was still found to have a positive relationship with the behavioral intention. However, the attitude–intention gap still exists as trust in social network was found to moderate the relationship between the attitude and intention with the working people sample while trust in brands advertised facilitate the relationship with the student sample. Interestingly, involvement was not found to moderate the relationship.

Several practical implications can be recommended. In general, the marketing strategy for managers is still to develop positive attitude by consumers toward viewing advertisements. However, personalization strategy should be taken with care in advertisement in social network. Providing consumers with perceived privacy control may help enhance the advertisement effectiveness. Finally, building trusts, on or off the social network, should be optimized to increase the users' intention to view advertisements in social network.

This research offers a new explanation for the attitude–intention inconsistency in general and for viewing advertisements in social networks in particular. Going beyond the measurement issues, the research suggests looking at the process under that the attitude can be formed and activated to impact on the intention. Moreover, mixed findings from two comparable samples provide nuanced insights for different groups of consumers.

The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-10-2021-0563.

This study aims to analyze whether average video watch time or click-through rates (CTR) on YouTube videos are more closely associated with high numbers of views per subscriber using linear regressions.

In 2018, YouTube began releasing CTR data to its video creators. Since 2012, YouTube has emphasized how it favors watch time over clicks in its recommendations to viewers. To the best of the author’s knowledge, this is the first academic study looking at that CTR data to test what matters more for views on YouTube. Is watch time or CTR more important to getting views on YouTube?

The author analyzed new video releases on YouTube. This paper finds almost no or limited evidence that higher percent audience retention or total average watch time per view, respectively, are associated with more views on YouTube. Instead, videos with higher CTR got significantly more views.

The author knows no other study that tests the relative importance of CTR or watch time per view in predicting views for new videos on YouTube.

Aiming to explore how audience consume and produce media events in the digital, distributed and social era we live in, the paper analyzes the viewing patterns of video news items during a media event (the week of Donald Trump's presidential visit to Israel, the first to a country outside the US), compared to a parallel comparable “ordinary” period (two weeks later, in which no inordinacy events occurred). The comparison focused on simultaneous activities of audiences engaged with the event, with either related (i.e. second screening) or unrelated (i.e. media multitasking).

The research is a diary study based on a dedicated mobile app in which respondents reported their news-related behavior during two periods: a media event period and comparable “ordinary” period.

Participants reported watching significantly more news video items in the first day of the media event week compared to the first day of the “ordinary” week. More than half of the viewing reports of the media event were not on TV. In the media event week, there were significantly higher percentages of viewing reports on smartphones/computers and significantly higher percentages of second-screening reports.

This is the first study that empirically explores the viewing patterns of video news items during a media event, compared to an “ordinary” period, focusing on media second screening of audiences engaged with the event. This comparison may reveal whether (1) media events still retain their centrality in a multi-screen era and (2) the role of the internet and online social media in the experience of media events.

Organizations have started using the metaverse to sell non-fungible tokens, execute engineering processes and conduct business meetings. A condition of creating value by moving business processes to the metaverse is acceptance of this technology. In business-to-business scenarios, internal employees and external partners may have different views on the topic but must agree upon new practices. Understanding common motivations and challenges associated with using the metaverse is crucial to its success.

The authors interviewed managers from a pharmaceutical company considering conducting meetings with clients in the metaverse. A series of 23 statements on reasons for (non)-use was generated. Twenty-five individuals (13 employees and 12 clients) then ranked these statements against each other, revealing what would drive or hinder their metaverse use. The authors compared these perspectives to identify common issues.

The authors identified four different views. Views 1 and 2 correspond to internal and external participants, while Views 3 and 4 correspond to external ones only. View 1 is skeptical and underlines the role of peers in acceptance. View 2 is a positive perspective centered on usefulness. View 3 is ambivalent and is centered on efforts required to use the metaverse. View 4 reveals a reversed perspective wherein using the metaverse is a low-effort activity.

This paper proposes a case study probing acceptance of a realistic business use of the metaverse. This paper identifies risks to mitigate and motivations to leverage when proposing metaverse usage in a business-to-business context.