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About this book

This book constitutes revised selected papers from the 15th International Conference on Web Information Systems and Technologies, WEBIST 20109 held in Vienna, Austria, in September 2019.

The 10 full papers presented in this volume were carefully reviewed and selected from originally 87 paper submissions. They contribute to the understanding of relevant trends of current research on Web Information Systems and Technologies, including Big Data and Connected Services; Web Performance; Context-aware and Adaptive Web Applications; Human Robot Collaboration and Multi-Agent Systems; Web Application Operating Systems and Platforms; Social Media Advertising and Enhancing Purchase Intentions; Natural Language Query Interfaces and Semantic Web; and Human-computer Interaction and Dynamic Web Pages.

Table of Contents

Frontmatter

webAppOS: Creating the Illusion of a Single Computer for Web Application Developers

Abstract
Unlike traditional single-PC applications, which have access to directly attached computational resources (CPUs, memory, and I/O devices), web applications have to deal with the resources scattered across the network. Besides, web applications are intended to be accessed by multiple users simultaneously. That not only requires a more sophisticated infrastructure but also brings new challenges to web application developers.
The webAppOS platform is an operating system analog for web applications. It factors out the network and provides the illusion of a single computer, the “web computer”. That illusion allows web application developers to focus on business logic and create web applications faster. Besides, webAppOS standardizes many aspects of web applications and has the potential to become a universal environment for them.
Sergejs Kozlovičs

Digital Services Based on Vehicle Usage Data: The Underlying Vehicle Data Value Chain

Abstract
The quantify-everything trend has reached the automotive sector while digitalization is a still the major driver of innovation. New digital services based on vehicle usage data are being created for different actors and purposes, e.g. for individual drivers who want to know about their own driving style and behavior or for fleet managers who want to find out about their fleet. As a side effect, a growing number of ICT start-ups from outside Europe have entered the automotive market to work on innovative use cases. Their digital services are based on the availability of vehicle data on a large scale. To better understand and capture this ongoing digital change in the automotive sector, we present an extended version of the Vehicle Data Value Chain (VDVC) originally published in Kaiser et al. (2019a) and use it as a model for better structuring, describing and testing digital services based on vehicle usage data. We classify digital services of two projects by using the VDVC in our paper, an intermodal mobility service and a pothole and driving style detection service. Thus, we evaluate the VDVC and show its general applicability and usefulness in a practical context.
Christian Kaiser, Andreas Festl, Gernot Pucher, Michael Fellmann, Alexander Stocker

Optimized Coordination and Simulation for Industrial Human Robot Collaborations

Abstract
For years, the manufacturing industry has been investing substantial amounts of research and development work for the implementation of hybrid teams of human workers and robotic units. The composition of hybrid teams requires an optimal coordination of individual players with fundamentally different characteristics and skills. In this paper, we present a highly configurable simulation environment supporting end-users, e.g. manufacturing planners, to optimally prepare, evaluate and improve the collaboration of hybrid teams in the scope of production lines. For generating the optimal task assignment, a GPU-based high-performance optimizer is introduced into the simulation environment. The framework is embedded in a web-based distributed infrastructure that models and provides the involved components (digital human models, robots, visualization environment) as resources. We illustrate the approach with a use case originating from the aircraft industry.
André Antakli, Torsten Spieldenner, Marcel Köster, Julian Groß, Erik Herrmann, Dmitri Rubinstein, Daniel Spieldenner, Ingo Zinnikus

Text Web Templates Considered Harmful

Abstract
For the last decades text-based templates have been the primary option to build dynamic web pages. Until today, no other alternative has rebutted this approach. Yet, using text-based templates has several drawbacks including: 1. blocking resolution, 2. programming languages heterogeneity, 3. limited set of templating features and 4. opinionated idioms. In this paper we show how a domain specific language (DSL) for HTML (such as HtmlFlow, Kotlinx.html or React JSX) can suppress the text-based templates limitations and outperform state-of-the-art template engines (such as JSP, Handlebars, Thymeleaf, and others) in well known benchmarks. To that end, we use the Spring Framework and the sample application PetClinic to show how a DSL for HTML provides unopinionated web templates with boundless resolving features only ruled by the host programming language (such as Java, Kotlin or JavaScript).
Fernando Miguel Carvalho, Luis Duarte, Julien Gouesse

Resource Multiplexing and Prioritization in HTTP/2 over TCP Versus HTTP/3 over QUIC

Abstract
Modern versions of the HTTP protocol, such as HTTP/2 over TCP and the upcoming HTTP/3 over QUIC, use just a single underlying connection to transfer multiple resources during a web page load. The resources are divided into chunks, optionally multiplexed on the connection, and reassembled at the receiver’s side. This poses challenges, as there are many different ways simultaneously requested resources can share the available bandwidth, and not all approaches perform equally well with regards to achieving low loading times. Making matters worse, HTTP/2’s prioritization system for directing this multiplexing behaviour is difficult to use and does not easily transfer to the new HTTP/3.
In this work, we discuss these challenges in detail and empirically evaluate the multiplexing behaviours of 10 different QUIC implementations, as well as 11 different prioritization schemes for HTTP/3. We find that there are large differences between strategies that can have a heavy impact on page load performance, of up to 5x load time speedup in specific conditions. However, these improvements are highly context-sensitive, depending on web page composition and network conditions, turning the best performers for one setup into the worst for others. As such, we also critically evaluate the ability of the newly proposed HTTP/3 prioritization mechanism to flexibly deal with changing conditions.
Robin Marx, Tom De Decker, Peter Quax, Wim Lamotte

CATI: An Extensible Platform Supporting Assisted Classification of Large Datasets

Abstract
More and more, researchers in humanities and companies need large classified document data-sets. These users are not familiar with information retrieval or data science notions. For data scientists, there is also often a need for those classified document data-sets as ground truth. There are multiple tools that allow users to carry out this classification task on large data-sets, involving always a quite expert level in computer and data science. More over, these tools are not usually oriented to the domain of micro-blogs or do not always take into account meta data and attached images as additional dimensions to improve the classification. In this work, we present a platform to enable end users to classify large document collections of several hundred thousands documents in an assisted way, within a humanly acceptable number of clicks, with no coding and without having data science and information retrieval expert knowledge. The system includes a graphical user interface with several classification assistants doing text- and image-based event detection, geographical filtering, image clustering, search services with rich visual metaphors to visualize their results and finally Active Learning (AL) with different sampling strategies. We also present a comparative study on the impact of using different and interchangeable AL components on the number of clicks needed to reach a stable level of accuracy.
Gabriela Bosetti, Előd Egyed-Zsigmond

Progress in Adaptive Web Surveys: Comparing Three Standard Strategies and Selecting the Best

Abstract
Progress indicators inform the participants of web surveys about their state of completion and play a role in motivating participants with a special impact on dropout and answer behaviour. Researchers and practitioners should be aware of this impact and, therefore, should select the right indicator for their surveys with care. In some cases, the calculation of the progress becomes, however, more difficult than expected, especially, in adaptive surveys (with branches). Previous work explains how to compute the progress in such cases based on different prediction strategies, although the quality of prediction of these strategies still varies for different surveys. In this revised paper of a conference paper, we demonstrate the challenges of finding the best strategy for progress computation by presenting a way to select the best strategy via the RMSE measure. We show the application of this method in experimental designs with data from two large real-world surveys and in a simulation study with over 10k surveys. The experiments compare three prediction strategies taking into account the minimum, average, and maximum number of items that participants have to answer by the end of the survey. Selecting the mean as strategy is usually a good choice. However, we found that there is no single best strategy for every case, indicating a high dependence on the structure of the survey to produce good predictions.
Thomas M. Prinz, Jan Plötner, Maximilian Croissant, Anja Vetterlein

A New Approach for Processing Natural-Language Queries to Semantic Web Triplestores

Abstract
Natural Language Query Interfaces (NLQIs) have once again captured the public imagination, but developing them for the Semantic Web has proven to be non-trivial. This is unfortunate, because the Semantic Web offers many opportunities for interacting with smart devices, including those connected to the Internet of Things. In this paper, we present an NLQI to the Semantic Web based on a Compositional Semantics (CS) that can accommodate many particularly tricky aspects of the English language, including nested n-ary transitive verbs, superlatives, and chained prepositional phrases, and even ambiguity. Key to our approach is a new data structure which has proven to be useful in answering NL queries. As a consequence of this, our system is able to handle NL features that are often considered to be non-compositional. We also present a novel method to memoize sub-expressions of a query formed from CS, drastically improving query execution times with respect to large triplestores. Our approach is agnostic to any particular database query language. A live demonstration of our NLQI is available online.
Shane Peelar, Richard A. Frost

Towards a Context-Sensitive User Interaction Framework for Information Systems

Abstract
With the rise of mobile devices, users operate applications in a large variety of contexts. In each of these contexts, a user may have different requirements and preferences regarding an application’s user interface. The context describes the current physical and social environment of the user, his activity and locomotion, as well as the current location and time. Hence, different user interfaces may be more suitable in specific contexts than others. At the moment, a user interface is an integral part of an application, consequently also limiting its usefulness in certain contexts as the information is not presented in the best possible way. Therefore, we propose a way to decouple the user interface from a specific form of representation. Through this decoupling, it is possible to dynamically adapt user interfaces to the user’s specific needs in a context, to increase the value of the application for the user. In this paper, we introduce a general framework for the context-dependent adaptation of user interfaces and evaluate it in the specific context of travel information systems. Travel information systems are particularly suited to evaluate such a framework, as they are usually operated in many different contexts – before a trip, during a trip, and after a trip. The adaptation framework transforms between system-oriented messages and user-oriented messages. The user’s context, the output device capabilities, and the user’s preference, all influence the choice of the actual representation for user-oriented messages. We implemented a prototype of the proposed system and conducted an experimental evaluation focusing on scenarios from the domain of travel information systems.
Stephan Kölker, Felix Schwinger, Karl-Heinz Krempels

Paid Advertising on Social Media: Antecedents and Impacts of General and Specific Attitudes

Abstract
Social media platforms have become important channels of promotional communication from marketers to users with the goal of enhancing purchase intention. One important element of the communication mix is paid advertising on social media. In this context, the interplay between general attitude towards advertising on social media and specific attitude towards an individual advertisement as drivers of purchase intention has not yet been addressed in extant social media research. This study investigates this issue by distinguishing between these two levels of attitude and examining their antecedents as well as their impacts on purchase intention. The empirical test of the nomological network with survey data shows that platform enjoyment is an antecedent of general attitude towards social media advertising whereas perceived meaningfulness and brand awareness drive specific attitude towards the individual advertisement. Perceived intrusiveness has no impact in a social media setting. Specific attitude shows a stronger impact on purchase intention than general attitude although both are significant. The findings point at the need for a clear conceptual differentiation between both levels of attitudes and the role of their antecedents for an appropriate design of paid social media advertisements.
Maria Madlberger, Lisa Kraemmer

Correction to: Web Information Systems and Technologies

Alessandro Bozzon, Francisco José Domínguez Mayo, Joaquim Filipe

Backmatter

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