On the Role of Context in the Design of Mobile Mashups

This paper presents a design methodology and an accompanying platform for the design and fast development of Context-Aware Mobile mashUpS (CAMUS). The approach is characterized by the role given to context as a first-class modeling dimension used to support i) the identification of the most adequate resources that can satisfy the users' situational needs and ii) the consequent tailoring at runtime of the provided data and functions. Context-based abstractions are exploited to generate models specifying how data returned by the selected services have to be merged and visualized by means of integrated views. Thanks to the adoption of Model-Driven Engineering (MDE) techniques, these models drive the flexible execution of the final mobile app on target mobile devices. A prototype of the platform, making use of novel and advanced Web and mobile technologies, is also illustrated

From mashups to telco mashups: A survey

Given their increasing popularity and novel requirements and characteristics, telco mashups deserve an analysis that goes beyond what's available for mashups in general. Here, the authors cluster telco services into different types, analyze their features, derive a telco mashup reference architecture, and survey how well existing mashup tools can respond to these mashups' novel needs. © 2012 IEEE

A Web Services Infrastructure for the Management of Mashup Interfaces

In the technological world of today, user interfaces (as an essential part of many software applications) are constantly changing in order to meet the needs of different users and adapt to their environment. Accordingly, there is a need for mechanisms to carry out these change processes. This article describes a structure of web services which support the adaptation which constructs mashup type web user interfaces. These interfaces are constructed using third party component architectures, called COTSgets

End-user composition of interactive applications through actionable UI components

Developing interactive systems to access and manipulate data is a very tough task. In particular, the development of user interfaces (UIs) is one of the most time-consuming activities in the software lifecycle. This is even more demanding when data have to be retrieved by accessing flexibly different online resources. Indeed, software development is moving more and more toward composite applications that aggregate on the fly specific Web services and APIs. In this article, we present a mashup model that describes the integration, at the presentation layer, of UI components. The goal is to allow non-technical end users to visualize and manipulate (i.e., to perform actions on) the data displayed by the components, which thus become actionable UI components. This article shows how the model has guided the development of a mashup platform through which non-technical end users can create component-based interactive workspaces via the aggregation and manipulation of data fetched from distributed online resources. Due to the abundance of online data sources, facilitating the creation of such interactive workspaces is a very relevant need that emerges in different contexts. A utilization study has been performed in order to assess the benefits of the proposed model and of the Actionable UI Components; participants were required to perform real tasks using the mashup platform. The study results are reported and discussed

How Do Web-Active End-User Programmers Forage?

Web-active end-user programmers spend substantial time and cognitive effort seeking information while debugging web mashups, which are platforms for creating web applications by combining data and functionality from two or more different sources. The debugging on these platforms is challenging as end user programmers need to forage within the mashup environment to find bugs and on the web to forage for the solution to those bugs. To understand the foraging behavior of end-user programmers when debugging, we used information forging theory. Information foraging theory helps understand how users forage for information and has been successfully used to understand and model user behavior when foraging through documents, the web, user interfaces, and programming environments. Through the lens of information foraging theory, we analyzed the data from a controlled lab study of eight web-active end-user programmers. The programmers completed two debugging tasks using the Yahoo! Pipes web mashup environment. On analyzing the data, we identified three types of cues: clear, fuzzy, and elusive. Clear cues helped participants to find and fix bugs with ease while fuzzy and elusive cues led to useless foraging. We also identified the strategies used by the participants when finding and fixing bugs. Our results give us a better understanding of the programming behavior of web-active end-users and can inform researchers and professionals how to create better support for the debugging process. Further, this study methodology can be adapted by researchers to understand other aspects of programming such as implementing, reusing, and maintaining code

Supporting Mobile Web Augmentation by End Users

This article presents MoWA Authoring, an End User Development platform supporting the improvement of existing –usually third party– Web applications with mobile features. This enhancement is carried out by the addition of specific behaviours, mostly dependent on context values. The tool assists the user in the construction of applications by easily selecting the components that fit his needs. A series of forms allows selecting sensors, context values of interest and digital counterparts to define an augmentation layer. The latter is composed of augmentation units, called augmenters, which are configurable through widgets that can be placed over the presentation layer of any Web application.Trabajo publicado en Lecture Notes in Computer Science book series (LNCS, vol. 10360)Laboratorio de Investigación y Formación en Informática Avanzad

UNDERSTANDING ADVANCES IN WEB TECHNOLOGIES: EVOLUTION FROM WEB 2.0 TO WEB 3.0

The current generation of Web applications (Web 2.0) have made them an outright phenomenon in today’s society helping to redefine the way organisations and individuals communicate and collaborate with each other. The purpose of this paper is to conceptualise the evolution of Web technologies from a user perspective. Based on inference from existing studies, this paper attempts to identify the architectural direction that the next generation (Web 3.0) of Web applications would meld itself into. The paper emphasizes limitations of current Web technologies and how future trends may address these limitations by focusing on migration that has been witnessed in the scope of the applications presented and features delivered on the Web from a users’ perspective

Measuring Mental Effort for Creating Mobile Data Collection Applications

To deal with drawbacks of paper-based data collection procedures, the QuestionSys approach empowers researchers with none or little programming knowledge to flexibly configure mobile data collection applications on demand. The mobile application approach of QuestionSys mainly pursues the goal to mitigate existing drawbacks of paper-based collection procedures in mHealth scenarios. Importantly, researchers shall be enabled to gather data in an efficient way. To evaluate the applicability of QuestionSys, several studies have been carried out to measure the efforts when using the framework in practice. In this work, the results of a study that investigated psychological insights on the required mental effort to configure the mobile applications are presented. Specifically, the mental effort for creating data collection instruments is validated in a study with N=80 participants across two sessions. Thereby, participants were categorized into novices and experts based on prior knowledge on process modeling, which is a fundamental pillar of the developed approach. Each participant modeled 10 instruments during the course of the study, while concurrently several performance measures are assessed (e.g., time needed or errors). The results of these measures are then compared to the self-reported mental effort with respect to the tasks that had to be modeled. On one hand, the obtained results reveal a strong correlation between mental effort and performance measures. On the other, the self-reported mental effort decreased significantly over the course of the study, and therefore had a positive impact on measured performance metrics. Altogether, this study indicates that novices with no prior knowledge gain enough experience over the short amount of time to successfully model data collection instruments on their own. Therefore, QuestionSys is a helpful instrument to properly deal with large-scale data collection scenarios like clinical trials

User-defined semantics for the design of IoT systems enabling smart interactive experiences

© The Author(s) 2020. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.Automation in computing systems has always been considered a valuable solution to unburden the user. Internet of Things (IoT) technology best suits automation in different domains, such as home automation, retail, industry, and transportation, to name but a few. While these domains are strongly characterized by implicit user interaction, more recently, automation has been adopted also for the provision of interactive and immersive experiences that actively involve the users. IoT technology thus becomes the key for Smart Interactive Experiences (SIEs), i.e., immersive automated experiences created by orchestrating different devices to enable smart environments to fluidly react to the final users’ behavior. There are domains, e.g., cultural heritage, where these systems and the SIEs can support and provide several benefits. However, experts of such domains, while intrigued by the opportunity to induce SIEs, are facing tough challenges in their everyday work activities when they are required to automate and orchestrate IoT devices without the necessary coding skills. This paper presents a design approach that tries to overcome these difficulties thanks to the adoption of ontologies for defining Event-Condition-Action rules. More specifically, the approach enables domain experts to identify and specify properties of IoT devices through a user-defined semantics that, being closer to the domain experts’ background, facilitates them in automating the IoT devices behavior. We also present a study comparing three different interaction paradigms conceived to support the specification of user-defined semantics through a “transparent” use of ontologies. Based on the results of this study, we work out some lessons learned on how the proposed paradigms help domain experts express their semantics, which in turn facilitates the creation of interactive applications enabling SIEs.Peer reviewedFinal Published versio