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

Enhancement of the usability of SOA services for novice users

Recently, the automation of service integration has provided a significant advantage in delivering services to novice users. This art of integrating various services is known as Service Composition and its main purpose is to simplify the development process for web applications and facilitates reuse of services. It is one of the paradigms that enables services to end-users (i.e.service provisioning) through the outsourcing of web contents and it requires users to share and reuse services in more collaborative ways. Most service composers are effective at enabling integration of web contents, but they do not enable universal access across different groups of users. This is because, the currently existing content aggregators require complex interactions in order to create web applications (e.g., Web Service Business Process Execution Language (WS-BPEL)) as a result not all users are able to use such web tools. This trend demands changes in the web tools that end-users use to gain and share information, hence this research uses Mashups as a service composition technique to allow novice users to integrate publicly available Service Oriented Architecture (SOA) services, where there is a minimal active web application development. Mashups being the platforms that integrate disparate web Application Programming Interfaces (APIs) to create user defined web applications; presents a great opportunity for service provisioning. However, their usability for novice users remains invalidated since Mashup tools are not easy to use they require basic programming skills which makes the process of designing and creating Mashups difficult. This is because Mashup tools access heterogeneous web contents using public web APIs and the process of integrating them become complex since web APIs are tailored by different vendors. Moreover, the design of Mashup editors is unnecessary complex; as a result, users do not know where to start when creating Mashups. This research address the gap between Mashup tools and usability by the designing and implementing a semantically enriched Mashup tool to discover, annotate and compose APIs to improve the utilization of SOA services by novice users. The researchers conducted an analysis of the already existing Mashup tools to identify challenges and weaknesses experienced by novice Mashup users. The findings from the requirement analysis formulated the system usability requirements that informed the design and implementation of the proposed Mashup tool. The proposed architecture addressed three layers: composition, annotation and discovery. The researchers developed a simple Mashup tool referred to as soa-Services Provisioner (SerPro) that allowed novice users to create web application flexibly. Its usability and effectiveness was validated. The proposed Mashup tool enhanced the usability of SOA services, since data analysis and results showed that it was usable to novice users by scoring a System Usability Scale (SUS) score of 72.08. Furthermore, this research discusses the research limitations and future work for further improvements

ResEval Mash: A mashup tool for advanced research evaluation

In this demonstration, we present ResEval Mash, a mashup platform for research evaluation, i.e., for the assessment of the productivity or quality of researchers, teams, institutions, journals, and the like - a topic most of us are acquainted with. The platform is specifically tailored to the need of sourcing data about scientific publications and researchers from the Web, aggregating them, computing metrics (also complex and ad-hoc ones), and visualizing them. ResEval Mash is a hosted mashup platform with a clientside editor and runtime engine, both running inside a common web browser. It supports the processing of also large amounts of data, a feature that is achieved via the sensible distribution of the respective computation steps over client and server. Our preliminary user study shows that ResEval Mash indeed has the power to enable domain experts to develop own mashups (research evaluation metrics); other mashup platforms rather support skilled developers. The reason for this success is ResEval Mash's domain-specificity. Copyright is held by the International World Wide Web Conference Committee (IW3C2)

Role-Based Enterprise Mashups with State Sharing, Preservation and Restoration Support for Multi-Instance Executions

Veebimaastikul suurt populaarsust kogunud tavatarbijatele suunatud vidinapõhised veebi-rakendused on loonud soodsa pinnase üldotstarbeliste mashup’ite loomise raamistike ning tööriistade tekkeks. Need tööriistad on eelkõige suunatud tava-Interneti kasutajatele, et luua lihtsaid mashup-tüüpi rakendusi. Samal ajal oleks vidinapõhistest veebirakendustest kasu ka ärirakendustena. Peamiseks takistuseks ärirakenduste loomisel veebipõhiste raken-dustena on keerulisest äriloogikast tulenevad keerukad nõuded ning protsessid. Antud magistritöö uurib, kuidas teostada veebividinatel põhinevate mashup-tüüpi ärirakenduste arendamist nii, et säiluks mashup’ite loomisega seotud peamised eelised, lihtsus ja kiirus. Käesolev magistritöö pakub välja laienduse olemasolevale mashup-tüüpi raamistikule, et toetada mashup’i dekompositsiooni rollipõhisteks vaadeteks. Selleks jagatakse mashup väiksemateks vidinate komplektideks, tagades igale kasutajarollile komplekt just temale vajaminevatest vidinatest. Kuigi igal kasutajarollil võib olla erinev vaade kogu ärirakendusest, tagab käesolevas magistritöös pakutud lahendus suhtluse nende erinevate vaadete vahel. See on vajalik tagamaks mashup’i eksemplari ühtsust kõikide mashup’i vaadete vahel, olenemata sellest, millistest vidinatest antud kasutaja vaade koosneb. Lisaks pakub käesolev magistritöö välja lahenduse toetamaks mitut eksemplari samast vidinapõhisest ärirakendusest ning toetamaks ärirakenduse oleku salvestamist ning taastamist. Kuna ärirakendused on suunatud lahendamaks kasutajate igapäevaseid ülesandeid, on vajalik, et kasutaja saaks valida olemasolevate mashup’i eksemplaride hulgast või alustada uut eksemplari. Lisaks on vajalik, et kasutaja saaks igal ajahetkel rakenduse kasutamise lõpetada selliselt, et hiljem rakenduse kasutamist jätkates oleks tagatud sama rakenduse olek, millest kasutamine katkestati. Väljapakutud lahenduse toimimist testitakse näidisrakendusega, mis realiseerib krediidihalduse protsessi.Recent hype on consumer web mashups has resulted in many general-purpose mashup frameworks and tools. These tools aim at simplifying the creation of mashups targeted to mainstream Internet users. At the same time, mashups are also used for solving specific business-related tasks. Such mashups are called enterprise mashups and more sophisticated frameworks and tools have been developed to support their creation. However, similarly to traditional web application development tools, the complexity of these frameworks is hindering the main benefits associated with mashup development – agility and simplicity. This thesis aims at extending a general-purpose mashup framework to support develop-ment of enterprise mashups while still preserving the simplicity and agility of develop-ment. More specifically, this thesis describes a solution for role-based decomposition of mashups for multi-instance executions with state sharing, preservation and restoration. In this thesis, a general-purpose mashup framework is extended with the concept of roles to support multi-user interaction and decomposing complex enterprise mashups with rich interactions into role-based views. In the context of this thesis, a view is defined as a subset of widgets a mashup is made of. Hence, through views an effective mechanism is provided for decomposing enterprise mashups to mashups as simple as general-purpose mashups. Additionally, this thesis proposes a generic solution for multi-instance mashup executions. In this thesis, each workflow instance is associated with an instance of a mashup. Since situational applications target at solving users day-to-day tasks, it is necessary to support multiple instances of a mashup. Furthermore, support for multiple mashup instances leverages users’ ability to participate in multiple workflow instances and to initialize new ones. Such mashup instances are in this thesis also referred to as mashup sessions. Finally, a solution is proposed for supporting mashup state sharing, preservation and restoration. Sharing states with other users is the key mechanism for facilitating interaction and collaboration between multiple users. State preservation and restoration are needed to allow a user to stop using the mashup and to resume to the same state at a later time. The proposed solution is also validated through a proof of concept application

Proceedings of the First International Workshop on Mashup Personal Learning Environments

Wild, F., Kalz, M., & Palmér, M. (Eds.) (2008). Proceedings of the First International Workshop on Mashup Personal Learning Environments (MUPPLE08). September, 17, 2008, Maastricht, The Netherlands: CEUR Workshop Proceedings, ISSN 1613-0073. Available at http://ceur-ws.org/Vol-388.The work on this publication has been sponsored by the TENCompetence Integrated Project (funded by the European Commission's 6th Framework Programme, priority IST/Technology Enhanced Learning. Contract 027087 [http://www.tencompetence.org]) and partly sponsored by the LTfLL project (funded by the European Commission's 7th Framework Programme, priority ISCT. Contract 212578 [http://www.ltfll-project.org

Personalizing the web: A tool for empowering end-users to customize the web through browser-side modification

167 p.Web applications delegate to the browser the final rendering of their pages. Thispermits browser-based transcoding (a.k.a. Web Augmentation) that can be ultimately singularized for eachbrowser installation. This creates an opportunity for Web consumers to customize their Web experiences.This vision requires provisioning adequate tooling that makes Web Augmentation affordable to laymen.We consider this a special class of End-User Development, integrating Web Augmentation paradigms.The dominant paradigm in End-User Development is scripting languages through visual languages.This thesis advocates for a Google Chrome browser extension for Web Augmentation. This is carried outthrough WebMakeup, a visual DSL programming tool for end-users to customize their own websites.WebMakeup removes, moves and adds web nodes from different web pages in order to avoid tabswitching, scrolling, the number of clicks and cutting and pasting. Moreover, Web Augmentationextensions has difficulties in finding web elements after a website updating. As a consequence, browserextensions give up working and users might stop using these extensions. This is why two differentlocators have been implemented with the aim of improving web locator robustness

Prediction, Recommendation and Group Analytics Models in the domain of Mashup Services and Cyber-Argumentation Platform

Mashup application development is becoming a widespread software development practice due to its appeal for a shorter application development period. Application developers usually use web APIs from different sources to create a new streamlined service and provide various features to end-users. This kind of practice saves time, ensures reliability, accuracy, and security in the developed applications. Mashup application developers integrate these available APIs into their applications. Still, they have to go through thousands of available web APIs and chose only a few appropriate ones for their application. Recommending relevant web APIs might help application developers in this situation. However, very low API invocation from mashup applications creates a sparse mashup-web API dataset for the recommendation models to learn about the mashups and their web API invocation pattern. One research aims to analyze these mashup-specific critical issues, look for supplemental information in the mashup domain, and develop web API recommendation models for mashup applications. The developed recommendation model generates useful and accurate web APIs to reduce the impact of low API invocations in mashup application development. Cyber-Argumentation platform also faces a similarly challenging issue. In large-scale cyber argumentation platforms, participants express their opinions, engage with one another, and respond to feedback and criticism from others in discussing important issues online. Argumentation analysis tools capture the collective intelligence of the participants and reveal hidden insights from the underlying discussions. However, such analysis requires that the issues have been thoroughly discussed and participant’s opinions are clearly expressed and understood. Participants typically focus only on a few ideas and leave others unacknowledged and underdiscussed. This generates a limited dataset to work with, resulting in an incomplete analysis of issues in the discussion. One solution to this problem would be to develop an opinion prediction model for cyber-argumentation. This model would predict participant’s opinions on different ideas that they have not explicitly engaged. In cyber-argumentation, individuals interact with each other without any group coordination. However, the implicit group interaction can impact the participating user\u27s opinion, attitude, and discussion outcome. One of the objectives of this research work is to analyze different group analytics in the cyber-argumentation environment. The objective is to design an experiment to inspect whether the critical concepts of the Social Identity Model of Deindividuation Effects (SIDE) are valid in our argumentation platform. This experiment can help us understand whether anonymity and group sense impact user\u27s behavior in our platform. Another section is about developing group interaction models to help us understand different aspects of group interactions in the cyber-argumentation platform. These research works can help develop web API recommendation models tailored for mashup-specific domains and opinion prediction models for the cyber-argumentation specific area. Primarily these models utilize domain-specific knowledge and integrate them with traditional prediction and recommendation approaches. Our work on group analytic can be seen as the initial steps to understand these group interactions