On the Role of Context in the Design of Mobile Mashups

Abstract

Abstract. 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.

Context-Aware Access to Heterogeneous Resources Through On-the-Fly Mashups

“…The contribution of this paper is a principled definition of the design method underlying CAMUS (Context-Aware Mobile mashUpS) [8], a research project that aims at the conception of high-level abstractions for efficient data and service integration in context-aware mobile applications. The method is general in nature and can be applied in the development of any kind of information system that requires on-the-fly, context-aware data access capabilities (e.g., the method can be used to provide context-aware access to external resources if it is wrapped by a suitable API called from within an application, or it can be used to provide context-aware access to internal data sources in parallel to existing data access channels).…”

“…We preliminarily measured the performance of service selection and invocation; results are encouraging and time log-normally distributed [8]. Next, we will generalize our prototype implementation, parameterize it, and devise suitable transformation logics able to transform the resource schema (already expressed in GraphQL schema language), the CDT and the set of context-agnostic queries into full-fledged GraphQL APIs.…”

“…In this section we describe the synthesis of a query execution plan from the context-aware query and the consequent selection of the related data and services; in the last subsection we then give an account of the real execution flow of our framework, as it has been made concrete in a research prototype [8].…”

“…More refined methods to enlarge the space of solutions considered for tile pattern matching can be also adopted [5]. For example, to address the case when multiple valid services can serve a specific query, we already experimented techniques (i) to invoke them all and then fuse their outputs and also (ii) to apply some ranking strategy, for example based on service quality criteria, and then select the best service [6,8].…”

An Approach for Recommending Contextualized Services in e-Tourism

“…The service wrapper uses the context together with mash-up techniques able to retrieve information from different sources and, therefore, to overcome the limits of "pre-packaged" contents and services [27], whose structures must instead vary according to situation of use during the fruition phase. The main objective is the ability to identify relevant sources, selected on the basis of their adequacy with respect to the user's needs, integrating data and services through a single interface.…”