A flexible data acquisition system for storing the interactions on mashup user interfaces

Abstract Nowadays, mashups applications are growing in popularity. They are accessible by cross-device applications, supporting multiple forms of interaction in cloud environments. In general, mashups manage a huge amount of heterogeneous data from different sources and handle different kinds of users. In this respect, mashup User Interfaces are becoming one of the most important pieces in many kinds of current management systems, such as for certain geographic or environmental information systems working on the Internet. In this type of systems, the user interface plays a particular role due to the huge variety of components or apps that the users need to manage at the same time. However, currently, there has been scant attention paid to the management of the user’s interaction with mashups interfaces. This goal involves the need of having important, well-constructed tools and methods conducting the data acquisition process for managing properly: (a) the interaction over the mashup user interfaces, at the front-end side; (b) the storage of the interaction in relational databases; and (c) well-supported microservices structures handled in the cloud. The fact of having valuable and flexible data acquisition processes encourages the deployment of others important issues of the interaction management, i.e., data searching, data mining, marketing, security, accessibility, usability or traceability of interaction data, among others. In this article, we present a flexible Data Acquisition System capable of capturing the human-computer interactions performed by users over mashup (User) Interfaces with the aim of storing them in a relational database. Firstly, the morphology of traditional mashup applications, their specifications and the relevant information that surrounds an interaction have been studied. Thereupon, a data acquisition system that stores user interaction on mashup based on such specifications was constructed. To achieve that purpose, an architecture of microservices was also designed in the cloud to detect, acquire, and collect the interactions performed over this kind of interfaces. The whole process is ready for acquiring internal data of the information system as well as context information and location awareness. To validate the data acquisition system, some tests on empirical case studies have been developed. Efficiency and effectiveness have also been determined by evaluating the performance of the acquisition system during different load tests. Finally, in order to ensure the software quality, a continuous integration strategy for software development and an easy management of the code have been used, facilitating the software maintenance alongside the microservice architecture, where functionalities are well encapsulated.