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A Data-Interoperability Aware Software Architecture

Making heterogeneous data sources homogeneous manually and off-line can become a high time-consuming task. This paper presents a software architecture that extends the standardized-based architectures for heterogeneous sensors with components to also support devices and data that are not compliant with standards. The defined architecture is based on Internet of Things (IoT) layered architectures that establish perception, network, middleware, application, and business as main layers. To define the architecture, an architectural framework was used; this framework supports the identification of non-compliant data, providing then a different processing path. This proposed architecture covers a wide spectrum of data interoperability addressing the IoT challenge of «Interoperability and Standardization». The implemented solution proved that the processing time between data acquisition and the feeding of analysis algorithms can be reduced from 100% to approximately to 1% with systems based on the proposed architecture compared with those that manage data manually and off-line.

Achieving software-assisted knowledge generation through model-driven interoperability

A software system is a complex artefact involving several aspects, such as requirements and behavioural workflows. Information systems engineering has generated several approaches to create software models reflecting these aspects. To obtain the necessary integration, the relations between the involved models must be expressed formally. Currently, this necessity is particularly evident in systems built to assist users in performing knowledge generation, such as scientific knowledge-management systems. Model-Driven Engineering provides some interoperability techniques for expressing inter-model relations. In this paper, a specific metamodel is proposed for integrating different modelling perspectives of software systems built for assisting users in knowledge generation. Furthermore, the integration metamodel is initially validated through its application to the integration of modelling perspectives of a system to assist knowledge generation in the cultural heritage domain. The integration metamodel proposed allows the system to make knowledge generation decisions by manipulating the relations between the involved models on behalf of the user.