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This paper aims to propose a method based on Linked Data and Semantic Web principles for composing microservices through data integration. Two frameworks that provide support for the proposed composition method are also described in this paper: Linkedator, which is responsible for connecting entities managed by microservices, and Alignator, which aligns semantic concepts defined by heterogeneous ontologies.

The proposed method is based on entity linking principles and uses individual matching techniques considering a formal notion of identity. This method imposes two major constraints that must be taken into account by its implementation: architectural constraints and resource design constraints.

Experiments were performed in a real-world scenario, using public government data. The obtained results show the effectiveness of the proposed method and that, it leverages the independence of development and composability of microservices. Thereby, the data provided by microservices that adopt heterogeneous ontologies can now be linked together.

This work only considers microservices designed as data providers. Microservices designed to execute functionalities in a given application domain are out of the scope of this work.

The proposed composition method exploits the potential data intersection observed in resource-oriented microservice descriptions, providing a navigable view of data provided by a set of interrelated microservices. Furthermore, this study explores the applicability of ontology alignments for composing microservices.

Designing efficient XML schemas is essential for XML applications which manage semi‐structured data. On generating XML schemas, there are two opposite goals: to avoid redundancy and to provide connected structures in order to achieve good performance on queries. In general, highly connected XML structures allow data redundancy, and redundancy‐free schemas generate disconnected XML structures. The purpose of this paper is to describe and evaluate by experiments an approach which balances such trade‐off through a workload analysis. Additionally, it aims to identify the most accessed data based on the workload and suggest indexes to improve access performance.

The paper applies and evaluates a workload‐aware methodology to provide indexing and highly connected structures for data which are intensively accessed through paths traversed by the workload.

The paper presents benchmarking results on a set of design approaches for XML schemas and demonstrates that the XML schemas generated by the approach provide high query performance and low cost of data redundancy on balancing the trade‐off on XML schema design.

Although an XML benchmark is applied in these experiments, further experiments are expected in a real‐world application.

The approach proposed may be applied in a real‐world process for designing new XML databases as well as in reverse engineering process to improve XML schemas from legacy databases.

Unlike related work, the reported approach integrates the two opposite goal in the XML schema design, and generates suitable schemas according to a workload. An experimental evaluation shows that the proposed methodology is promising.