Today, many applications produce and manipulate a large volume of data, the so-called Big Data. Traditional databases (DB), like relational databases, are not suitable to Big Data management. In order to solve this problem, a new category of DB has been proposed, the so-called NoSQL DB. NoSQL DB have different data models, as well as different access methods which are not usually compatible with the SQL language. In this context, approaches have been proposed for providing mapping of relational DB schemata and operations to equivalent ones in NoSQL DB to deal with large relational data sets in the cloud, focusing on scalability and availability. However, these approaches map relational DB only to a single NoSQL data model and, sometimes, to a specific NoSQL DB product. This paper presents SQLtoKeyNoSQL, a layer able to translate relational schemata as well as SQL commands to equivalent schemata and access methods to any key-oriented NoSQL DB (document-oriented, key-value and column-oriented). We present the architecture of our layer focusing on our mapping strategies, as well as some preliminary experiments that evaluate the impact of SQLtoKeyNoSQL as a solution for transparent mapping of relational DB to key-based NoSQL DB.

Several data-centric applications today produce and manipulate a large volume of data, the so-called Big Data. Traditional databases, in particular, relational databases, are not suitable for Big Data management. As a consequence, some approaches that allow the definition and manipulation of large relational data sets stored in NoSQL databases through an SQL interface have been proposed, focusing on scalability and availability. This paper presents a comparative analysis of these approaches based on an architectural classification that organizes them according to their system architectures. Our motivation is that wrapping is a relevant strategy for relational-based applications that intend to move relational data to NoSQL databases (usually maintained in the cloud). We also claim that this research area has some open issues, given that most approaches deal with only a subset of SQL operations or give support to specific target NoSQL databases. Our intention with this survey is, therefore, to contribute to the state-of-art in this research area and also provide a basis for choosing or even designing a relational-to-NoSQL data wrapping solution.

XML has been explored by both research and industry communities. More than 5500 papers were published on different aspects of XML. With so many publications, it is hard for someone to decide where to start. Hence, this paper presents some of the research topics on XML, namely: XML on relational databases, query processing, views, data matching, and schema evolution. It then summarizes some (some!) of the most relevant or traditional papers on those subjects.

This paper introduces the idea of building a body of knowledge (BoK) to gather the better practices in software requirements traceability that could bring major benefits for analyzing, managing, and implementing software changes impact. The implementation of traceability in the organizations is still a challenge even many studies have been conducted on the subject. The aim of this work is to evaluate traceability approaches focusing on software product traceability by a systematic review. We conducted a series of interviews with practitioners to complement the evaluation. Based on this study, we categorize the approaches, and we propose a body of knowledge (Bok) on traceability requirements TraceBoK. This BoK intends to assist software engineers to decide how to define an implementation of traceability in the development and maintenance of software products. Experts in traceability have evaluated this BoK, and we notice that it meets practitioners needs. However, some improvements must be done in the future versions, and we have made TraceBoK available at tracebok.org. We hope that the proposed BoK helps practitioners to apply better and understand traceability in both academic and industry areas.