Curricula from the Lattes Platform are a vast source of information for the creation and analysis of researchers' social networks. However, due to the large amount of data, the manual filling-in, and the use of semi-structured data, there are several challenges in the use of Lattes as a source of data. This paper presents a database produced from the mining of more than one million Brazilian Lattes curricula. Moreover, it highlights some descriptive characteristics and relationships among these curricula and among the knowledge areas, directions and challenges to the production and analyzes of social networks generated from these data.

Scientific collaboration has been studied by researchers for decades. Several approaches have been adopted to address the question of how collaboration has evolved in terms of publication output, numbers of coauthors, and multidisciplinary trends. One particular type of collaboration that has received very little attention concerns advisor and advisee relationships. In this paper, we examine this relationship for the researchers who are involved in the area of Exact and Earth Sciences in Brazil and its eight subareas. These pairs are registered in the Lattes Platform that manages the individual curricula vitae of Brazilian researchers. The individual features of these academic researchers and their coauthoring relationships were investigated. We have found evidence that there exists positive correlation between time of advisor–advisee relationship with the advisee’s productivity. Additionally, there has been a gradual decline in advisor–advisee coauthoring over a number of years as measured by the Kulczynski index, which could be interpreted as decline of the dependence.

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Service Oriented Computing (SOC) is a computing paradigm for the agile development of software based on the orchestration of loosely-coupled services. Services perform functions from the solution of simple atomic requests to execution of complex business processes. Nowadays, new services are created from the manual composition of basic Web Services. It is an arduous and susceptible to errors task. To avoid this problem, it is necessary the existence of discovery and automatic composition mechanisms.This paper presents the specification of a architecture and implementation of a prototype for the automatic composition of Web Services using Artificial Intelligence planning techniques and the WSMO ontological model. Moreover, the paper contains a discussion about design and implementation choices and further improvements.

The amount of information currently available, the different media and presentation formats joined with the little time availability of the researchers and people in general, make necessary the implementation of automated tools selecting and evaluating information, aiming at not only optimizing resources but also obtaining useful and personalized results that optimize the daily work of its users. A technique known as Information Filtering could be seen as a solution to this problem. Within an information filtering system, a user introduces a profile in the System which represents his/her information needs; then, the system works to display the relevant information. This article contains a sample of the research carried out by us in this important area, focusing the work towards two of its most representative techniques: "Content Based filtering" and "Collaborative filtering." These techniques have been studied from different points of view, allowing to create a solid framework which involves the necessary criteria for designing and creating a tool using the most outstanding characteristics of each technique. They provide a view to facilitate the work of people devoted to the search, depuration and distribution of information.