Semantic Privacy Policies for Service Description and Discovery in Service-Oriented Architecture

Privacy can be defined as the right of an individual to have information about them accessed and used in conformity with what they consider acceptable. Privacy preservation in Service-Oriented Architecture (SOA) is an open problem. A solution for this problem must include features that support privacy preservation in each area of SOA. This thesis focuses on the areas of service description and discovery. The problems in these areas are that currently it is not possible to describe how a service provider deals with information received from a service consumer as well as discover a service that satisfies the privacy preferences of a consumer. Research has been carried out in these areas, but there is currently no framework which offers a solution that supports a rich description of privacy policies and their integration in the process of service discovery. Thus, the main goal of this thesis is to propose a privacy preservation framework for the areas of service description and discovery in SOA. The framework enhances service description and discovery with the specification and intersection of privacy policies using a base and domain-specific privacy ontologies. Moreover, the framework enhances these areas with an extension to basic SOA that includes roles responsible for implementing a privacy registry as well as mediating the interactions between service consumers and providers and the privacy preservation component. The framework is evaluated through a health care scenario as privacy preservation is an important issue in this domain

Web technologies in a collaborative platform for clinical trials - DOI: 10.3395/reciis.v3i4.236en

Web technologies have changed software development. The changes affect a full range of applications as well as the way users interact with computers. In the health domain, clinical research demands a lot of investment, effort and information in order to safely commercialize a new drug. The WebInVivo project aims at providing automated support for clinical research based on Web technologies. It includes mechanisms for sharing and reusing clinical trial information, such as protocols, protocol data, workflows and workflow metadata and for controlling the protocol life cycle, from modeling to execution. In this project, knowledge from the biomedical area permeates three segments of Brazilian society: (a) research and development, (b) health agents, and (c) the population. This knowledge will be made available through social networks for these segments of Brazilian society

NEOTROPICAL ALIEN MAMMALS: a data set of occurrence and abundance of alien mammals in the Neotropics

Biological invasion is one of the main threats to native biodiversity. For a species to become invasive, it must be voluntarily or involuntarily introduced by humans into a nonnative habitat. Mammals were among first taxa to be introduced worldwide for game, meat, and labor, yet the number of species introduced in the Neotropics remains unknown. In this data set, we make available occurrence and abundance data on mammal species that (1) transposed a geographical barrier and (2) were voluntarily or involuntarily introduced by humans into the Neotropics. Our data set is composed of 73,738 historical and current georeferenced records on alien mammal species of which around 96% correspond to occurrence data on 77 species belonging to eight orders and 26 families. Data cover 26 continental countries in the Neotropics, ranging from Mexico and its frontier regions (southern Florida and coastal-central Florida in the southeast United States) to Argentina, Paraguay, Chile, and Uruguay, and the 13 countries of Caribbean islands. Our data set also includes neotropical species (e.g., Callithrix sp., Myocastor coypus, Nasua nasua) considered alien in particular areas of Neotropics. The most numerous species in terms of records are from Bos sp. (n = 37,782), Sus scrofa (n = 6,730), and Canis familiaris (n = 10,084); 17 species were represented by only one record (e.g., Syncerus caffer, Cervus timorensis, Cervus unicolor, Canis latrans). Primates have the highest number of species in the data set (n = 20 species), partly because of uncertainties regarding taxonomic identification of the genera Callithrix, which includes the species Callithrix aurita, Callithrix flaviceps, Callithrix geoffroyi, Callithrix jacchus, Callithrix kuhlii, Callithrix penicillata, and their hybrids. This unique data set will be a valuable source of information on invasion risk assessments, biodiversity redistribution and conservation-related research. There are no copyright restrictions. Please cite this data paper when using the data in publications. We also request that researchers and teachers inform us on how they are using the data