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In the last three decades, the development of the artisanal and small-scale mining (ASM) sector has been increasing in the Democratic Republic of Congo (DRC), bringing more and more urban families into this flourishing business sector, and among them, children. This article aims to look at the often unconceivable, and as a result neglected, social agency of children even when they are involved in activities which are, in the international legislation on children's rights, categorized as one of the worst forms of child labour. To do so, it relies on the results of a socio-anthropological collective research project on children's mining activities which was carried out in a small locality called La Ruashi in the city of Lubumbashi (Province of Katanga). The article aims to provide a comprehensive understanding of these child mining-related activities by looking at different spheres of social relations within which children are embedded. Examining the set of social relations that children have with their families, the broader community and their 'peers', several 'family portraits' are offered, highlighting a heterogeneity of social interpretations regarding this form of child work. It is shown that for families from a middle-class background, this kind of work is often socially disruptive, at the forefront of intergenerational conflict. As for families from lower classes, social changes induced by children's mining activities are often better incorporated into the family habitus. Common dynamics, encountered in all families irrespective of class belonging, is also portrayed. KeywordsChildren's agency, child work in artisanal mining, interdependencies, intergenerational relationships, social differentiation of childhood

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Agricultural energy consumption is an important environmental and social issue. Several diagnosis tools have been proposed to define indicators for analyzing the large-scale energy consumption of agricultural farm activities (year, farm, production activity, etc.). In Bimonte, Boulil, Chanet and Pradel (2012), the authors define (i) new appropriate indicators to analyze agricultural farm energy-use performance on a detailed scale and (ii) show how Spatial Data Warehouse (SDW) and Spatial OnLine Analytical Processing (SOLAP) GeoBusiness Intelligence (GeoBI) technologies can be used to represent, store, and analyze these indicators by simultaneously producing graphical and cartographic reports. These GeoBI technologies allow for the analysis of huge volumes of georeferenced data by providing aggregated numerical values visualized by means of interactive tabular, graphical, and cartographic displays. However, existing data collection systems based on sensors are not well adapted for agricultural data. In this paper, the authors show the global architecture of our GeoBI solution and highlight the data collection process based on agricultural ad hoc sensor networks, the associated transformation and cleaning operations performed by means of Spatial Extract Transform Load (ETL) tools, and a new implementation of the system using a web-services-based loosely coupled SOLAP architecture to provide interoperability and reusability of the complex multi-tier GeoBI architecture. Moreover, the authors detail how the energy-use diagnosis tool proposed in Bimonte, Boulil, Chanet and Pradel (2012) theoretically fits with the sensor data and the SOLAP approach.

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