Big Data and Causality

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.Causality analysis continues to remain one of the fundamental research questions and the ultimate objective for a tremendous amount of scientific studies. In line with the rapid progress of science and technology, the age of big data has significantly influenced the causality analysis on various disciplines especially for the last decade due to the fact that the complexity and difficulty on identifying causality among big data has dramatically increased. Data mining, the process of uncovering hidden information from big data is now an important tool for causality analysis, and has been extensively exploited by scholars around the world. The primary aim of this paper is to provide a concise review of the causality analysis in big data. To this end the paper reviews recent significant applications of data mining techniques in causality analysis covering a substantial quantity of research to date, presented in chronological order with an overview table of data mining applications in causality analysis domain as a reference directory

Exploratory Analysis of Spanish Energetic Mining Accidents

Using data on work accidents and annual mining statistics, the paper studies work-related accidents in the Spanish energetic mining sector in 1999–2008. The following 3 parameters are considered: age, experience and size of the mine (in number of workers) where the accident took place. The main objective of this paper is to show the relationship between different accident indicators: risk index (as an expression of the incidence), average duration index for the age and size of the mine variables (as a measure of the seriousness of an accident), and the gravity index for the various sizes of mines (which measures the seriousness of an accident, too). The conclusions of this study could be useful to develop suitable prevention policies that would contribute towards a decrease in work-related accidents in the Spanish energetic mining industry

Occupational Accidents in artisanal mining in Katanga, D.R.C.

Introduction: This study focuses on accidents in artisanal mining, to support policies improving miners' employability. Materials and Methods: Based on a questionnaire administered in November 2009 to a sample of 180 miners from the artisanal mining of LUPOTO, in the Province of Katanga, we explored significant trends between the accidents and their consequences and behavioral or sociological variables. Results: During the 12 months preceding the study, 392 accidents occurred, affecting 72.2% of miners. Tools handling represents 51.5%, of the accidents' causes, followed by handling heavy loads (32.9%). Factors such as age, seniority or apprenticeship did not generate significant differences. Contusions were the most common injuries (50.2%), followed by wounds (44.4%). These injuries were located in upper limbs (50.5%) and in lower limbs (29.3%). 80.5% of miners were cared for by their colleagues and 50% of them could not work for more than 3 days. Physical sequelae were reported by 19% of the injured miners. Discussion: Many surveys related to accidents in the area of artisanal mining report such high frequency. The unsuitability of tools to jobs to be done is usually raised as one of the major causes of accidents. The lack of differentiation of the tasks carried out in relation to age is another factor explaining the lack of protective effect of seniority as it minimizes the contribution of experience in the worker's safety. The apprenticeship reported is inadequate; it is rather a learning by doing than anything else. That is why it lacks protective effect. Low income combined with precariousness of artisanal mining are likely to explain the low level of work stoppages. Conclusion: Tools improvement associated with adequate training seem to be the basis of accident prevention. Availability of suitable medical care should improve artisanal miners' recovery after accidents. © 2013 Versita Warsaw and Springer-Verlag Wien.SCOPUS: ar.jinfo:eu-repo/semantics/publishe