This files provides some information on the structure of the dataset so that others can properly interpret and make use of them. Please, to understand the full development of this dataset, please refer to the journal paper:

Moura, R., Beer, M., Patelli, E., Lewis, J. and Knoll, F., 2016. Learning from major accidents to improve system design. Safety science, 84, pp.37-45. (https://doi.org/10.1016/j.ssci.2015.11.022)


Basic information:

The dataset is named MATA-D: Multi-Attribute Technological Accidents Datase

When the data were collected: The data was collected between 2013 and 2015.

How the data were collected: the authors (Moura, R., Beer, M., Patelli, E., Lewis, J. and Knoll, F.) have assessed 238 accident investigation reports (where at least 98 are publicly available and easily found on the internet). 

Definitions of the variables: The variables from line 1 to 4, and columns E to BE are the categories found on the CREAM taxonomy to explain human factors and human errors in industry. To know more about the variables, read the paper above and also the book: Hollnagel, E., 1998. Cognitive reliability and error analysis method (CREAM). Elsevier.

At lines 5 to 242 correspond for each one out of the 238 accident reports. Number 1 refers to when a variable was observed on an investigation report.

Details of any software necessary to read and interpret them: only Excel or any other spreadsheet software (e.g. Google sheets) is needed to read the file. The data have been used to different research on human reliabililty analysis.