*3.6. Data Analysis*

Although there are various well-known taxonomies currently being used to code accidents and incidents datasets, Insley's MxFACS taxonomy and Hieminga's taxonomy were used to code the accidents and serious incidents dataset. According to Hieminga (2018), having reviewed the taxonomies used in "Maintenance Error Decision Aid" (MEDA), which is an investigation tool developed by Boeing, HFACS-ME Framework, CAA Paper 2009/05 [33] and CAP 1367 [32]—none of these appeared to inhibit the two scales of adequate "usability" and "comprehensiveness" at the same time. This led to the solution of developing a di fferent taxonomy to aid in coding incident events.

Another reason why a new taxonomy was not developed for the analysis of accidents and incidents in Nigeria was due to inadequate standard phraseology present in the dataset analysed. It can be argued that although the thematic analysis provides flexibility for the researcher, that same flexibility could lead to inconsistency and a lack of coherence when developing themes from a dataset.

Thematic analysis is a suitable qualitative research method that can be used in a wide range of analysing large qualitative datasets. Its advantage is that trustworthy and insightful findings can be produced using this method [40]. It has also been described as a method used to identify, organise and describe reporting themes within a dataset [41]. This was the main method of qualitative analysis used for the SME's survey.
