• journal_title：Mineralogical Magazine
• Contributor：D. P. Bennett ; R. J. Cuss ; P. J. Vardon ; J. F. Harrington ; R. N. Philp ; H. R. Thomas
• Publisher：Mineralogical Society of Great Britain and Ireland
• Date：2012-12-01
• Format：text/html
• Language：en
• Identifier：10.1180/minmag.2012.076.8.48
• journal_abbrev：Mineralogical Magazine
• issn：0026-461X
• volume：76
• issue：8
• firstpage：3355
• section：Gas

A new data analysis toolkit which is suitable for the analysis of large-scale, long-term datasets and the phenomenon/anomalies they represent is described. The toolkit aims to expose and quantify scientific information in a number of forms contained within a time-series based dataset in a quantitative and rigorous manner, reducing the subjectivity of observations made, thereby supporting the scientific observer. The features contained within the toolkit include the ability to handle non-uniform datasets, time-series component determination, frequency component determination, feature/event detection and characterization/parameterization of local behaviours. An application is presented of a case study dataset arising from the ‘Lasgit’ experiment.