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Rail infrastructure managers are forced to work sustainably and efficiently due to increasing cost pressure. Track engineers face increasing difficulties to legitimate necessary measures owing to budget restrictions. This requires an objective tool enabling a proper condition monitoring as well as component-specific, preventive maintenance planning. This book presents a condition evaluation of railway track using innovative track data analyses. Applying functional knowledge - both IT and railway skills - allows extracting smart data out of big data for railway asset management. The only required input data are vertical track geometry and track gauge as already measured and stored by infrastructure managers using state-of-the-art track recording cars. Based on a bottom-up approach, this methodology enables for both establishing net-wide renewal demands and an in-depth assessment of specific track sections. In this way, planning of specific renewal and maintenance measures for track sections becomes just as possible as strategic asset management on a large scale.

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