Clear Visual Separation of Temporal Event Sequences

Extracting and visualizing informative insights from temporal event sequences becomes increasingly difficult when data volume and variety increase. Besides dealing with high event type cardinality and many distinct sequences, it can be difficult to tell whether it is appropriate to combine multiple events into one or utilize additional information about event attributes. Existing approaches often make use of frequent sequential patterns extracted from the dataset, however, these patterns are limited in terms of interpretability and utility. In addition, it is difficult to assess the role of absolute and relative time when using pattern mining techniques. In this paper, we present methods that addresses these challenges by automatically learning composite events which enables better aggregation of multiple event sequences. By leveraging event sequence outcomes, we present appropriate linked visualizations that allow domain experts to identify critical flows, to assess validity and to understand the role of time. Furthermore, we explore information gain and visual complexity metrics to identify the most relevant visual patterns. We compare composite event learning with two approaches for extracting event patterns using real world company event data from an ongoing project with the Danish Business Authority.Comment: In Proceedings of the 3rd IEEE Symposium on Visualization in Data Science (VDS), 201

Empirical evidence on the relationship between fare and travel distance

Author's accepted version (postprint)

The relationship between travel distance and fares, time costs and generalized costs in passenger transport

Theoretical studies have discussed the importance of travel distance in passenger transport but the empirical evidence is weak. This paper reviews empirical studies and gives a comparative analysis of the relationship between travel distance on one hand and fare, generalized journey costs and time costs on the other hand for air transport, bus, fast boat, ferry, and rail in Norway. Presuming that all transport modes are valid alternatives, a comparison of generalised journey costs for a passenger can identify which transport mode is preferred for a given distance. Fast boat is the preferred alternative for trips up to 50 kms followed by bus up till about 90 kms where rail becomes the best alternative for longer distances. The passengers’ marginal generalised costs for travelling one more kilometre depend on transport mode and vary from NOK 2 to NOK 6, of which the marginal time costs share varies from 11 % to 72 %

Service Quality Aspects in Ferry Passenger Transport - Examples from Norway

Changes in the level of service for scheduled passenger transport influence both operating costs and passengers’ generalised travel costs. This article focuses on the service level and service quality of ferry crossings using empirical data from a survey carried out in Norway in 2008. Using gap analysis we document how both enterprise and household ferry users rate the importance of and their current satisfaction with a number of service aspects concerning Norwegian ferries. Fares, discount schemes and sufficient capacity in the summer are rated as highly important but providing a low level of satisfaction by both user enterprise and household respondents. These elements should, therefore, be paid special attention to when adjusting the service level. The results from the survey are of special interest for the Norwegian transport authorities with respect to revisions of the national ferry service standard, and the survey method can provide a useful tool when evaluating transport initiatives

Using Standardized Revenue and Cost Norm Analyses to Reveal Subsidy Fraud in Contracted Public Transport Services

Author's accepted version (postprint).This is an Accepted Manuscript of an article published by Taylor & Francis in Transport Reviews on 20/10/2009, available online: http://wwww.tandfonline.com/10.1080/01441640902986866.In 2004, one of the biggest ferry operators in Norway was found guilty of having intentionally attempted to defraud the state of about 113 million Norwegian kroner in subsidies by underreporting revenues and overstating costs during the period 1992-2002. The company and five of the top managers were convicted and the case was regarded as one of the most serious subsidy offences ever committed in Norway. The aim of this article is to show that standardized revenue and cost norm models from the state can deter operators from committing such offences and when relevant detecting the fraud attempts at an early stage. Our model suggests that the operator in question overstated costs by about 19% and that the actual subsidy fraud attempt was about three times higher than concluded by the Court