Abstract
Contemporary urban transportation networks are facing challenges to address the growing needs of mobility, all the while improving their economic gains and environmental sustainability. Several studies demonstrate that competitive alternatives to individual private transport are able to address these challenges, such as public transportation services. Thus, the need for optimising their operational efficiency and offer user-centric service delivery arises, with a range of challenges related to the inherent complexity of urban transportation networks as well as the range of dynamic elements involved in such systems. An innovative approach to this problem leverages personal mobile devices in combination with collaborative exchange of information. In this study a system was developed to combine information provided by travellers with data from public transport operators. The result is a rich model of the transportation network that enables the distribution of information in a personalized way and in real-time: the Seamless Mobility solution. Large-scale and expensive infrastructures, such as existing ticketing systems, constitute a threat to such flexibility and traveller access to services. As a result, a distributed architecture was targeted with the goal of integrating personal mobile devices in the infrastructure, with benefits for travellers and transport operators. The proposed solution integrates a broad scope of challenges, including application of secure mobile payments methods, data aggregation from different components and distribution based on relevance techniques. With the implementation of this solution we expect to positively impact the way travellers and transport operators interact, and contribute towards mobility services that are more agile and adequate, taking into account that mobility patterns vary from person to person, seasonally, and even throughout a day. (C) 2016 The Authors. Published by Elsevier B.V.

Abstract
This paper proposes an ontology-based approach to visualizing urban mobility data. Our approach, which is in ongoing development, is centered in a visualization-oriented urban mobility ontology that is used to semantically characterize data and visualization techniques. We present a practical application to a public transportation network of the city of Porto, Portugal. We address how semantics can empower and facilitate tasks like automatic recommendation of visualization techniques, and definition of a data filter based on passengers' journey patterns.

Abstract
This paper develops an innovative methodology to assess municipal performance concerning the environmental efficiency of new buildings construction, focusing on the consumption of different types of materials. This study aims to support local governments in the definition of policies for improvements in service provision based on the results of a benchmarking study. The methodology developed includes two stages. The first step concerns the evaluation of municipal environmental efficiency using Data Envelopment Analysis and the identification of factors that may explain different levels of performance. The second step enables the classification of municipalities in terms of the efforts required to achieve environmental efficiency. For this purpose, we used clustering analysis, namely the k-means algorithm. To illustrate the methodology developed, we analyzed the data of the major materials used in the construction of new buildings (metals, non-metallic minerals, fossil fuels, and biomass) in the municipalities of Lisbon metropolitan area between 2003 and 2009. The study revealed that the environmental efficiency of new buildings construction varies considerably among municipalities, suggesting a high potential for performance improvement.

Abstract
This paper introduces VUMO, a visualization-oriented ontology that formalizes the knowledge about urban mobility events (e.g. ridership and travel intentions) and visualization techniques. It focuses on serving as a foundation for the development of semi-automatic visualization tools, while also facilitating the process of data integration. The ontology allows techniques to be characterized with human perception factors, so they can be considered when automatically infering recommended techniques for a dataset. The ultimate goal is to benefit transportation decision makers and foster the development of semantically rich visualization techniques. We propose a structured visualization workflow based on VUMO, and apply it to the development of a prototype featuring real data extracted from a journey planner mobile application.

Abstract
In Public Transportation systems, accurate representation of information has been key for users to take the more advantages of the services and fulfil their travel needs. The Spider Map is a particular schematic representation to illustrate all travel possibilities from a given geographical location. Recently the Spider Map interaction and generation process automation have been studied, although there are yet different possibilities to explore in the technological approach and interactive solution fields. This research proposes the Cobweb solution, dissecting the components of an Interactive Spider Map, focusing on the interactive dynamic potential, the ways to represent information, challenging the existing standard. An implementation of this solution is evaluated using carefully designed user tests to validate the design decisions, taking into consideration different interaction alternatives for each phase of the map generation. The results show improvements regarding the traditional alternative, with positive user response, valuing highly context awareness and information features.

Abstract
A methodology for estimating the destination of passenger journeys from automated fare collection (AFC) system data is described. It proposes new spatial validation features to increase the accuracy of destination inference results and to verify key assumptions present in previous origin-destination estimation literature. The methodology applies to entry-only system configurations combined with distance-based fare structures, and it aims to enhance raw AFC system data with the destination of individual journeys. This paper describes an algorithm developed to implement the methodology and the results from its application to bus service data from Porto. The data relate to an AFC system integrated with an automatic vehicle location system that records a transaction for each passenger boarding a bus, containing attributes regarding the route, the vehicle, and the travel card used, along with the time and the location where the journey began. Some of these are recorded for the purpose of allowing onboard ticket inspection but additionally enable innovative spatial validation features introduced by the methodology. The results led to the conclusion that the methodology is effective for estimating journey destinations at the disaggregate level and identifies false positives reliably.