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The transportation domain is characterised by a multitude of different formats to represent data, thus creating a problem of (lack of) interoperability between systems and a need for data conversion. In or- der to cope with the specific requirements of production systems, special attention should be given to performance and scalability of conversion solutions. In this paper, we present a thorough evaluation of the Chimera framework for semantic data conversion through declarative mappings, in both a dataset and message conversion scenarios. We illustrate the experimental results and we offer our considerations and recommenda- tions for the successful implementation of conversion pipelines exploiting Semantic Web technologies.

For connected vehicles, as well as generally for the transportation sector, data are now seen as a precious resource. They can be used to make right decisions, improve road safety, reduce CO2 emissions, or optimize processes. However, analyzing these data is not so much a question of which technologies to use, but rather about where these data are analyzed. Thereby, the emerging vehicle architecture has to become a data-oriented architecture based on embedded computing platforms and take into account new applications, artificial intelligence elements, advanced analytics, and operating systems. Accordingly, in this paper, we introduce the concept of data management to the vehicle by proposing an on-board data management layer, so that the vehicle can play the role of data platform capable of storing, processing, and diffusing data. Our proposed layer supports analytics and data science to deliver additional value from the connected vehicle data and stimulate the development of new services. In addition, our data platform can also form or contribute to shaping the backbone of data-driven transport. An on-board platform was built where the dataset size was reduced 80% and a rate of 99% accuracy was achieved in a 5 min traffic flow prediction using artificial neural networks (ANNs).

Like Dar es Salaam, many large cities face major transport challenges due to the continuous growth of the urban population, private vehicle ownership, congestion, and the fragility of public transportation systems. Transport can become a constraint on both economic growth and social development and inclusion, along with increased negative impacts on health and on the environment. Because of the increasing use of modern technology, transportation has become a data-rich industry. By bringing the data together, and by using open formats, the data can be used for innovative applications to help relieve urban traffic congestion, to improve the provision and operation of public transport services, and to reduce environmental damage with the goal of improving the lives of citizens. The use of data enables transport planners, operators, and users to obtain additional economic, social, and environmental benefits from the physical transport investment and infrastructure. This report shows that Dar es Salaam is on the cusp of a transport data revolution. Generally, the conclusions are that there are no major blocks to progress, but in many areas, there is a lot of work that will need to be done over time.

The transport sector is currently facing a significant transition, with strong drivers includingdecarbonization and digitalization trends, especially in urban passenger transport. The availability ofmonitoring data is at the basis of the development of optimization models supporting an enhancedurban mobility, with multiple benefits including lower pollutants and CO2 emissions, lower energyconsumption, better transport management and land space use. This paper presents two datasetsthat represent time series with a high temporal resolution (five-minute time step) both for vehiclesand bike sharing use in the city of Turin, located in Northern Italy. These high-resolution profileshave been obtained by the collection and elaboration of available online resources providing liveinformation on traffic monitoring and bike sharing docking stations. The data are provided for theentire year 2018, and they represent an interesting basis for the evaluation of seasonal and dailyvariability patterns in urban mobility. These data may be used for different applications, rangingfrom the chronological distribution of mobility demand, to the estimation of passenger transportflows for the development of transport models in urban contexts. Moreover, traffic profiles are at thebasis for the modeling of electric vehicles charging strategies and their interaction with the powergrid.

The globalization of the economy is influencing not only internal and external migration and demographic processes but also urbanization in almost all countries. Big cities are growing fast, increasing the critical role of the transportation. Today, digital technologies and data analytics techniques provide tremendous opportunities to urban planners, central and municipal governments, and residents and the business sector to share and reuse data from various sources to jointly solve problems associated with transportation. The latest global trends in urban planning and management demonstrate significant increase of technology deployment, expansion of Big Data, Open Government Data (OGD), cloud computing, wide spread of mobile devices, and the internet of things. This report presents key findings of the Transport Data Readiness Assessment conducted in the Kyrgyz Republic, with special focus on urban transportation in Bishkek, the capital city. Based on the analysis of the situation, the report identifies obstacles and challenges and provides a set of recommendations to be considered by the central government and the Bishkek city administration, including relevant smart digitally enabled solutions.

There is an increase in traffic volumes and, as such, a requirement for maximisation of the road capacity. It is crucial that there is awareness of the traffic volumes in order to make the right choices regarding road development. Video registrations and related software to video analysis to measure traffic volumes are increasingly used, but there is limited documentation on the reliability of these. This paper compares manual registrations, treated as ground truth, the hardware independent software RUBA and an on-the-shelf product. While the RUBA software, in general, had a reasonable precision on the direction parallel to the camera direction (8% and 3% deviations, respectively); it was less precise regarding transversal-driving vehicles (23% deviation). The on-the-shelf hardware had a significantly higher deviation regarding the two parallel directions, (35% and 67% deviations, respectively) and a reasonable deviation regarding transversal-driving vehicles (11% deviation). It indicates that on-the-shelf hardware might need further calibration in general. There is an increase in traffic volumes and, as such, a requirement for maximisation of the road capacity. It is crucial that there is awareness of the traffic volumes in order to make the right choices regarding road development. Video registrations and related software to video analysis to measure traffic volumes are increasingly used, but there is limited documentation on the reliability of these. This paper compares manual registrations, treated as ground truth, the hardware independent software RUBA and an on-the-shelf product. While the RUBA software, in general, had a reasonable precision on the direction parallel to the camera direction (8% and 3% deviations, respectively); it was less precise regarding transversal-driving vehicles (23% deviation). The on-the-shelf hardware had a significantly higher deviation regarding the two parallel directions, (35% and 67% deviations, respectively) and a reasonable deviation regarding transversal-driving vehicles (11% deviation). It indicates that on-the-shelf hardware might need further calibration in general.

This report summarizes the World Bank’s activities to support the Open Data efforts of developing countries during the period 2012 - 2017. It is largely descriptive, but Chapter 4 includes key analysis and lessons learned. The main objectives of this report are to share information within the World Bank and with its partners and client countries, and to preserve the institutional memory and highlight the lessons learned as a way to improve the development effectiveness of Open Data.

Long-distance travel, respectively interurban travel, makes up a considerable share in transport performance: nearly half of the passenger transport performance is accounted by trips of more than 100 km. Furthermore passenger long-distance travel is achieving considerable growth while other segments of transport rather remain static. Above that passenger long-distance travel is in the focus of politics and research against the background of energy and climate objectives and due to a dynamic supply development. Despite the relevance of this transport segment, an appropriate depiction of long-distance travel behavior within the framework of a multimodal model is missing in Germany and most other countries. One fundamental reason for that is the heterogeneous data situation, resulting from the fact that the topic is of interest by different institutions that generate relevant data. By means of different survey methods the data on long-distance travel behavior is collected, but mostly with deviant focuses or different objectives. The question arises, whether it is possible to generate a consistent and exclusive data set from the different data sources, which can build the basis for long-distance travel model. The aim is, to apply and enhance statistic and econometric methods, to build a model respectively an instrument for data fusion of long-distance travel data. An essential basic work hereby is to clearly differentiate and define the segment of long-distance travel. In the next step the today available data sources are listed and contrasted with each other. Finally I provide a methodological framework on how the available data can enhance the current data basis for long-distance travel behavior. The work intends to contribute to presently existing fundamental challenges in modelling long-distance passenger travel through combining available data in a creative and innovative manner.

It is widely accepted that the costs of underpricing energy are large, whether in advanced or developing countries. This paper explores how large these costs can be by focussing on the size of the external effects that energy subsidies in particular generate in two important sectors—transport and agriculture—in two countries in the Middle East and North Africa, the Arab Republic of Egypt (transport) and the Republic of Yemen (agriculture). The focus is mainly on the costs associated with congestion and pollution, as well as the impact of underpriced energy for depletion of scarce water resources, including through crop selection. Quantifying the size of external effects in developing countries has received relatively little analytical attention, although there is a significant body of literature for developed countries. By building on earlier research, as well as employing the United Nations ForFITS model, the paper provides indicative estimates of the external costs of energy subsidies, as manifested in congestion and pollution. The estimates using simulations indicate that these costs could be materially reduced by elimination or reduction of energy subsidies. The paper also describes the impact of energy subsidies on water consumption in a region where water resources are particularly limited. The findings provide further evidence of the adverse and significant consequences of subsidizing energy.

Various transport-related agencies and local governments develop their respective transport plans or strategies to address bottlenecks and improve outcomes in the transport sector. However, to be able to bring a more focused or targeted intervention that is more inclusive, these various strategies need to focus on establishing interconnectivity between key urban growth centers and between lagging and fast-growing regions, and creating supporting institutions that promote greater integration. Upon the request of the National Economic and Development Authority, a framework plan was developed to provide policy-makers with a strategic framework to help identify the transport needs of the Philippines and guide in implementing an integrated, more coordinated approach to establishing stronger transport infrastructure linkages to support the country’s inclusive growth agenda. The framework plan was developed under the guidance of a vision and goals developed by stakeholders across the Philippines. This comprehensive vision can be summarized as ‘Bringing us all closer together for prosperity.’ The geographic focus of the Framework Plan includes all of the Philippines outside of Metro Manila. This Framework Plan does not replicate the work being done by the Japan International Cooperation Agency (JICA) for Metro Manila (the JICA study covers Metro Manila with an approximate radius of 100 kilometers and is being conducted to evaluate specific transport infrastructure projects for the Metro Manila area). Future improvements and needs of transportation infrastructure to meet the demand for long-distance transport to and from Metro Manila and to other urban/economic centers in the Philippines are considered; nevertheless, national-level strategies recommended in this study affect all areas of the Philippines.

In this paper, we consider a molecular diffusion based communications link that can reliably transport data over-the-air. We show that the system can also reliably transport data across confined structural environments, especially in cases where conventional electromagnetic (EM) wave based systems may fail. In particular, this paper compares the performance of our proprietary molecular communication test-bed with Zigbee wireless sensors in a metal pipe network that does not act as a radio wave-guide. The paper first shows that a molecular-based communication link's performance is determined primarily by the delay time spread of the pulse response. The paper go on to show that molecular-based systems can transmit more reliably in complex and confined structural environments than conventional EM-based systems. The paper then utilizes empirical data to find relationships between the received radio signal strength, the molecular pulse spread, data rate (0.1 bits/s) and the structural propagation environment., IEEE International Conference on Communications (ICC)

Mozambique, the only Lusophone country covered in the agribusiness indicators initiative, has had a turbulent history since independence. Civil unrest over some 20 years and frequent drought in southern Mozambique, coupled with floods near the many waterways that transect the country (mainly east-west), have inhibited an agricultural transformation. Even so, Mozambique could be a regional breadbasket. The country has much potentially usable arable land, along with access to river water for irrigation in many agricultural production zones, particularly in central and northern Mozambique. Sesame, pigeon peas, and cashew exports are significant and rising, not to mention exports of industrial crops such as cotton, leaf tobacco, and sugarcane, yet production of grain and most other food crops remains stagnant. Irrigated area is way below what is possible and needed to increase yields and total agricultural output.

Developed at the request of the Mexican G20 Presidency for consideration by the Finance Ministers and Central Bank Governors at the G20 Leaders' Summit in Mexico, and jointly prepared with the Asian Development Bank, this policy paper positioned green transport in the context of cities development. Urban transport determines the shape of a city and its ecological footprint. Many cities in low and middle income countries are at a crossroads. Policy decisions taken now, while car use is still relatively low and cities retain a relatively transit friendly, compact urban form, will affect how people will live in their cities for many decades into the future. A new paradigm of urban transport can be part of the solution to reversing the deteriorating situation in some cities of developing countries, and supporting others to embark on a sustainable, low carbon, green growth path: developing a city for people rather than cars, and including public and mass transport as a major component of the modal structure. Implementing such a new paradigm can be truly transformational. This joint World Bank and Asian Development Bank paper lays out six aspects, which are most difficult to align, yet, are critical to ensure the sustainability of urban transport systems, visionary leadership, integrated strategy for land use and urban transport, coordination among agencies, domestic capacity, adequate cost recovery, and private participation in the operation and construction of urban transport systems. The paper proposes a set of new initiatives for G20 leaders' consideration, including the development of an umbrella toolkit to guide policy makers in charge of urban planning to make transport decisions best suited to their local contexts.

This paper examines the issue of measuring logistics costs from an applied trade policy research perspective, as well as identifying logistics-intensive sectors. It focuses on currently available data at the macro-and firm-levels. This paper has two main aims. First, it provides a first overview of currently available data relevant to logistics, and suggests some preliminary applications. The second objective of this paper is to frame the issue of logistics cost measurement and data collection in terms of the types of inputs needed for applied trade policy research. The paper is organized as follows. The next section presents an overview of possible directions in applied trade policy research using logistics data. Section three examines existing data sources that can be used to measure domestic logistics costs, focusing on the national accounts, input-output tables, price comparisons, and firm-level data. Section four presents a new methodology for measuring international trade costs, and identifies the proportion of those costs due to logistics. Section five uses input-output data to identify logistics-intensive sectors in a range of countries. Section six concludes. This paper has explored a number of different data sources and methodologies in an effort to move forward on the analysis of logistics costs from a trade policy research perspective. In the future, it will be important to distinguish between data collection efforts that are industry-driven-such as estimates of total logistics costs in Gross Domestic Product (GDP)-and those that are research-driven. Moving further in this direction will help fuel research that identifies sectors in particular countries that are most sensitive to improvements in logistics performance, and which therefore will tend to expand relative to other sectors in the face of logistics sector reforms. From a policy and political economy point of view, it will be important to identify such sectors and make them aware of the potential role logistics can play in facilitating their growth.

Everyone involved in transport and spatial planning is at some stage involved with data production or analysis. Each transport survey is conducted for a set of objectives. Data obtained from these transport surveys do not follow any specific pattern, and are thus difficult to understand. At the same time, a re-search organization conducts a wide variety of surveys ranging from simple road-side interviews to the complex travel diaries, which can be either longitudinal or cross-sectional, and differences in methodology, design, and protocols will often obscure basic similarities between them. Above all, it is almost impossible to collect complete information about the existing transportation system in a single survey. Most transport surveys collect partial information and depend on other sources for more. To under-stand the interactions between the datasets obtained from different surveys, a conceptual data model as a platform to integrate transport and spatial was developed. Both the transport data and spatial data were broadly classified. Transport data was classified as travel survey data, transport data (infrastructure), and transport data (functional); Spatial data were classified into geographic data and geo-data. Individual data models were developed for each classification. These data models help in streamlining the data from longitudinal surveys and standardizing the data from cross-sectional surveys. As a final step, the independent models are integrated into a single conceptual data model that represents integrated transport and spatial data. This final model facilitates easy understanding of the relationships between various data sources and allows the users to pass the information between them., Arbeitsberichte Verkehrs- und Raumplanung, 302

Urban transport planning aims at balancing conflicting challenges by promoting more efficient transport systems while reducing negative impacts. The availability of better and more reliable data has not only stimulated new planning methodologies, but also created challenges for efficient data management and data integration. The major focus of this study is to improve methodologies for representing and integrating multi-source and multi-format urban transport data. This research approaches the issue of data integration based on the classification of urban transport data both from a functional and a representational perspective. The functional perspective considers characteristics of the urban transport system and planning requirements, and categorises data into supply, demand, performance and impact. The representational perspective considers transport data in terms of their spatial and non-spatial characteristics that are important for data representation. These two perspectives correspond to institutional and methodological data integration respectively, and are the foundation of transport data integration. This research is based on the city of Wuhan in China. The methodological issues of transport data integration are based on the representational perspective. A framework for data integration has been put forward, in which spatial data are classified as point, linear and areal types, and the non-spatial data are sorted out as values and temporal attributes. This research has respectively probed the integration of point, linear and areal transport data within a GIS environment. The locations of socio-economic activities are point-type data that need to be spatially referenced. A location referencing process requires a referencing base, source address units and referencing methods. The referencing base consists of such spatial features as streets, street addresses, points of interest and publicly known zones. These referencing bases have different levels of spatial preciseness and have to be kept in a hierarchy. Source addresses in Chinese cities are usually written as one sentence, which has to be divided into address units for automatic geo-coding. As it is difficult to separate from the sentences, the address units have to be clearly identified in survey forms. Depending on the types of address units, the referencing process makes use of either semantic name matching or address matching to link source addresses to features in the referencing base. The name-based and road-based referencing schemes constitute a comprehensive location referencing framework that is applicable to Chinese cities. The relationship between two sets of linear features can be identified with spatial overlay in the case of independent representation, or with internal linkage in a dependent representation. The bus line is such a feature that runs on the street network and can be dependently referenced by streets. In the heavily bus-oriented city of Wuhan, bus lines constitute a large public transit network that is important to transport planning and management. This research has extended conventional bus line representation to a more detailed level. Each bus line has been differentiated as two directional routes that are defined separately with reference to the street network. Accordingly, individual route stops are also represented in the database. These stop sites are spatial features with geometry that are linked to street segments and bus routes by linear location referencing methods. A data model linking base street network, bus lines and routes, line and route stops, and other bus operations data has been constructed. The benefits of the detailed model have been demonstrated in several transport applications. Zonal data transitions include three types of operations, i.e. aggregation, areal interpolation and disaggregation. This study focuses on disaggregating data from larger zones to smaller zones. In the context of Wuhan, zonal data disaggregation involves the allocation of statistical data from statistical units to smaller parcels. Given the availability of land use data, a weighted approach reflecting spatial variations has been applied in the disaggregation process. Two technical processes for disaggregation have been examined. Weighted area-weighting (WAW) is an adaptation of the classic area-weighting method, and Monte Carlo simulation (MC) is a stochastic process based on a raster data model. The MC outcome is more convenient for subsequent re-aggregation, and is also directly available for micro-simulation. An important contribution arising from this zonal integration study is that two standardised disaggregation tools have been developed within a GIS environment. The research has also explored the institutional aspect of data integration. The findings of this study show that there is generally a good institutional transport structure in the city of Wuhan and that there is also a growing awareness of using information technology. Professional cooperation exists among transport organisations, but not yet at a level for data sharing. An integrated data support framework requires data sharing. In such a framework, it should be possible to know where to get data for specific transport studies, or which kind of research an institution supports.

Urban transport planning aims at balancing conflicting challenges by promoting more efficient transport systems while reducing negative impacts. The availability of better and more reliable data has not only stimulated new planning methodologies, but also created challenges for efficient data management and data integration. The major focus of this study is to improve methodologies for representing and integrating multi-source and multi-format urban transport data. This research approaches the issue of data integration based on the classification of urban transport data both from a functional and a representational perspective. The functional perspective considers characteristics of the urban transport system and planning requirements, and categorises data into supply, demand, performance and impact. The representational perspective considers transport data in terms of their spatial and non-spatial characteristics that are important for data representation. These two perspectives correspond to institutional and methodological data integration respectively, and are the foundation of transport data integration. This research is based on the city of Wuhan in China. The methodological issues of transport data integration are based on the representational perspective. A framework for data integration has been put forward, in which spatial data are classified as point, linear and areal types, and the non-spatial data are sorted out as values and temporal attributes. This research has respectively probed the integration of point, linear and areal transport data within a GIS environment. The locations of socio-economic activities are point-type data that need to be spatially referenced. A location referencing process requires a referencing base, source address units and referencing methods. The referencing base consists of such spatial features as streets, street addresses, points of interest and publicly known zones. These referencing bases have different levels of spatial preciseness and have to be kept in a hierarchy. Source addresses in Chinese cities are usually written as one sentence, which has to be divided into address units for automatic geo-coding. As it is difficult to separate from the sentences, the address units have to be clearly identified in survey forms. Depending on the types of address units, the referencing process makes use of either semantic name matching or address matching to link source addresses to features in the referencing base. The name-based and road-based referencing schemes constitute a comprehensive location referencing framework that is applicable to Chinese cities. The relationship between two sets of linear features can be identified with spatial overlay in the case of independent representation, or with internal linkage in a dependent representation. The bus line is such a feature that runs on the street network and can be dependently referenced by streets. In the heavily bus-oriented city of Wuhan, bus lines constitute a large public transit network that is important to transport planning and management. This research has extended conventional bus line representation to a more detailed level. Each bus line has been differentiated as two directional routes that are defined separately with reference to the street network. Accordingly, individual route stops are also represented in the database. These stop sites are spatial features with geometry that are linked to street segments and bus routes by linear location referencing methods. A data model linking base street network, bus lines and routes, line and route stops, and other bus operations data has been constructed. The benefits of the detailed model have been demonstrated in several transport applications. Zonal data transitions include three types of operations, i.e. aggregation, areal interpolation and disaggregation. This study focuses on disaggregating data from larger zones to smaller zones. In the context of Wuhan, zonal data disaggregation involves the allocation of statistical data from statistical units to smaller parcels. Given the availability of land use data, a weighted approach reflecting spatial variations has been applied in the disaggregation process. Two technical processes for disaggregation have been examined. Weighted area-weighting (WAW) is an adaptation of the classic area-weighting method, and Monte Carlo simulation (MC) is a stochastic process based on a raster data model. The MC outcome is more convenient for subsequent re-aggregation, and is also directly available for micro-simulation. An important contribution arising from this zonal integration study is that two standardised disaggregation tools have been developed within a GIS environment. The research has also explored the institutional aspect of data integration. The findings of this study show that there is generally a good institutional transport structure in the city of Wuhan and that there is also a growing awareness of using information technology. Professional cooperation exists among transport organisations, but not yet at a level for data sharing. An integrated data support framework requires data sharing. In such a framework, it should be possible to know where to get data for specific transport studies, or which kind of research an institution supports.

The report is a study of data requirements and methodologies for goods transport. The study is intended to provide the basis for general discussion about the application of goods transport models in Denmark. The report provides an overview of different types of models and data availability.

The Ph. D. thesis describes and analyses how environmental obejctives and strategies have materialised in the real-life context of local transport policies and plans, how environmental perspectives have been picked up by policy makers concerned with transport issues, how policy and planning processes have been effected.

Maritime transport costs significantly impede international trade. This article examines why these costs are so high in some countries and quantifies the importance of two explanations: restrictive trade policies and private anticompetitive practices. It finds that both matter, but the latter have a greater impact. Trade liberalization and the breakup of private carrier agreements would lead to an average of one-third lower liner transport prices and to cost savings of up to US dollar 3 billion on goods carried to the United States alone. The policy implications are clear: there is a need not only for further liberalization of government policy but also for strengthened international disciplines on restrictive business practices. The authors propose an approach to developing such disciplines in the current round of services negotiations at the World Trade Organization (WTO).

Transportation Research Circular, E-C008, ISSN:0097-8515