Addressing Gaps in the Availability of Travel Behaviour Data
J Polak, J-D Schmoecker, Imperial College London; M Wigan, J Cooper, Napier University, UK
Sound transport research and policy making depends upon the availability of appropriate, high quality and up to date information. Thus, the means by which transport related data are collected, stored, processed and made available for use are issues of central concern to the transport profession.
In recent years there has been a significant expansion in the range and complexity of the issues confronting transport researchers and decision makers. Emphasis is now placed not only on the traditional concerns of capacity provision and management but also on the relationship of transport to environmental issues and health impacts and to wider considerations of land use and sustainability. Moreover, much greater emphasis is also being placed on the differential impact of transport on specific groups such as the elderly, the disabled or those groups deemed to be socially excluded. These new policy drivers have given rise to a range of new research questions calling for new and different types of modelling and analysis and hence also, underpinning data. This in turn has exposed a number of significant problems with existing data provision ranging from a basic lack of data on potentially significant aspects of behaviour (e.g., travellers? temporal constraints and preferences) to ambiguities and uncertainties in the definition of key data items. None of these problems are in themselves new, but the growing demand from the research and practitioner communities for more and more complex behavioural data has highlighted afresh their importance.
At the same time as these ?demand? factors are operating, a parallel set of data ?supply? factors are beginning to assert themselves and potentially transform the landscape of data provision:
* Many travel behaviour surveys in the UK and elsewhere are encountering increasing difficulties in obtaining the cooperation of the general public to take part.
* Despite this, there is an increasing emphasis on continuous surveys of individual travel behaviour, principally driven by the need to closely monitor the implementation of policy.
* The rapid emergence of new forms of data collection technologies, especially those based on navigation and positioning technologies and web based methods.
* The increasing availability of large volumes of data from ITS and other automatic operational sources, though uncertainty remains regarding the extent to which these data will be available and configured in a manner useful for secondary research use.
The convergence of these demand and supply factors creates many exciting opportunities, but also poses challenges. The key challenge is to identify those areas in which the opportunities offered by new and emerging technologies and methods can make the most effective contribution to relieving key data bottlenecks on research and practice.
Aims and Objectives
The aim of this paper is to present the results of a project undertaken to identify key areas in which shortcoming in the collection, processing and dissemination of behavioural data have held back needed research and, building on this, to define how best, in the light of current trends in data collection methods, these limitations can be addressed. The specific objectives of this work were to:
* To consult widely with the relevant professional communities (e.g., government, research, operational) to establish the existence and nature of gaps and shortcomings in existing data sources and methods.
* To assess the areas where research gaps can best be addressed by a coordinated ?model? data set collection programme.
* To report on the outcome of the review and consultation process and to make specific recommendations regarding the locations and types of data collection and integration that might most usefully take place.
The project was supported by the UK Engineering and Physical Sciences Research Council. Whilst principal focus of the work was therefore on the UK data context, the review and consultation activities were international in scope.
Structure of the Paper
The paper is divided into a number of sections.
In the first section, we present a brief overview of the historical development of behavioural transport data methods and sources, from simple traffic counts to detailed travel diary and stated preference exercises.
In the second section, we then go on to highlight some of the current policy drivers and directions that are shaping the development of transport data needs and to discuss the potential impact of a number of new technologies (from positioning technologies, to XML-based data definition to data warehousing), throughout the data-lifecycle.
The third section identifies and discuses the key data-related barriers that can inhibit effective research and practice. These barriers are considered in terms of seven general headings:
* Availability: In some cases the required data are simply not collected (e.g., due technical difficulty or cost) or if collected are of insufficient temporal or geographical coverage or quality to render a useful estimate of the required parameter(s).
* Access and use: Ownership and access rights relating to transport data are often opaque resulting in (real or imagined) barriers to access.
* Fragmentation: Data holdings are often fragmented, both physically and institutionally (both within and between organisations), leading to both institutional and operational difficulties in fully exploiting existing data resources.
* Documentation: Opportunities for the re-use and efficient archival storage of data are often limited by the lack of proper data documentation and archival processes and/or administrative provision for re-use.
* Standards: There exist few appropriate standards for the precise characterisation and description of transport activity. Nor are there, in general, agreed metadata conventions for the exchange of information on the precise nature of data holdings.
* Integration: Rarely does a single dataset contain all the information necessary to address a particular research or policy question, leading to the need to combine data from different sources ? a task fraught with statistical and methodological difficulties.
* Uncertainty: Datasets almost invariably embody uncertainty regarding the parameters of the real-world process to which they relate, due to sampling and/or non-sampling errors. Yet data are frequently stored and transferred without taking into account this uncertainty, leading to inhibitions stemming from the perceived risk of inappropriate use.
The paper identifies and discusses a number of existing and potential responses to these barriers, ranging from the development of agreed standards for the characterisation and documentation of behavioural transport data to the
One practical response, which has been growing in popularity in a number of countries in recent years, is the establishment of ?model data sets? for regions or cities. These typically fulfil a number of roles:
* They serve to centralise the control of access to a single (usually public sector) body.
* They ensure a consistent data base for researchers, consultants and others to work with on project analyses to ensure underlying consistency
* They provide a common basis against which a wide range of often-unanticipated explorations can be undertaken on a consistent data base
* They ensure that a richer and better quality managed data set is available to allow new questions to be addressed using data of higher than simply the quality and cost sustainable by a single project would ever allow
The fourth section presents the results of a user consultation exercise held in the UK during the spring and summer of 2003, with relevant sectors of the transport research and practitioner communities and with users of transport data from cognate fields, including social policy and land use planning. These consultations took place both telematically (through a web questionnaire and forum) and through the medium of a series of regional meetings with key individuals. The objective of the consultation exercise was to assess professional opinion regarding the salience of different data-related barriers and to explore views regarding the desirability and potential focus of one or more model data set exercises in the UK. At the time of writing these activities are still ongoing.
In the final section we draw together and synthesise the results of our initial review and the user consultation exercise leading to recommendations regarding the most useful practical steps that can be taken to reduce data-related barriers to behaviourally oriented research and practice.
Association for European Transport