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Chapter 2
State of Transportation Statistics

The U.S. transportation system, one of the world’s largest, serves 284 million residents and 7 million business establishments dispersed over the fourth largest country (by land area). This complex system enables economic activity, making it possible for even small towns or businesses to physically link with the rest of the world, and offers citizenry a high degree of mobility, facilitating access to goods, services, work, recreation, and social activities. The system must continually adjust to changes in external conditions, such as shifting markets, global competition, changing demographics, safety concerns, weather conditions, energy and environmental constraints, and security needs.

Given the nature of the system, good information is key to effective transportation decisionmaking, whether by governments, businesses, or consumers. Having the right data and information available in the right form, at the right time can affect decisions as different in scale and importance as what route to pick on the morning commute, which modes to use to ship goods, where to locate transportation facilities, and how to allocate public or private investments for transportation.

With such vastly different uses for transportation data and information, the system for collection, analysis, and dissemination of this data and information is itself complex, involving multiple public and private entities. Some of the complexity arises from the uniqueness of key transportation data (box 1). Public access to some information—especially that collected by government agencies—is often not difficult, while information collected by or from private sources is frequently kept proprietary or confidential. States, planning organizations, localities, and transportation authorities collect much data, often for operational and planning purposes; however, its utility beyond the specific location may be limited, because it is not available in a form that enables others to easily use it, for example, a standard format. The federal government often obtains data from states or other public agencies and collects data through surveys and other means, for its own purposes.

With all of this data, several questions arise:

• Do the data cover the right subjects?
• Are the data relevant to decisionmaking needs?
• Are the data reliable and accurate?
• Are the data understandable, accessible, and timely for decisionmaking?

With an eye toward improving the transportation information system, Congress in 1991 authorized the establishment of the Bureau of Transportation Statistics (BTS). BTS’s mandates were reaffirmed by reauthorization legislation in 1998. As part of this mandate, Congress called on BTS to assess both the state of the transportation system and the state of transportation statistics in a transportation statistics annual report. Specifically, the report is to include “. . . recommendations for improving transportation statistical information.” This chapter, in response to BTS’s congressional mandate, focuses on public dimensions of transportation statistics.

The Importance of Data

The need for data has been a continuing theme throughout the extensive history of transportation statistics (box 2). A long period of increasing interest in transportation statistics reached a zenith in 1977 with major data-collection activities in all modes of transportation, the publication of comprehensive analyses of national transportation needs and a national transportation atlas, and a joint program of multimodal data collections by the Department of Transportation (DOT) and the Census Bureau of the Department of Commerce.

Transportation statistics entered a period of decline after 1977 as deregulation and shrinking budgets brought many federal programs to an end. Comprehensive national analyses of transportation were not conducted by the federal government between 1979 and 1989. Nor were national multimodal data on commodity flows collected between 1977 and 1993. However, the demand for this information remained strong, as was reflected in various mandates placed on BTS when it was established by the Intermodal Surface Transportation Efficiency Act and then reauthorized by the Transportation Equity Act for the 21st Century.

Underlying the importance of transportation data is the knowledge that data are key tools for the work of the transportation community: for making informed policy decisions; supporting rules and standards; creating, evaluating, and changing programs; effective planning; and conducting research. Fundamentally, without good data, the transportation system cannot be properly assessed and appropriate strategic changes made to enhance its performance.

Because changes cannot always wait for good data and the appropriate analysis that flows from it, transportation decisions are sometimes made today using data that are inferior. Knowing this, BTS has striven throughout its 10 years to change this situation, to assure that transportation data are relevant, timely, comparable, complete, high quality, and useful. Bad data can mean faulty decisions. Conversely, when data are unimpeachable, they enhance objectivity and draw attention to matters that might otherwise be missed. Good data can focus contentious policy debates.

Still, good data are often unavailable because they are expensive to collect. The Commodity Flow Survey (CFS), the core federal program for collecting freight movement data, costs several million dollars to produce. Despite its relatively high cost and efforts to improve it, the CFS has serious limitations. It does not cover all freight movements, lacks important geographic detail, and is only available every five years. CFS brings to attention a problem facing other significant data-collection efforts in transportation: how to assess the benefits of more or new data-collection efforts against the costs of data collection itself. A strong argument can often be made that the cost of a mistake because of unavailable or bad data can be far larger than the cost to develop appropriate data systems. A single highway project, for instance, can cost millions of dollars more than the cost of gathering a full set of nationwide data on flows of cargo shipments. With apologies to Roger Bacon: He who has no data cannot learn the other sciences . . . and what is worse, they know not their own shortcomings nor their proper remedies.¹ Bacon was referring to mathematics, but, without data, decisionmakers may not know the shortcomings of their policies or how to construct proper remedies.

Assessing the costs and benefits of data collection poses a challenge to statistical agencies that are the producers, custodians, and disseminators of data. A relatively new statistical agency like BTS, which has been charged by Congress to identify what a comprehensive system of transportation statistics might be, has to judge not only what data might be useful but also whether the benefits justify the costs. In transportation, benefits may often have to be assumed, especially in the absence of data that can reveal them.

To produce good data, the fragmentary nature of transportation institutions must be overcome. Many of the major transportation issues today cut across modes and political boundaries. Solving these problems may require multimodal solutions, including either intermodal transfers or a better allocation of origin-to-destination (O–D) flows across competing modes. For instance, increases in congestion currently impact the cost-effective movement of both people and freight, with subsequent negative effects on the economy, the environment, and energy consumption. Sustainable solutions to congestion mitigation will also involve multiple modes, and identifying the most promising solutions will mean finding improved ways of comingling data sources across the different modes.

Those who collect transportation data are often constrained by past history. Much local, state, and national data cannot be merged to produce larger pictures of transportation status and needs. There are highway, air, railroad, and maritime accident and fatality data, but comparisons are risky because data definitions and collection methodologies differ. Passenger and freight data exist but not for every mode in comparable fashion. Institutions can rise above this “stovepiping” of transportation data by, for instance, finding ways to genuinely cooperate with each other, but often there are disincentives to making the necessary changes. It will take time and resources to accomplish a more integrated transportation data system, but savings will accrue in the long term.

Finally, a good data system needs to be agile. It must produce timely data and be flexible enough to adjust its orientation as the needs of transportation shift. Much of transportation lies within the private sector where the pace of change can be rapid. In such a context, timely data focused on changes in the mix of modes, geography, and demand for transportation in relation to supply has never been more important.

Today’s Transportation Data System

The present transportation statistics system consists of an array of data systems each constructed for specific, sometimes narrow purposes. These systems exist much like a collection of pieces from different jigsaw puzzles of the same picture. The pieces answer some questions well but leave many others unanswered or partly or poorly answered. The pieces do not constitute a whole because of a number of factors, including conflicting data users needs; incompatible definitions; diverse collection methods; and data overlaps, omissions, timeliness, coverage, and apparent inconsistencies. Many of the most pressing transportation data problems faced by decisionmakers when BTS was formed a decade ago have been addressed. The following discussion and its contrast with a visionary system suggest that important challenges remain.

Data Users

The transportation community has a highly diverse set of data users (box 3) whose needs do not always complement one another; in fact, they can be in conflict at times. No one can realistically provide all data in all the accessible forms to all users, nor can anyone easily select an optimal subset of users on which to focus data efforts. However, by concentrating on finding broad solutions to data needs, providers might be able to satisfy many users. For instance, an Intelligent Transportation System can capture information an operator can use to manage urban traffic flow. These data can also be used for measuring performance of the road system and for validating planning models. Then, if the data are archived, they would allow highway planners to identify areas of excessive congestion to determine project priorities or researchers to determine parameters for developing traffic flow models.

This approach suggests that the process of identifying data needs be a collaborative one involving all potential stakeholders. Further, it means moving away from the concept of data owners who create and maintain systems for their own purposes and only reluctantly consider the needs of others. Instead, data stewards could focus on designing systems with as wide an input as possible with the ultimate aim of sharing data to the maximum extent possible. Even then, some conflicts are inevitable. For instance, the public may be in favor of having highway monitoring systems that permit operators to reroute traffic in response to an incident. They may even agree to have that same data archived so that planners can identify trouble spots requiring infrastructure adjustments. But, the public is often reluctant to let enforcers have access to that same data if the intent is to use it to identify and track movements of specific individuals.

Standard Definitions

Issues of data comparability abound and can stem from differences in levels of detail and purpose among data collectors. The federal government may be primarily interested in national-level data, while state and local governments may want similar data but on a regional or local basis. Local and regional data may not allow aggregation for analysis of national characteristics and trends. These data are often developed in ways that lead to incompatibilities among localities or regions. Federal collections, which are also often developed without consulting a full range of users, tend to lack data specific enough, in content or quantity, to meet local needs. International data may not be comparable among countries, making comparisons misleading even though they are often made.

Both the public and private sectors need and collect data, often the same type of information, but not always for the same purposes. Each can be unwilling to share with the other. Industry may not want government, especially regulators, to know any more than what the law says government is entitled to know. They are also wary about competitors getting information that could shed light on their operations or plans. Regulators may not want the private sector to have access to operational data. Businesses and trade associations that collect, package, and sell data sometimes compete with governments that either charge less or tend to give data away.

Much of the conundrum over data comparability comes down to standards. A common misperception about standards is that everything has to be identical: hardware, software, and communications systems. In today’s world of information technology, this is not true. The critical issue revolves around the lack of standard definitions for the data. Examples are numerous. There is no common definition of a transportation fatality across all transportation modes. Buses are defined differently by various DOT administrations. Different maritime organizations use a variety of vessel classification schemes. Without standard definitions, combining or comparing data elements is extremely difficult if not impossible. Software may be able to match up datasets that report data in different formats, but it is not so easy when the relationships are not straightforward. Coordination and cooperation are key. Agreement among data collectors, managers, and users on common definitions, data elements, and structure would resolve most incompatibility problems.

Suboptimal Data

There are a number of ways in which data collection results in suboptimal data. Two examples are federal government mandates that call for data submission without funds to cover the cost of reporting or that fail to provide something in return for the reporting effort. While DOT often provides transportation funding to states, these funds are seldom tied to data requirements. Thus, states develop data systems that fit their own needs and budgets, resulting in data that may only generally conform to the mandate.

Industries or others are required by regulation to submit certain data, some of which they may already collect individually for their own needs. However, if the government does not provide easy access to the industry-wide data that results from the mandate or is not timely in making the data available, then the private sector gets little in return, leaving it with minimal incentive to provide data other than to avoid punitive action. To improve data availability, BTS’s new TranStats database is intended to provide “one-stop shopping” for transportation data. As such, it could provide industry a tangible return on the effort expended to comply with mandated data-reporting requirements.

Suboptimal data can also result when data collection is not the primary focus of those given collection responsibilities. For instance, the police officer at an automobile accident scene must ensure the safety of the victims and property, protection of potential evidence, and traffic management before gathering highway traffic safety data. This suggests that data-collection procedures should be designed, where possible, in ways that do not interfere with other, more important tasks. Even then, collection may result in data shortcomings or inaccuracies. In the safety arena, commonly known data gaps include lack of detail about motor vehicle crash scenes, the people involved, crash causes, and the severity of injuries. However, seeking alternative data-collection methods and sources may be more appropriate rather than adding burdens to crash site responders. Insurance companies and medical service providers, for instance, may be sources of more detailed damage and injury data, although confidentiality issues would likely have to be addressed before data could be shared.

Cost-Effectiveness

Data budgets have to compete with other priorities within government agencies, industry, or other organizations. Difficulties in assessing positive outcomes from data use can lead to minimal levels of funding. The entity that does pay will expect to have the final say on what, where, when, and how the data are collected and used. This can result in stovepiped data systems where the developer optimizes the design to meet its organizational needs and pays little heed to other possible uses of the data. Cooperative efforts can help avoid this, as exemplified by the National Household Travel Survey. This project, which surveys 25,000 households to develop a national picture of travel habits and patterns, is jointly funded and managed by the Federal Highway Administration and BTS. While the survey is not large enough to ensure adequate coverage for analysis much below the national level, the survey instrument is made available to states and metropolitan planning organizations (MPOs) to collect more regionalized data. The state or MPO provides the funding for an addition to the survey and gets the desired data at less cost than if it developed and administered its own comparable survey. This approach also allows for comparisons between MPO and national data.

When decisionmakers do not have good data, they manage without it. Projects still get approved and funded, and some level of improvement in transportation occurs. The expense of additional data collection and analysis may not, thus, appear necessary. However, poor data do not generally result in the most cost-effective solutions. A Catch-22 situation can result. Without proof that the data would be beneficial, better data collection may not be approved. Without the better data, proof of its usefulness may not exist.

Frequency

What is the right frequency for data collections? The easy answer is that it depends on the use of the data, but there are other factors. The CFS is a nationwide survey of shippers conducted by the Census Bureau in partnership with BTS. To date, the survey has generated freight transportation data for 1993 and 1997, and the next set of data (covering 2002) will be released in 2003. Some say this five-year cycle is sufficient since the federal government produces an economic census every five years, DOT’s legislative reauthorization occurs about every five years, and the planning process runs over a five-year period. Having commodity flow information every five years to measure how the national transportation system is being used by all modes and to determine if performance is improving or declining is, in this view, adequate. However, those who need freight flow information for local infrastructure assessment or for building a business strategy do not agree, because five-year-old data are too stale for their decisionmaking processes.

One way to overcome this difference of opinion would be to conduct multiple surveys: a nationwide survey every five years for federal government purposes and others done more frequently by state or local governments and by industry. However, this proposition is costly and can result in data incompatibility problems, as discussed earlier. Once again, a coordinated approach involving data users in different levels of government and in industry could produce less costly but unified data that meet a variety of user needs. A modified CFS with a smaller sample size, collected more frequently, may meet the need for more timely data and be aggregated at five- or six-year intervals to provide a more comprehensive picture of freight flows. This approach requires breaking with tradition and adopting innovative solutions but has the potential to meet more needs at a reasonable cost.

Comparability

When data users get a different answer to the same question, they rightfully complain about a lack of comparability in data. The reason, however, often relates to differing sources and the status of data rather than fundamental problems with the data.

Multiple data sources that cover the same topic will not necessarily give the same answer. For instance, a user can get foreign waterborne commerce information from the Census Bureau’s U.S. International Trade in Goods and Services report and the Journal of Commerce’s Port Import/Export Reporting Service (PIERS) database. The Census data are generated from trade-based data, while the Journal of Commerce data are from vessel manifests. Data from different collection methods can be used to check the quality of each system, while centralized data distribution can reduce user confusion. The Office of Management and Budget designated the U.S. Army Corps of Engineers as the central collection agency for the U.S. Foreign Waterborne Transportation Statistics program. The Corps has access to both trade- and .manifest-based data, knows the strengths and deficiencies of each, and can combine the information from both sources to give the most complete picture of import and export cargo movement.

A different type of inconsistency results from the use of preliminary versus final data. Preliminary data releases allow for timelier but lesser quality data. The National Highway Traffic Safety Administration (NHTSA) publishes an early assessment of traffic fatalities each spring covering the previous calendar year. These data are revised at a later date when all fatality information has been reported and the data have gone through NHTSA’s data quality validation process. Preliminary data are extremely valuable to those who need information for performance monitoring or planning purposes. Timely indicators can identify problem areas and result in early interventions. Decisions can be made sooner with preliminary estimates, with the understanding that timeliness is being balanced against greater accuracy.

Omissions

Missing data occur for a number of reasons (box 4 and box 5) and result in an incomplete picture of who and what is transported. Existing data collections are often either too general to break down to the level of specificity users desire, or they do not adequately cover subjects of interest. For instance, little is known about some aspects of the usage of public vehicles, such as ambulances, police vehicles or garbage trucks; retail vehicles, such as delivery trucks; or private cars used as delivery vehicles. Data on commuter air carriers and air cargo is not as extensive or consistent with that collected from the larger passenger air carriers, yet commuter jets and air cargo operations have become significant elements of the air transportation system. General aviation and recreational boating, after highway vehicles, account for the most transportation fatalities, yet exposure data are limited.

Missing elements generate questions that cannot be answered: What are the travel patterns of the elderly, the disabled, low-income households, pedestrians, bicyclists, recreational boaters, and so forth? How can exposure to risk be calculated if how often and how much they travel is not known? How many large truck, delivery, emergency, and service vehicle trips take place each day? When do they occur and what routes do they take? How can their impact on congestion be calculated if how often and how much they travel is unknown?

These questions reflect an interest among data users to target specific segments of the population and transportation users to ensure that their impact on the transportation system and the system’s impact on them can be measured and appropriate action taken. Filling gaps in the behavioral data are important: to federal, state, and local governments to determine allocation of resources; to business and industry to determine market strategy and operating policy; and to the public to address issues of equity and safety of transportation services. New data collections or modification of existing methods will be necessary to provide a more complete picture of U.S. travel patterns.

Intermodalism

Effective movement of both people and freight can involve multiple modes of transportation. These types of trips are poorly represented in current transportation data. Sometimes, this can occur because of the way questions about travel are posed. Prior to September 2001, policymakers were very concerned about the apparent growing congestion in air travel resulting in air flight delays. BTS has focused on improving data collection and dissemination on this specific issue. However, part of air travel involves getting from city centers or other origins to airports by other modes of transportation; it is the combination of modes and how they are integrated that determine the true length of a trip for an individual. Similarly, multiple modes of transportation are commonly used to move freight shipments from their initial origin to final destination. However, these intermodal data are not readily available. Each modal portion is often captured but in data systems with different formats, definitions, and data elements, making it difficult to integrate the data into a single trip (box 6).

Data Focus: Prevention v. Survival

Datasets are generally collected with a particular, and usually narrow, focus in mind. This narrow focus will supply answers to some questions but can ignore important related issues. The best examples of this situation are in the area of safety data. All modes of transportation capture extensive safety data, particularly on accidents, however, each mode may go about it in different ways for different purposes.

Aviation accidents are few in number but often result in loss of life. The National Transportation Safety Board (NTSB), accordingly, does an exhaustive job of investigating crashes to determine why they happened. On the other hand, there are so many highway traffic accidents each year (ranging from minor fender-benders to fatal crashes) that a great deal of attention has been paid to collecting survivability information. This disparate focus has left both modes with data gaps. Limited data are captured on aviation passenger survivability leaving NTSB analysts unable to conduct indepth research on how to make aircraft safer for passengers during crashes. Conversely, if limited data are collected about causes of highway accidents, traffic safety researchers could be left with a poor understanding of how to prevent highway accidents.

Security Data and Data Security

Overlaying all of these transportation data issues today is how to achieve a balance between the need for security data and data security. There is currently a paucity of transportation security data available, especially in a consolidated fashion, on costs, incidents, and critical infrastructure. Prior to September 2001, security concerns about transportation infrastructure focused on military deployments; that is, making sure the routes to get military personnel and supplies to destinations overseas were kept open. Now, security issues are centered on potential disruptions of infrastructure and impacts on the physical and economic well-being of the country. This new focus requires more extensive information on transportation routes, system capacity, and vulnerabilities.

Meanwhile, concern about potentially damaging uses of data has led to restrictions, for security purposes, on the release of data. Data about transportation infrastructure, particularly geographic information, are not as readily accessible as they once were. After September 2001, the White House issued a memo requesting that federal agencies review the information they make available on the Internet to safeguard potentially sensitive data. More broadly, agencies now follow Department of Justice guidelines when reviewing requests under the Freedom of Information Act.

BTS: A Leader in Transportation Statistics

The primary role of BTS, as expressed in its mission statement, is “. . . to lead in the development of transportation data and information of high quality and to advance their effective use in both public and private decisionmaking.”² Legislation granted BTS a leadership role in the domain of transportation statistics but not authority over the data programs of other transportation administrations. While BTS spends almost half its budget on data collection, the bulk of transportation data are collected by other DOT administrations, federal agencies, and nonfederal entities, both public and private. Thus, BTS plays a coordinating role, helping to overcome the complexities of integration among levels (e.g., local, national, and international) and types of data and data that cut across modes.

Data Systems Coordination

Given the decentralized nature inherent in the national transportation data system, greater coordination between data users and data collectors is needed. BTS and other federal agencies need to play a prominent role in ensuring that data gathered by state and local agencies use comparable national definitions.

In recent years, BTS has taken on a number of functions aimed at coordination, including: development of TransStats, the Intermodal Transportation Database; geographic information systems (GIS) for transportation; and the Safety Data Initiative. Also, to enhance coordination and the flow of data and information among data producers and users, BTS maintains the National Transportation Library (NTL).

TranStats, the Intermodal Transportation Database. TranStats is a network-based portal to the wealth of transportation-related data collected by DOT as well as others outside DOT. The aim is one-stop shopping for transportation data, and ultimately—in conjunction with the NTL—one-stop shopping for all of the information needed to carry out transportation research. The premise is fairly simple. By reducing the overall amount of time needed for data gathering, more time is available for analysis, and by providing easy linkages across datasets, new insights are facilitated. Having all of the data in one place also provides side benefits (and challenges). It potentially exposes discrepancies in definitions, differences in schemes, and data gaps—offering new opportunities for improving data quality, comparability, and coverage. It also provides an opportunity to more easily develop standards for presentation and documentation, to make transportation data more usable.

The most prominent feature of TranStats is the scope of its data. BTS plans to eventually include all of the major datasets within DOT, as well as a variety of demographic, economic, and social data, to enable wide-ranging analyses. TranStats also will contain powerful web-based tools to look at the data, including the ability to construct tables, graphics, and maps and do selective downloads.

Geographic Information Systems. Because of the spatial nature of transportation, geographic displays are an ideal way to analyze travel data and can present compelling pictures for decisionmakers. BTS creates, maintains, and distributes geospatial data through the National Transportation Atlas Database program. These data are obtained from multiple sources and include the National Highway Planning network, a national rail network, public-use airports and runways, and Amtrak stations. In the near future, layers will be added for land use, waterways, and transit. Together, the data comprise the transportation layer of the National Spatial Data Infrastructure. BTS distributes transportation geodata and a. number of geographic reference files including state, county, congressional district, and metropolitan statistical area boundaries.

To coordinate the development of GIS data, standards, and tools within DOT, BTS created a Geographic Information Working Group. BTS is also partnering with other federal agencies to share geospatial data over the Internet and is building geographic information systems into the design of TranStats to provide dynamic mapping of statistical information.

Safety Data Initiative. BTS was the lead agency in a DOT-wide effort to improve safety data. Four working groups were established with team members from all transportation modes (i.e., air, rail, highway, water, and pipelines) and other federal agencies, as well as from academia. The working groups developed plans for 10 research projects.

National Transportation Library. BTS maintains an electronic “virtual” library, the NTL, that is accessible through the Internet. The library provides broad access to the nation’s transportation research and planning literature. Currently, NTL contains over 150,000 documents and abstracts for another half million. NTL also maintains the DOTBOT search engine, indexing documents from 170 DOT websites. Through its partnership with the Transportation Research Board, NTL provides access to over 420,000 bibliographic records in the Transportation Research Information Services (TRIS) Online database.

Data Collection

As has been mentioned, good data are needed for effective transportation decisionmaking at all levels of society. Data for freight and passenger movements by mode, for instance, enable policymakers to estimate investment needs, track economic trends, and assess the financial health and performance of the transportation system.

BTS is responsible for several national-level datasets. The National Household Travel Survey (NHTS) is being conducted for 2001/2002 in partnership with the Federal Highway Administration. The 2002 Commodity Flow Survey is being done in partnership with the Census Bureau, following CFS data produced for 1993 and 1997. To improve freight data, BTS has considered an annual freight survey, which would provide more timely, complete, and detailed O–D commodity flow data and other types of freight traffic volume and shipment cost data. This new survey would include sectors now excluded in the CFS and supply more detailed data at the metropolitan level than is currently available. As a first step, the agency has asked the Transportation Research Board to conduct a 12-month study, “Freight Transportation Data: A Framework for Development,” to offer expert advice on the development of the new survey.

At the international level, BTS tabulates, analyzes, and disseminates monthly North American land trade flow data, which are collected by the U.S. Customs Service and processed by the Census Bureau. These data provide information on commodity type by surface mode of transportation (rail, truck, pipeline, mail, and other). In addition, they include geographic detail for U.S. exports to and imports from Canada and Mexico. The information is used to monitor freight flow changes under the North American Free Trade Agreement, as well as for trade corridor studies, transportation infrastructure planning, marketing and logistics analyses, and other purposes. Similarly, BTS also tabulates, analyzes, and disseminates monthly passenger border-crossing and entry data collected by the Customs Service. These data provide information on the number of passengers and vehicles entering the United States across the northern and southern borders.

For air passenger travel and freight movements, BTS (through its Office of Airline Information) collects and publishes monthly ontime airline data, as well as more extensive monthly operating data for both domestic and foreign airlines. BTS also collects detailed financial statistics for domestic airlines and various statistics on service quality. The data reporting is mandated by law, and several issues are now driving changes in the reporting regulations. Prior to September 2001, public concern about airline delays led to legislation requiring better data on the causes of delay, and in mid-2002 BTS was in the final stages of rulemaking on data collection that would cover causal information. BTS also has been working for some time to modernize the data-collection program, bringing it up-to-date with changes that have occurred in the airline industry and with advances in information technology.

Airline data collected and compiled by BTS include:

• U.S. air carrier financial statistics (quarterly and annually);
• U.S. air carrier traffic statistics (monthly, quarterly, and annually);
• U.S. air carrier passenger origin-destination, itinerary, and ticket pricing data (monthly, quarterly, and annually;
• foreign air carrier traffic statistics (monthly);
• U.S. airport activity statistics (quarterly and annually); and
• U.S. major air carrier ontime and flight delay data (monthly).

BTS supported DOT’s Office of the Secretary in its review of claims for and decisions on payments to air carriers under the Air Transportation Safety and System Stabilization Act, enacted after the terrorist attacks on September 11, 2001, to aid the airline industry. BTS support included data processing, claims review, and data validation and analysis. By the middle of 2002, DOT had authorized the payment of almost $4.3 billion to air carriers.

BTS, through its Office of Motor Carrier Information, manages a mandatory data-collection program of financial and operating statistics.³ All trucking companies with gross annual operating revenues of $3 million or more are required to file annual reports, and those with revenue of $10 million or more are also required to file quarterly reports. In addition, all bus companies with gross operating revenues of $5 million or more are required to file annual reports. Types of data collected from trucking companies include:

• company name and identifying motor carrier numbers;
• company’s segment of the trucking industry (“revenue commodity group”);
• annual revenue, expenses, and net income;
• annual driver and helper wages;
• annual miles traveled, total number of shipments, and ton-miles; and
• the number of drivers with and without commercial licenses employed and the number of trucks and truck-tractors the company operates (owned or leased), as of the end of the reporting year.

These data are widely used in the private and public sector by motor carriers for benchmarking and competitive analyses, academics for scholarly analyses and to train future trucking industry executives, law firms for expert testimony in court cases, federal and state government agencies for studies of the trucking industry, consulting firms, and trade journals and other publications to show rankings and business information for individual trucking companies. BTS plans to make annual report data (1999 and thereafter) available electronically via TranStats. Data users will then be able to extract data they need by individual company and industry segment or access the entire annual data series for analysis using statistical analytical software.

The monthly Omnibus Survey is coordinated by BTS for offices in DOT, enabling data collection on the transportation system, how it is used, and how users view it. The survey provides timely, high-quality data on issues related to safety, security, mobility and access, the human and natural environment, and economic growth to support informed planning and decisionmaking. In addition to monthly core questions covering DOT’s strategic goals, administrations can add questions to the survey. These questions typically cover specific events or issues of interest to the various DOT administrations or measure public reaction to issues like fluctuating fuel prices, seat belt use, airline service, or boating safety. In addition to the Omnibus Survey, BTS conducts occasional special topic surveys. For instance, after the terrorist attacks of September 2001, BTS conducted a survey to assess the public’s intentions for traveling over the holidays and their expected mode choices and in early 2002 surveyed the public’s perspectives on government efforts to improve transportation security.

Compilation, Analysis, and Dissemination

BTS compiles extensive data from diverse sources into collections relevant for policymakers and other transportation data users. These compilations range from sets of data tables to presentations of data with analyses, and include:

• Transportation Statistics Annual Report, prepared under BTS's le’gislative mandate, covers nearly 100 transportation topics, analyzing time series data and recent developments.
• Transportation Indicators, available monthly on the BTS website,⁴ tracks over 130 indicators.
• National Transportation Statistics, an annual publication with over 250 data tables, is organized into four broad categories (i.e., system, safety, economy, and energy/environment) and is available in hard copy and on the BTS website.
• Pocket Guide to Transportation, an annual pocket-sized booklet of key transportation data presented in tables and figures.
• North American Trade and Travel Trends (2001), a data and analysis presentation of recent trends in U.S. trade and passenger travel with Canada and Mexico.
• U.S. International Travel and Transportation Trends (2002), an overview of U.S. international and regional travel trends between 1990 and 2000, plus significant changes in air travel since September 2001.
• Maritime Trade and Transportation (2002), an overview with data and analysis of maritime issues.
• State Transportation Profiles, presentations of individual state transportation data from federal and other national data sources. The first edition in this series, covering all 50 states and the District of Columbia, will be issued during 2002 and 2003.
• Government Transportation Financial Statistics (2002), a trend analysis of federal, state, and local transportation revenues and expenditures, is available on the BTS website.

In addition to the analysis conducted for these and other BTS publications, the agency is engaged in a number of focused transportation studies. These include studies of leading transportation indicators, productivity measures in various transportation sectors, and transit availability. BTS is also working to develop measures of sprawl, as well as measures for DOT Strategic Outcome goals. These latter measures cover, among others, transportation-related deaths and injuries, access to transportation systems for individual users, travel costs and times, the U.S. international competitive position in transportation goods and services, and transportation dependence on foreign fuel supplies.

BTS and the Bureau of Economic Analysis (BEA) in the U.S. Department of Commerce developed Transportation Satellite Accounts (TSA), which provide detailed information about transportation’s contribution to the Gross Domestic Product (GDP). A key feature is estimation of the value added to the economy by the in-house transportation sector (transportation undertaken by firms in the nontransportation sector of the economy, such as trucks owned and operated by grocery chains). Before the TSAs were developed, reliable estimates of this value added were not available. BTS and BEA have also been developing a method for capital stock accounting to measure the value of the nation’s transportation infrastructure, as directed by the Transportation Equity Act for the 21st Century (TEA-21.)

Filling Data Gaps

Gaps in data may involve the absence of data, data that are of poor quality, or data that are collected but not provided in a timely manner or in a form that a decisionmaker can use. For example, a known major data gap is the absence of good inland O–D data covering traffic moving in international commerce. In 2001 and 2002, BTS comprehensively assessed gaps in transportation data and the benefits and costs of possible solutions. This project was conducted in consultation with major stakeholders including those within DOT and among congressional staff, state DOTs, metropolitan planning organizations, the transportation industry, and research organizations.

Solutions to several critical data problems are being planned or are underway in BTS. Surveys of bicycle and pedestrian travel and of persons with disabilities will provide information on demographic groups for which little data has been collected in the past. The planned American Freight Survey will fill gaps in coverage to provide data on freight flows that were not captured in past surveys. It will collect information on travel costs and times to identify bottlenecks that are vital in the context of national competitiveness and on containerization useful for security purposes. The National Household Travel Survey will provide improved travel data on trips in the 50- to 100-mile range. Implementation of Safety Data Initiative recommendations will reengineer safety data systems to reduce redundancy and improve quality and timeliness. This will result in uniform reporting of fatality and accident data and allow comparability across modes of transportation.

However, other gaps exist and solutions have yet to be designed. There remains an incomplete picture of hazardous materials transportation due to the lack of data identifying shippers, carriers, and the transportation workforce involved in the industry. Also needed are better data on the rapid developments in the transportation requirements of service industries and effects of e-commerce on just-in-time delivery systems on these and other sections of the freight-generating economy. Little data exist on the travel characteristics of those involved in recreational boating. The number, characteristics, and their contribution to traffic flows are unknown for certain types of motor vehicles such as those providing municipal services, for example, ambulances, municipal trash haulers, and government motor pools. Transportation workforce labor hours are not captured for all segments of the transportation industry making it difficult to conduct analyses of economic issues or safety concerns, such as fatigue. These, and several other, gaps will be addressed in the Data Gaps Final Report due to be completed in 2003.

Assuring Data Quality, Good Statistical Practice, and Measuring Results

Legislation requires BTS to issue guidelines for DOT data collection to ensure that transportation data are accurate, reliable, relevant, and in a form that permits systematic analysis. In addition, the Office of Management and Budget issued a requirement in 2001 that agencies develop information quality guidelines. As an active participant in the Interagency Council for Statistical Policy working group, BTS has the lead role in developing these guidelines for all of DOT.

As part of these responsibilities, BTS developed the portion of the new DOT information guidelines that cover statistical information. These guidelines applied to all of DOT as of October 1, 2002. In addition, BTS will use the guidelines as a foundation for a more comprehensive Guide to Good Statistical Practice. This guide will be a handbook for transportation data program managers and analysts on all aspects of data quality, including data system planning, collection, processing, analysis, interpretation, dissemination, and evaluation.

BTS also has an ongoing data quality assessment project. In 2001, the agency assessed 5 DOT data systems (in conjunction with the Safety Data Action Plan) and plans to assess 10 more in 2002. The databases reviewed in 2001 included hazardous materials incidents and enforcement actions, airline passenger travel, transit safety and security, and airline safety. In addition, BTS assisted the Office of the Secretary of Transportation in a review of data submitted by air carriers to support claims for compensation after the September 11 shutdown of the air traffic system.

In accordance with the Government Performance and Results Act, DOT maintains a performance measurement system. BTS provides technical support for the development of performance measures, analysis of performance data, and reliability assessment. As part of this work, BTS develops verification and validation plans and coordinates with DOT agencies to develop “data details” that describe the scope and limitations of the data elements.

The Future

In BTS’s vision of the future, data and information of high quality will support every significant transportation policy decision, thus advancing the quality of life and economic well-being of all Americans. BTS plans to be at the focal point of this vision, to develop its capabilities such that people will come to BTS before starting a planning effort or transportation policy study because the Bureau has good data and the information they need.

To be that focal point, BTS will have data ready for every significant policy analysis. BTS will be agile, assuring that data cover emerging trends in transportation. The data will be good, clean, and timely. The data will also be easy to get and use and be complemented by analysis. BTS will accomplish this, not alone, but as part of a team or network of data collectors and providers, both public and private.

In essence, the BTS goal is to make transportation better—to enhance DOT’s strategic goals: security, safety, mobility, economic growth, and the human and natural environ-ment.

Footnotes

¹ This thought is reminiscent of Bacon’s work, On Experimental Science, published in 1268.

² U.S. Department of Transportation, Bureau of Transportation Statistics, “A Strategic Plan for Transportation Statistics (2000–2005),” March 2000, available at http://www.bts.gov, as of May 2002.

³ 49 CFR 1420. The Interstate Commerce Commission collected financial and operating statistics data from the time that the Motor Carrier Act of 1935 went into effect until 1994, at which time BTS took over the data collection.

⁴ Available at http://www.bts.gov.