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62.1 Barriers and Challenges to Freight Data Sharing The following categories of barriers to freight data sharingâand to success in obtaining proj- ect approval or required funding in other public-private partnershipsâwere identified in the research and are shown in Table 2.1. 1. Legal Barriers. In some cases, there are laws that interfere with the ability to share data or complete a project. Legal barriers might include contract law or might be national privacy laws that restrict what information can be requested. Legal barriers are difficult to overcome because they require a contractual or legal remedy. 2. Resource Barriers. The lack of resources is a common barrier. This might involve lack of personnel resources, particularly at small private firms, to actually collect, sanitize, compile, or share data. Lack of funding also is a significant barrier in accomplishing data sharing, processing the data, and in keeping a project going smoothly. 3. Competition Barriers. Private firms are concerned that data about their operations might be used by their competitors to gain business advantage. While firms know they need to comply with regulatory requirements involving data, the companies are reticent to share data without protection of the details of their business and customers. 4. Institutional Barriers. The more parties there are in a project, the more difficult it is to work through all of the coordination issues. This is particularly true of projects that involve international borders with multiple federal, state/provincial, and local governments as well as private firms in the respective countries. There also are institutional barriers between private sector firms and public agencies. While usually easier to overcome than legal barriers, insti- tutional barriers take a great deal of time and use scarce resources. 5. Coordination Barriers. Somewhat related to institutional barriers, significant coordination is needed to achieve data sharing and to accomplish large public-private projects. Failure to coordinate with all stakeholders and failure to articulate why a project is being conducted and how it will benefit the various stakeholder groups can lead to failure of a project or a much longer and more expensive project or data sharing approval process. Table 2.1 lists the freight data sharing barriers, with generalized examples of projects that encoun- tered these problems. Detailed information about these projects may be found in Appendix A. 2.2 Motivators for Freight Data Sharing The research also identified a set of motivators that can help to overcome barriers to data shar- ing. The categories of motivators that promote or facilitate freight data sharingâand help proj- ects gain approval or required funding in other public-private partnershipsâare defined here. C h a p t e r 2 Barriers and Motivators for Freight Data Sharing
Barriers and Motivators for Freight Data Sharing 7 Table 2.1. Freight data sharing barriers. Barriers Examples Legal Lack of formal contract Programs utilizing truck GPS data at the national and state levels to support freight planning activities required a process to develop nondisclosure agreements and other protections of private data. This process, which required the use of attorneys, can be time consuming and costly. Lack of legal basis for public- private partnerships Public funds needed to complete infrastructure improvements are sometimes not available. However, public-private partnerships that can fund such improvements are not legally allowed in some states or political jurisdictions. Control of data by technology contractor If the contractor controlling the data is unwilling to release the data, freight tracking data cannot be shared with funding organizations, complicating their ability to effectively evaluate a project. National security sensitivities Due to security restrictions, customs agencies may not participate or provide data to international freight improvement or border crossing projects. Data sharing with foreign countries Some international projects have legal limitations on what data could be shared with agencies in other countries. Resource Small companies find it harder to provide freight data In some state level truck GPS projects, smaller firms did not have the resources to share their truck GPS data and the data was only acquired from larger GPS vendors. Smaller firms have also had limitations in their ability to participate in various U.S. Homeland Security freight data initiatives for import and export cargo. Funding uncertainties make it difficult to keep all partners interested in and committed to participation In general, having a good relationship with partners makes them more willing to expend additional effort and resources to participate in projects. Public-private partnerships in some regional areas found this to be the case. Limitations in data analysis that can be done with aggregated data In order to protect privacy, projects often release summary results based on aggregate data. Data source diversity, and in some cases the large amounts of data, required costly processing Many existing freight data sources need to be collated, compiled, and analyzed before they are useful. This particularly is the case for larger regional and national data sharing efforts and those that use technology data. Examples include studies based on truck GPS data and both domestic and U.S.-Canada corridor projects. Competition Sensitivity about sharing information which could be used by competitors This is a common concern for many projects where public agencies use private sector business data. This can impede a private companyâs willingness to participate in projects. A regional public-private partnership rail infrastructure project in Chicago had to address such concerns when they collected information from competing railroads. Disclosure of individual shipment or company data viewed as proprietary or business-sensitive Once public agencies have collected private sector data, they need to have a mechanism in place to protect the data. This is a common barrier found in many freight data sharing projects. Increased security data requirements may delay cargo Customs organizations have found that processes to collect data by scanning containers overseas is difficult to implement in part because it affects the efficiency of freight flows. Third-party data supplierâs validation and cleaning process not known Projects which collect freight data that has been provided by a third party can be a challenge to process and to understand. Some past freight analysis projects used GPS data that is prepackaged by vendors. The use of the data required additional validation before it could be used to support policy decisions. (continued on next page)
8 Freight Data Sharing Guidebook Barriers Examples Institutional Lengthy negotiation process to obtain approval for data sharing; extra time needs to be planned In addition to addressing data privacy concerns, the negotiation process can be needed to determine prices and set up funding arrangements. There are many examples of freight and border crossing analysis projects in North America that required a negotiation process. Private sector interests sometimes interfere with the public good Public-private partnerships are often needed for infrastructure projects. There have been projects in some states or regions in which conflicts between public and private sector interests have delayed the projects. Different facilities, such as border crossings, operate differently so may have different requirements A common freight data sharing issue. Freight data collected by one organization may not address the need of another organization. For example, Customs and Border Protection collects truck data at border crossings but this information is not in a format that is always usable by the freight community. Compatibility issues between national freight data sets For example, different commodity codes used in different national data sets can require additional processing in order to be compared. Some state and regional projects that involve freight forecasting must perform additional analysis to overcome differences among national data sets. Coordination Not articulating uses of data to private data providers Experience from several GPS-based performance measures projects at the national and state level shows that private sector organizations sharing freight data want to understand how their data will be used. There is a particular need to demonstrate that the data will not be used by government for regulatory enforcement. Lack of coordination with stakeholders Acquiring freight data requires working with the stakeholder community. Several border crossing facility improvement projects and some state or regional parking information system efforts would have been more successful with additional stakeholder outreach. Sharing across international boundaries is more difficult as is coordination with multiple international agencies This barrier is common with any project with freight data sharing across international boundaries. There are several examples in border crossing projects in the United States with both Canada and Mexico. Table 2.1. (Continued). 1. Nondisclosure Agreements. An important way to protect data and to assure that those with the data are willing to provide it is to execute non-disclosure or privacy agreements. These may be part of legal contracts or separately negotiated documents. 2. Stakeholder Engagement. It is incumbent upon project leaders, particularly public sector participants who desire data from other entities, to coordinate with everyone involved in a project. Coordination committees and numerous stakeholder meetings are important to the ultimate success of a project. 3. Funding for Data Sharing and Projects. An important motivator to project participation and to sharing of data is funding. The most successful projects are those where participants are reimbursed for their costs and efforts and where public and private money are brought to bear in accomplishing results. 4. Technology Innovation. Sometimes implementation of a particular technology makes it easier to share data and helps a project to succeed. An automated technology which could accomplish the identification of a transportation vehicle without requiring the divulging of certain data about that vehicle could be a motivator. 5. Scrubbing or Restricting Data. While often done as part of project coordination, the willing- ness of all parties to remove sensitive information from data to be exchanged or to restrict the uses that can be made of data can be important in gaining acceptance of data sharing.
Barriers and Motivators for Freight Data Sharing 9 6. Articulating Benefits of Sharing. It is important for project proponents to be able to explain to the public, to private sector participants, and to other stakeholders how they will benefit from the conduct of a project. Articulating benefits is an important part of coordination of a project. Sometimes publishing analyses of the expected costs and benefits of a project helps to assure its success. 7. Legislative Changes. Sometimes the introduction of legislation can overcome barriers and introduce protections of data that can then motivate firms and entities to participate in a project and to share appropriate data. Canada, for example, has a well-known national pri- vacy protection law that restricts the way data can be used. This protection is helpful in gain- ing participation from firms in projects. The relationship between barriers to data sharing and motivators that help projects succeed is shown in Figure 2.1. Table 2.2 lists motivators in more detail. Again, detailed project descriptions are available in Appendix A. These motivators became the basis for definitions of guidelines that constitute the bulk of the information in this guidebook. Barriers Motivators Legal Barriers Nondisclosure Agreements Resource Barriers Stakeholder Engagement Competition Barriers Funding/Cost Sharing Institutional Barriers Technology Innovation Coordination Barriers Scrubbing/Restricting Data Articulating the Benefits of Sharing Legislative Changes Figure 2.1. Relationships between barriers and motivators. Table 2.2. Freight data sharing motivators. Motivators Examples Nondisclosure Agreements Data agreements to allow multiple uses which ultimately lowers cost Freight travel measurements collected at some regional and border projects were usable by multiple stakeholders. Explicit inclusion of data sharing in formal contracts Contracts can be written which contain nondisclosure agreements and other protections of private data. These were used within most national and state truck GPS data projects. Standard nondisclosure agreements and memoranda of agreement The GPS truck data efforts developed nondisclosure agreements that could be reused to expand the data collection process. Stable contracting relationship with data provider The national and state GPS truck data at some border crossing had longer-term contractual arrangements that supported data sharing. (continued on next page)
10 Freight Data Sharing Guidebook Motivators Examples Agreement to maintain confidentiality of private sector data Such agreements are a common tool when freight survey data is collected using interviews. There are numerous examples of such agreements in state or regional freight studies. Federal agencies who work with the private sector make efforts to protect company-specific data and agree not to divulge cargo contents data. Third-party data is usually in cleaned format and simpler to acquire than directly collected data Using third-party data was found to be a resource- effective approach to gathering freight data for several corridor and border crossing projects, so long as the data supplierâs validation and cleaning process is understood. Stakeholder Engagement Extensive coordination with public and private stakeholders and gradual implementation of data acquisition is helpful. Coordinating meetings and committees is useful Stakeholder engagement was an important element in a number of successful freight data sharing efforts, including several border crossing travel time studies and regional public-private partnership infrastructure projects. Clear identification of purposes of data sharing. Understanding public uses may help providers share data Key national and state GPS truck studies clearly stated that the data collected would support freight system improvements. Trusted third parties (consultants or academics) as well as personal relationships with data providers; involvement of trade associations Including performing contractors who were trusted by public and private sector partners proved to be a benefit for freight performance measures projects at the national and state level and with freight innovation projects sponsored by the Federal Highway Administration. Funding for Data Sharing and Projects Joint public-private funding of projects Rail projects usually involved both public and private funding. This motivated both the public agencies at the state and regional level and the private railroad companies to participate. Funding to cover costs of data sharing and for infrastructure partnerships Some Federal and state agencies which sponsored freight analysis projects provided stipends to trucking companies to help with their costs of providing data. Government contracts (with funding) help, particularly long-term contracts The government funding of border crossing projects and some freight efficiency improvement projects helped offset costs and encouraged participation if there were fewer identifiable private-sector benefits. Funding to cover costs of data sharing If it costs data providers to share data and they do not otherwise perceive benefits, reimbursement sometimes helps. Government agencies sometimes reimbursed trucking companies in truck GPS projects. Using open source data or gathering data from volunteer stakeholder groups or round tables Such data lowers cost and reduces the need to set up data sharing agreements. Typically state and regional studies include the use of open sources or stakeholder groups as a first choice of data sources. Technology Innovation Some technologies do not require sharing agreements and are not intrusive on data providers No data sharing agreement was needed for RFID transponder use for the projects where RFID tags were already in use for toll collection. However, trucking partners needed to be involved in coordination. Manual surveys for truck counts do not require sharing agreements, nor do Bluetooth readers. Various Corps of Engineers and other government system programs and activities such as the Institute for Water Research provide data that is useful to the private sector. Table 2.2. (Continued).
Barriers and Motivators for Freight Data Sharing 11 Table 2.2. (Continued). Motivators Examples Usefulness of technology for other functions Some border crossing travel improvement projects used existing technology (RFID transponders and GPS) to develop border metrics for trucks. Some waterways and other transportation network projects used standard telecommunications technologies to provide transportation carriers with network status information. Private sector GPS data will become more available as more fleets have the technology and as GPS data read rates increase The conduct of national and state GPS truck projects helped increase the number of trucks with devices. These projects, and their successors, are likely to have access to better quantity GPS data in the future. Harmonize the freight data This already occurs with GPS data due to standards which facilitate data sharing. Several TRB research studies and DOT initiatives support freight data standards. Scrubbing or Restricting Data Scrubbing of individual shipment or company data from data to be shared; restricting data release to limited locations or in an aggregated format This occurred in most national and state vehicle tracking projects. These efforts needed to remove identifying information before data was provided to public agencies. Standardized interfaces or using same data collection technique as at other locations Some government systems have standard interfaces and facilitate private sector access to government data. Several national level freight analyses in Canada and Europe used common data and work at standardizing the sharing of freight technology data. Adding value to data and making it available to all stakeholders Several U.S. border crossing projects both with Canada and Mexico provided crossing time information that was of interest to a number of groups. Sufficiently protected data can lead to new markets for data providers The success of some GPS projects resulted in the purchase of data as part of similar studies in different regions. This, in turn, made the GPS vendor more willing share data with other agencies. System capability of restricting access to a companyâs data is an alternative to scrubbing data Truck IDs were scrambled by the vendor in several GPS truck studies. Federal data projects typically do not release specific vehicle or vessel identification information but generalize the location information. Articulating Benefits of Sharing Defining and articulating benefits and goals to stakeholders helps with data sharing and support of technology improvements This is common in many efforts where public sector agencies acquire freight data from private sector organizations. Often it is important to indicate the data will not be used for regulatory enforcement. Some waterways efforts share data for waterways operations rather than regulatory purposes. A stipulation that data is one-time use that canât be used for any other purposes such as regulation Used when obtaining private sector truck data for national and state GPS truck projects. (continued on next page)
12 Freight Data Sharing Guidebook Motivators Examples Favorable publicity for private companies and public visibility of accomplishments of a project. Peer pressure can also play a role Some Federal, state, and local freight improvement projects provided positive publicity that is valued by the participants. Indicating that sharing private data will support improved freight infrastructure decisions This approach works with agencies that have infrastructure responsibilities. There are numerous examples in the research by all the modes of transportation. Legislative Changes Laws on nondisclosure of data A Canadian law about protection of data made it easier for providers to share data in various projects without worry of disclosure issues. Table 2.2. (Continued).
